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Now that we’ve covered Security Incident and Event Management (SIEM) and Endpoint Detection and Response (EDR) in previous videos, you might be wondering which solution is best for your business. In many cases, the answer is both. Using SIEM and EDR together can greatly help to improve your company’s cybersecurity posture against threats, but they work in different ways. Chris Cummings, CEO of Petra Technologies, compares the features of these two cybersecurity essentials to help provide a better understanding of your options. (To learn more and see the full Cybersecurity Essentials List, visit this link: https://youtu.be/A50vRiJ_QVo) Want to add SIEM and/or EDR services to your company’s cybersecurity lineup? Contact Petra Technologies today!
A New Technique called ” Domain Fronting “ allow cybercriminals to hide the command & control Networks Traffic within a CDN. It acts as a mask for C&C networks and widely used advanced Technique for Malware Evasion. “A content delivery network (CDN) is a system of distributed servers (network) that deliver pages and other Web content to a user, based on the geographic locations of the user, the origin of the web page and the content delivery server.” This Method Affected by Many CND’s and major impact has been Identified in Akamai Technologies which carried the highly significant amount of traffic of various HIgh reputation domains through which we can mask our traffic. According to Akamai, their CDN carries 15-30% of the world’s web traffic, and it is extremely common to see outbound traffic to Akamai’s network from almost any potential target. This makes Akamai’s CDN a prime target for this new approach to domain fronting. Domain Fronting Working Method TOR Project used For Domain Fronting Tor Project used to implement the Domain Fronting to evade censorship in Different Countries where the internet Restriction that denies accessing the Particular Website which serves under the Content Delivery Networks. One specific Akamai domain (a248.e.akamai.net) was in use by the Tor project to bypass China’s internet restrictions and was later blocked in China, as it was used bypass the country’s content filtering controls.Cyber Ark said. Few months before CyberArk explained about this Domain Fronting says, There are 1000 of Domains are affected by this Domain Fronting Method includes domains for Fortune 100 companies. Two Requirements of Domain Fronting As an Attacker, you need two Requirements for Successfully implementing the DF For Evade the Traffic of Command & Control. - A two-way, persistent read-write mechanism (system or application) must be hosted by the CDN. Which means to utilize the list of an application hosted by the CDN to exchange instructions and data with Attacker. - Malware must be specially crafted to use this C2 channel, and users’ machines must be infected with this malware. Implementing Malware Command and Control CyberArk Conclude that This C2 evasion technique emphasizes the point that attackers, insiders or external actors, will find ways to establish a foothold within the network. The CDN could also give each domain virtual IP addresses that are tied to a specific SSL certificate. This stops malware from nesting in CDNs, but there are simply not enough public IPv4 addresses to make this happen. Also Read Hackers Increasing the use of “Command Line Evasion and obfuscation” to Spread Advance Level Threats Source : GBHackers
MTD / MARS (Mobile Threat Defense – Mobile Application Reputation Solution – Mobile Application Reputation Solution) The data contained in the end users’ mobile devices in the company is a risk due to mobile devices. In order to ensure the security of these risks, mobile device operating systems also need solutions to defend against threats. Along with mobile threat defense, end-user mobile devices can be secured in foreign networks where they are connected while they are outside corporate networks. Detection of the leakage of the data by means of harmful applications on the device can be realized. With the mobile application reputation solution, measures can be taken against possible threats or data leaks by following the movements of the applications in end user mobile devices. These motion streams allow measures to be taken to the data processing department when providing reports on threats. With MTD / MARS Solution; - Companies can provide security against network attacks on end-user mobile devices. Data leakage can be detected by entering traffic between devices connected to unknown networks. - Analysis of the applications of operating systems outside of global stores (Google, Apple, etc.) can be analyzed and any access is restricted in case of a threat. - Security of identity information such as keys and certificates on mobile devices can be provided. - Security measures can be taken by detecting the sensors on the device without using user information. - Access to the areas where personal data is kept on the user device can be monitored and access to threat applications can be reported. - Detailed analysis reports are given for applications in global stores, which application accesses to which data, where data is transferred, which perceptors are used and so on. security reports are provided. - If Mobile operating system is up-to-date and security vulnerabilities can be detected. - By means of identifying overruns through the mobile device, access to internal resources can be blocked by integrations. The MTD / MARS Solution is provided to the IT departments technically; 1. Security Threat Panel a. Monitoring of threats b. Device inventory c. Reporting potential threats 2. Device and Application Panel a. Detection of applications containing threats through the device b. Detection of device-based threats such as Jail-break / Root c. The threat of unknown source applications a. Writing security policies for threats b. Taking actions in case of threats and integrations MTD / MARS Features; • App. based threat protection • Network based threat protection • Device based threat protection • Custom threat policies • Threat dashboard • Data leakage control from apps. • Risky apps dashboard • Custom policies for risky apps • App. blacklisting • Enterprise app. review
An Introduction to Kubernetes Security using KubeArmor Introduction Kubernetes, often abbreviated as “K8s”, orchestrates containerized applications to run on a cluster of hosts. The K8s system automates the deployment and management of cloud-native applications Kubernetes security In recent times organizations are migrating from on-premise to cloud, owing to the multi-dimensional nature of today’s cloud-native technology landscape. Due to this, it is easier than ever […] Reading Time: 4 minutes Kubernetes, often abbreviated as “K8s”, orchestrates containerized applications to run on a cluster of hosts. The K8s system automates the deployment and management of cloud-native applications Kubernetes security In recent times organizations are migrating from on-premise to cloud, owing to the multi-dimensional nature of today’s cloud-native technology landscape. Due to this, it is easier than ever to build and deploy application environments quickly through containerization which has resulted in 45.6% of enterprises to use Kubernetes in their production environments, it is important for us to know how to secure it. Let’s Talk about why it is difficult According to this analysis, security is one of the hardest challenges of running Kubernetes. There are numerous moving layers in the cloud-native stack, hence we may not focus on security early on. By default, some distributions of Kubernetes may not secure. Prevention and Detection This has unfolded rampant increase in cyber attacks on the cloud. To mitigate this, we have to secure all the pods and containers which are simple platforms just like Windows or Linux or a MySQL database and are only as secure as you make it. There are some flaws in every system, including Kubernetes and Docker, but these security issues are caused directly or indirectly by the users and their applications. Kubernetes provides each pod in a cluster its own IP address and consequently, IP-based security is required. Moreover, cluster security demands: - Network policies - Access policies for individual pods - RBAC and namespace access policies, etc KubeArmor is an open-source tool that was created by AccuKnox and is available on GitHub<. It will operate with LSMs (Linux security modules) allowing it to run on top of any Linux platforms such as Alpine, Ubuntu, and Container-optimized OS from Google. KubeArmor will automatically detect the changes in security policies and it will be imposed on the respective containers without any human intervention. If there are any violations against security policies, KubeArmor immediately generates audit logs with container identities. KubeArmor provides a relay service that can be connected to if the user wants to connect the KubeArmor feeds for SIEM integration. Functionalities of KubeArmor include: - Restricting the behavior of containers at the system level - Enforcing security policies to containers in runtime - Produce container-aware audit logs - Provide easy-to-use semantics for policy definitions Setting KubeArmor up on Kubernetes Prerequisite: We need a working Kubernetes setup for this. We can use a cloud Kubernetes offering GCP or set yourself locally using minikube. If you are using minikube then we also require kubectl. The daemon-set has to be installed as part of the kube-system namespace thus giving it the rights to watch all the system events. Commands to install: Step #1: Deploy KubeArmor for GKE: With this KubeArmor should be running, to verify, you will see the pods you created in a moment. Before applying the security policy to the container or pod the annotations should be added to the deployment, under the metadata Sample deployment with annotations. An example of a security policy that is to block a process execution of the sleep command would be when you apply the policy it will block this particular command, we can get the audit logs of that security policy. KubeArmor Security Policy to block sleep command in containers during runtime. Find more about this on Sample deployment of Multiubuntu with KubeArmor. In this blog, we looked at the basics of Kubernetes security monitoring and how to set up the KubeArmor on Kubernetes which automatically detects the changes in security policies and enforces them on the respective containers without any human intervention, and sends the audit logs to their system admins. Now you can protect your workloads in minutes using AccuKnox, it is available to protect your Kubernetes and other cloud workloads using Kernel Native Primitives such as AppArmor, SELinux, and eBPF. Let us know if you are seeking additional guidance in planning your cloud security program. Must read articles - Zero Trust (ZT) – The Future of Cloud Security - Zero Trust (ZT) Architecture, Framework and Model - Cloud Security Governance, Risk and Compliance (GRC) - How to Pick the Right CNAPP (Cloud Native Application Protection Platform) Vendor - What is Driving the Need for CSPM (Cloud Security Posture Management) - Agent vs Agentless Multi Cloud Security You cannot secure what you cannot see. Your most sensitive information is stored on endpoints and in the cloud. Protect what is most important from cyberattacks. Real-time autonomous protection for your network's edges.
Christoforos Ntantogian, Stefanos Malliaros, and Christos Xenakis from the Department of Digital Systems in the University of Piraeus (Greece) conducted research on password hashing in open-source web platforms including the most popular content management systems (CMS) and web application frameworks. The results published in their paper were very disappointing from the security point of view. Many popular CMSs use insecure hashing by default. This means that if a criminal manages to get access to the database and download account information, they may relatively easily guess passwords and then perform privilege escalation, sell the passwords, or attempt to use them to compromise more websites (due to users often reusing passwords). Password Hash Security Considerations There are several elements that influence how safe the password hashing scheme is. The first element is the hash function. The MD5 function is now considered very insecure: it is easy to reverse with current processing power. The SHA1, SHA256, and SHA512 functions are no longer considered secure, either, and PBKDF2 is considered acceptable. The most secure current hash functions are BCRYPT, SCRYPT, and Argon2. In addition to the hash function, the scheme should always use a salt. A salt is a random element included during hashing which guarantees that every hash for the same password is different. MD5, SHA1, SHA256, and SHA512 functions do not include a salt and a separate function must be used to add the salt. On the other hand, PBKDF2, BCRYPT, SCRYPT, and Argon2 functions have integrated salts. The more times the hash function is applied, the more resources it requires to be reversed. MD5, SHA1, SHA256, and SHA512 must be iterated manually while PBKDF2, BCRYPT, SCRYPT, and Argon2 have iteration functionality built-in. The researchers examined 49 CMSs and 47 web application frameworks for these default settings (hash function, salt, iterations). Additionally, they examined other elements such as password length and complexity requirements. WordPress Leading the Bad Flock According to the researchers, WordPress is used for 31.3 percent of websites worldwide (59.8 CMS market share). WordPress (as of version 4.9.1) by default uses the least secure hashing function: MD5. Although the hash is applied with 8192 iterations and with a salt, there is no minimum password length being enforced, so WordPress passwords may be trivial to break. On the other hand, WordPress’s biggest competitors are safer (but only slightly). Drupal (as of version 8.4.4) uses the insecure SHA512 hash function but applied with 65,536 iterations and a salt. There is no minimum password length. Joomla (as of version 3.8.3) uses a secure BCRYPT hash function with default 1024 iterations, a salt, and a minimum password length of 4 (not long enough). Among less popular open-source systems there are some very good examples and some very bad ones. One of the top examples is the NodeBB forum system with BCRYPT, 4096 iterations, salt, and a minimum password length of 6. On the other hand, for example, Phorum 5.2.23 uses MD5, no iterations, no salt, and no minimum password length. The entire list of CMSs and frameworks is available in the research paper. The authors of the paper recommend the use of BCRYPT, SCRYPT, or Argon2 as the default hash functions. BCRYPT and Argon2 are implemented by default in PHP but Argon2 support was added in PHP v7.2 (very recent) and therefore very few solutions use it yet. SCRYPT is not yet implemented in PHP and most CMSs are written in PHP. The PBKDF2(SHA512) function is acceptable with at least 10,000 iterations (as recommended by NIST) and other functions (MD5, SHA1, SHA256, SHA512) are not acceptable as defaults. At the same time, the authors recommend the default use of a salt, an increased minimum number of iterations, and a minimum password length of 8. For example, PHP uses BCRYPT with 1024 iterations by default but the authors believe it can be increased to 16,384 iterations with no risk of regular login delays. Denial of Service Risks All hash functions except MD5 can introduce a Denial of Service (DoS) risk. Even 20 logins per second using BCRYPT with 1024 iterations can cause the server to reach 100% CPU utilization. To protect the CMS against such attacks, rate limiting must be introduced, for example, an hourly lock-out after 3 unsuccessful login attempts for the same account in 30 seconds. There are third-party plugins for many CMSs that offer such functionality, for example, WP Limit Login Attempts for WordPress. On the other hand, many CMSs introduce a maximum password length because older hash functions (MD5, SHA1, SHA256, SHA512, and PBKDF2) are susceptible to DoS attacks using very long passwords. BCRYPT and SCRYPT are not – the length of the password has next to no effect on hash function processing time. Therefore, CMSs do not need any length limits for passwords. Protect Your Passwords Unfortunately, many CMS users do not even realize that the hash function that they use is insecure. If your CMS uses a weak scheme by default, updating your installation will not help. Your best choice is to contact your CMS administrator or someone with programming skills and ask them to search how to change the default hashing scheme. In the case of WordPress it’s as easy as installing a plugin (for example, PHP Native password hash). When you change your default hash, current passwords are still stored using the old hash. However, when the user logs in, the CMS re-hashes the user password using the new scheme. Therefore, to secure all your user accounts, you must only ask all your users to log in. They do not need to change their passwords, just enter the current one. Get the latest content on web security in your inbox each week.
Automatic for the people Microsoft Azure Automation is designed to allow customers to schedule jobs, handle input and output, and more, with each customer’s automation code running inside a sandbox, isolated from other customers’ code executing on the same virtual machine. However, a vulnerability – discovered by Orca Security and dubbed 'AutoWarp' – shattered the sanctity of this virtualized environment. AutoWarp affected customers using the Azure Automation service providing the on-by-default Managed Identity feature in their automation account was enabled. Microsoft said it has contacted all the potentially affected customers. Researchers at Orca discovered a flaw that allowed an attacker to interact with an internal server that manages the sandboxes of other customers in order to obtain authentication tokens for other customer accounts. "Those tokens can be used against Azure to perform any action the customer would have given to the Azure Automation service," cloud security researchers Yanir Tsarimi and Yoav Alon of Orca Security told The Daily Swig. "Those permissions could allow the attacker to have full control over Azure resources, like virtual machines, and/or data belonging to the customer, depending on the permissions the customer assigned." These security issues were reported to Microsoft on December 6, which fixed it within four days. "The disclosure process was excellent. The people from the Microsoft Security Response Center are very friendly and responsive," according to Tsarimi and Alon. The vulnerability is the second cross-tenant issue to have been revealed by Orca in recent months. In January, the security consultancy discovered a vulnerability in Amazon Web Services (AWS) Glue data integration service. However, Tsarimi and Alon said that despite their research they don't believe that there are any fundamental security issues with cloud computing. "We believe that the cloud enables customers to build more secure services faster. Software vulnerabilities exist in all types of software, and the cloud shifts large parts of the responsibility for maintaining and patching security issues away from organizations to the cloud providers," they said. "Case in point, we found and reported a vulnerability to Azure – they quickly fixed the vulnerability [and] audited the platform to make it was not exploited by a malicious actor, without the need for the customer to take action."
Windows is a widely-used operating system that provides a stable and reliable platform for users to perform various tasks. However, like any other software, it is not immune to errors and malfunctions that can cause inconvenience and frustration to users. If you are experiencing issues with your Windows operating system, such as certain functions not working or Windows crashes, then you might want to consider using the System File Checker (SFC) to scan Windows and restore your files. The SFC is a built-in Windows utility that scans and repairs damaged or corrupted system files. It is a powerful tool that can help you fix a range of issues, including blue screen errors, system crashes, and other problems related to the operating system. By running an SFC scannow command, you can restore missing or corrupted files and ensure that your system is functioning properly. If you are unsure about how to use the SFC tool, don’t worry. In this guide, we will walk you through the process step-by-step. While the steps may seem complicated at first, just follow them in order, and we’ll try to get you back on track. Run SFC scannow command on Windows 10 Before we get started, it is important to note that the SFC tool requires administrative privileges to run. Therefore, you should ensure that you are logged in to your Windows account as an administrator. If you are not sure whether you have administrative privileges, follow these steps: - Click on the Start and type “cmd” in the search bar. - Right-click on the Command Prompt and select “Run as administrator“. - If prompted, enter your admin password and click “OK“. Once you have confirmed that you have administrative privileges, you can proceed with the SFC scan. Here’s how to do it: Step 1: Open Command Prompt Click on the Start menu and type “cmd” in the search bar. Right-click on the Command Prompt and select “Run as administrator“. If prompted, enter your admin password and click “OK“. Step 2: Run the SFC Scannow command on Windows 10 In the Command Prompt window, type “sfc /scannow” and press Enter. The scan may take some time to complete, so be patient and do not interrupt the process. Once the scan is complete, the SFC tool will display a message indicating whether any issues were found and whether they were fixed. Step 3: Restart Your Windows After the scan is complete, restart your computer to apply any changes that were made during the scan. Once your computer has restarted, check whether the issues you were experiencing have been resolved. In some cases, the SFC tool may not be able to fix all the issues it finds. If this happens, you can try running the scan again or use other troubleshooting methods to address the problem. You can also seek help from a professional if you are unsure about how to proceed. Run SFC scannow command on Windows 11 While the System File Checker (SFC) is still present in Windows 11, there are a few changes in how to access it compared to Windows 10. In Windows 10, you can access the SFC tool by typing “sfc /scannow” in the Command Prompt window, which can be opened by searching for “cmd” in the Start menu. In Windows 11, however, Microsoft has introduced a new feature called Windows Tools that combines several system tools, including the SFC, into a single menu. To access the SFC in Windows 11, follow these steps: Click on the Start button and select Windows Tools from the menu. Click on System File Checker to open the SFC tool. In the SFC window, click on Scan now to start the scan. The rest of the process is the same as in Windows 10. The SFC will scan your system files and attempt to repair any issues it finds. It’s worth noting that Windows 11 also includes a new feature called “Deployment Image Servicing and Management” (DISM), which can be used alongside SFC to repair Windows images. To use DISM, open the Command Prompt as an administrator and type “dism /online /cleanup-image /restorehealth”. This will scan your Windows image and attempt to repair any issues it finds. Overall, while the SFC tool works in a similar way in both Windows 10 and 11, the method for accessing it has changed slightly in the newer operating system. Use SFC on Windows 7 or 8 You can use the System File Checker (SFC) command on Windows 7 and Windows 8 just like you can on Windows 10. The steps to use the SFC command on Windows 7 or 8 are slightly different from those on Windows 10, but the basic process is the same. To use the SFC command on Windows 7 or 8, follow these steps: - Click on the Start menu and type “cmd” into the search bar. - Right-click on the Command Prompt application and select “Run as administrator“. - Type “sfc /scannow” into the Command Prompt window and press Enter. The SFC tool will begin scanning your system files and will replace any corrupted or missing files with a cached copy from your system. Note that on Windows 7 and 8, you may need to insert your Windows installation disc if the SFC command finds any corrupted system files that it cannot repair with cached copies. Here are the answers to the most searched questions about the System File Checker (SFC) command: What is the System File Checker command, and how does it work? The System File Checker is a command-line utility in Windows that scans and repairs corrupted or damaged system files. It compares the versions of system files on your computer against the versions stored in your Windows installation files and replaces them if necessary. How do I use the System File Checker command to scan and repair my Windows system files? To use the SFC command, you need to open the Command Prompt as an administrator and type “sfc /scannow” and then hit Enter. This will start the scan process, which may take several minutes to complete. Once the scan is finished, the SFC tool will either report that it found and repaired issues or that it found issues but could not repair them. What are some common problems that the System File Checker command can fix? The SFC command can fix various issues related to system files, such as missing or corrupted DLL files, system crashes, startup problems, and more. And in Windows 10, SFC scannow command is used the most. What should I do if the System File Checker command fails to repair my Windows system files? If the SFC command fails to repair your system files, you can try running the Deployment Image Servicing and Management (DISM) command to restore the health of your Windows image. Alternatively, you may need to perform a repair installation or a clean install of Windows. How long does it take for the System File Checker command to complete a scan and repair of my system files? The time it takes for the SFC command to complete a scan and repair depends on the size and complexity of your system files. It may take anywhere from a few minutes to an hour or more. Can I use the System File Checker command to repair corrupted or missing Windows system files on an external hard drive or USB drive? Yes, you can use the SFC command to repair corrupted or missing Windows system files on external hard drives or USB drives if they are connected to your computer. Can I run the System File Checker command in Safe Mode? Yes, you can run the SFC command in Safe Mode. To do so, press the F8 key during startup to enter the Advanced Boot Options menu, and then select Safe Mode with Command Prompt. How do I know if the System File Checker command has found and repaired any issues with my Windows system files? After the SFC command completes a scan and repair, it will display a message stating whether it found and repaired any issues. You can also check the SFC log file for more details on any repairs that were made. How do I use the Deployment Image Servicing and Management (DISM) command in conjunction with the System File Checker command to repair my Windows system files? To use DISM with the SFC command, open the Command Prompt as an administrator and type “dism /online /cleanup-image /restorehealth” and then hit Enter. This will scan and repair any issues with your Windows image, which may help the SFC command to complete any repairs. How often should I run the System File Checker command to maintain the health of my Windows system files? It’s generally a good idea to run the SFC command periodically to maintain the health of your Windows system files. You may want to run it after installing new software or making significant changes to your system. However, running it too frequently may not be necessary and could potentially cause issues.
Cloud Security Posture Management (CSPM) is an automated cloud security solution that identifies security risks in cloud infrastructure. It is like an automated auditor that reviews software deployed in the cloud and identifies security misconfigurations. CSPM is fully automated—instead of requiring security teams to manually check the cloud's security risks, it runs in the background and analyzes compliance risks and configuration vulnerabilities. Cloud infrastructure monitored by CSPM may include Software as a Service (SaaS), Platform as a Service (PaaS), Infrastructure as a Service (IaaS), containers, and serverless functions. Most CSPM tools can scan multi-cloud environments and provide a consolidated view of security posture across all cloud services. This feature is important because a majority of organizations leveraging the cloud use multiple cloud providers. Multi-cloud environments increase the risk of misconfiguration and are too complex to manage manually. In this article: Industry research shows that a vast majority of cloud security incidents are a result of failure by the cloud customer to properly secure their workloads, not failure by the cloud provider. Public cloud providers use the shared responsibility model, in which proper configuration of security for workloads and data is the responsibility of the cloud customer. Therefore, organizations cannot rely solely on cloud providers to manage cloud resources and enforce security policies. Security teams must take a proactive approach and have a comprehensive view of their cloud environment to maintain a healthy security posture. CSPM gives organizations the visibility they need to identify exposure to public networks, missing authentication, and many other data security risks. CSPM helps automate security workflows. Instead of manually assessing cloud configurations and then manually investigating and fixing each risk, the CSPM tool allows teams to automatically and continuously analyze all cloud configurations. Security issues can be discovered as soon as they occur, minimizing the time and effort by cloud operations and security teams. In some cases, the CSPM tool can also automatically remediate issues, for example by updating access control rules to increase security or disable outdated user accounts. CSPM tools can not only identify security risks, but can also classify them according to severity. Risk prioritization is critical to helping teams manage high volumes of security alerts while focusing on and fixing the most severe risks. Here is an example of how CSPM platforms might classify risks in a cloud environment: When using CSPM, make sure that the platform uses service discovery to identify new resources created in the cloud, and automatically audits them for security issues. This will ensure watertight discovery of security issues in any existing or new assets. Most cloud providers publish benchmarks to help you evaluate cloud configurations. These vendor-specific guidelines should be used in conjunction with third-party industry benchmarks such as those published by the Center for Internet Security (CIS) or regulatory bodies. CSPM should perform auditing of assets according to these recognized benchmarks. When dealing with security issues and vulnerabilities, you may want to address them as soon as you discover them. However, the order in which problems are found often does not match the level of risk presented by the problems. Avoid spending too much time on low-priority issues and focus on higher-priority ones that can have a major business impact. When reviewing alerts, investigating them, and managing vulnerabilities, focus on issues that could affect critical applications and workloads or potentially expose data or assets. Leverage the CSPM platform’s prioritization capabilities to help identify the most critical vulnerabilities. Once the higher-priority risks are managed, you can start working on the lower-risk ones. When developing software using a DevOps pipeline, you must incorporate security checks into the development lifecycle. New cloud environments and software deployments, due to their dynamic nature, can quickly become subject to vulnerabilities. Integrating CSPM policies and vulnerability checks throughout the DevOps pipeline helps prevent misconfiguration in development tools, which can lead to devastating supply chain attacks. In addition, it ensures that software has proper security configuration before it goes into production. CSPM can also help development teams identify required fixes and easily incorporate them into future releases. When choosing a CSPM vendor, consider the following: Cloud vendors provide compliance management and threat detection tools, although these tend to be vendor-specific. Managing the disparate tools of different vendors in a multi-cloud environment is challenging, so a CSPM must be able to integrate with these cloud native tools and display all the outputs via a centralized platform. Spot Security is a Cloud Security Posture Management (CSPM) tool providing threat protection to customers with their infrastructure and applications resources in the cloud against risk, threats and vulnerabilities in the cloud. Spot Security also enables customers to gain a 360° visibility into their cloud estates, with detailed and visual information about how their cloud assets are configured, connected, Shared and consumed and helps customers with defining the security scope to their teams to maximize their efficiency with visualization of threats and helps security teams understand the impact of each risk and take informed decisions on prioritization and mitigations of tasks. for up to 20 instances
Zero Trust has emerged for ten years. There are numerous posts and definitions if you google it. After digesting perspectives of Kindervag, CSA, Gartner, and NIST, Access Control 2.0 is the most effective terminology I can think of, to convey the idea of Zero Trust. Access Control 2.0 Zero Trust is a cybersecurity paradigm for access control featuring data-centric, fine-grained, dynamic, and with Visibility. - Software-defined perimeter over network perimeter. - Data-centric micro-segments over network-based segments. - Identity-based context and attribute-based access control for fine-grained control and policy dynamics. - Logging and observing for visibility. - Compliance with need-to-know, least privileges, and complete mediation.
And often enough, when we think we are protecting ourselves, we are struggling against our rescuer. - Marilynne Robinson, Gilead Like any other element connected to Internet, AWS instances are exposed to various attack vectors every day. The primary reason is that many AWS users allow the individual instances to be publicly addressable from anywhere on the Internet by trading off security to favor convenience. It enables, for instance, the Dev and Ops personnel easy access to every asset to load and test software. How would you shield the AWS assets from unauthorized access and other attacks? Security group is a great defense instrument. You take a stock of all the IP addresses from where your VPC will be accessed and build security groups that allow access from those locations (deny by default; accept only from known set). This works pretty well, but as your workforce expands and turns global, flexible, and mobile, security group administration becomes inconvenient. Adding to this, imagine the situation when you have AWS resources spread across multiple regions. Since each region operates independently, the security group upkeep nightmare multiplies. Bastion host is a commonly used method to protect individual instances from the attack vectors. You basically introduce one more hop (where you can insert custom authorization mechanisms) and keep the AWS instances in the internal network (VPC). Cons: the bastion host adds one more step for access and can be cumbersome operationally. Private connectivity to AWS The past sections concentrated on secure access to individual AWS instances. Integration of enterprise IT with AWS frequently calls for internal services (such as a corporate web site, wiki, source control) to be hosted securely on AWS. That requires privately (and securely) connecting the enterprise with AWS at the network level. A private network with AWS provides the best of the worlds: - It is secure, - Managing security groups is simpler, - You can seamlessly deploy enterprise applications on AWS. There are a few technologies available today to implement private connectivity to AWS: - Hardware virtual private gateway - Software appliance based VPN, such as OpenVPN - AWS direct connect - Provider cloud connect, such as AT&T Netbond and Verizon SCI You can find more information on this AWS guide. At Sproute, we believe that the extension of an enterprise private network to AWS should be a really simple operation and should just work. Not surprisingly, we think our approach for AWS connectivity is a great solution. We came up with a few metrics while evaluating the various approaches - here is a summary: We struggled through many of the same techniques while working with our AWS resources. Now, we are happily dogfooding SPAN.
The segmentation and detection of objects in a scene is one of the most frequent tasks in digital image processing, being also one of the most important. Normally it involves separating the object from a statistically distinct background. When the background and object in the scene have the same statistical properties, problems arise. The method presented uses temporal information about the scene to aid in the detection of moving objects. This work tries to bring an object with the exact same statistical characteristics of the background, from its camouflaged position, by the use of motion analysis instead of static picture analysis. Tipo (Avaliação Docente): Conference with international scientific committee and international participation Nº de páginas:
In this series I will cover some lesser-known features, built right into Windows, which can be used to secure your Windows infrastructure. I’m going to start the series by discussing a feature known as “Domain Isolation”. Domain Isolation (along with Server Isolation) is relatively easy to implement, transparent to users, and best of all, does not require any additional hardware, software or licenses. Domain isolation is provided by the Windows Firewall with Advanced Security and provides two services: authentication, and optionally, encryption. Using Group Policy Objects, computers and servers in an Active Directory forest can be required to authenticate before communicating, or, in more secure environments, encryption of network traffic can be required. Once implemented, the computers of visitors such as guests and consultants can share the same physical network segment, however all network traffic between these systems and domain-joined systems will be blocked by the Windows firewall. Before requiring authentication or encryption, all systems in the forest must first be configured to request authentication. Unless a system is able to request authentication, it will never be able to communicate with systems that require authentication or encryption. In other words, configuring a system to request authentication enables its ability to be part of an isolated domain. After that policy has been implemented and verified, the next step is to select systems that will require authentication, and a policy to enable this feature must be deployed. Domain Controllers and infrastructure servers such as DNS and DHCP servers generally should not be configured to require authentication, since computers that are not domain-joined may require their services. Publically accessible systems such as web and email servers must also be omitted from the policy. After authentication is required on a system, it will not even respond to pings from unauthenticated hosts, so it’s critical to have a good understanding of your environment and what the implications of this change will be. Lastly, encryption of all traffic to certain hosts can be required. Encryption uses IPSec transport mode, which encrypts just the contents of a packet, unlike a more common IPSec tunnel, in which the entire packet is encrypted. Servers holding the most sensitive information would be good choices for this policy, as well as Hyper-V host servers. One advantage of encrypting traffic between Hyper-V hosts is that it will protect replication traffic without requiring the configuration of certificates from within the Hyper-V settings. I hope this quick overview of Domain and Server Isolation helped you understand the capabilities and benefits of this powerful and easy to use security feature. If you’d like assistance implementing Domain and Server Isolation in your environment, or if you have questions or concerns about the security of your infrastructure in general, please feel free to contact us at any time.
An Efficient Multipath Erasure Coding based Secure Routing Protocol in Manet Mobile ad hoc network have been developed to afford various levels to provide secrecy protection. However existing anonymous routing protocol overcome the challenges such as high energy consumption due to acknowledgement free communication and data loss due to link breakage. By using Hierarchical zone partition it provides secure communication by hiding node identities and preventing traffic analysis attacks from outside observes. Information carriage is resolved by using multipath erasure coding i.e. split the data into two path and then GPSR algorithm, find the shortest path and then send the data to destination node.
Kubernetes is a container orchestrator. It provides some basic primitives to orchestrate application deployments on a low level —such as the pods, jobs, deployments, services, ingresses, persistent volumes and volume claims, secrets— and allows a Kubernetes cluster to be extended with the arbitrary custom resources and custom controllers. On the top level, it consists of the Kubernetes API, through which the users talk to Kubernetes, internal storage of the state of the objects (etcd), and a collection of controllers. The command-line tooling ( can also be considered as a part of the solution. The Kubernetes controller is the logic (i.e. the behaviour) behind most objects, both built-in and added as extensions of Kubernetes. Examples of objects are ReplicaSet and Pods, created when a Deployment object is created, with the rolling version upgrades, and so on. The main purpose of any controller is to bring the actual state of the cluster to the desired state, as expressed with the resources/object specifications. The Kubernetes operator is one kind of the controllers, which orchestrates objects of a specific kind, with some domain logic implemented inside. The essential difference between operators and the controllers is that operators are domain-specific controllers, but not all controllers are necessary operators: for example, the built-in controllers for pods, deployments, services, etc, so as the extensions of the object’s life-cycles based on the labels/annotations, are not operators, but just controllers. The essential similarity is that they both implement the same pattern: watching the objects and reacting to the objects’ events (usually the changes). Kopf is a framework to build Kubernetes operators in Python. Like any framework, Kopf provides both the “outer” toolkit to run the operator, to talk to the Kubernetes cluster, and to marshal the Kubernetes events into the pure-Python functions of the Kopf-based operator, and the “inner” libraries to assist with a limited set of common tasks of manipulating the Kubernetes objects (however, it is not yet another Kubernetes client library). See Architecture to understand how Kopf works in detail, and what it does exactly.
Posts Tagged ‘anticensorship’ Human rights activists and free speech advocates have every reason to worry about the future of an open and uncensored internet, but researchers from the University of Michigan and the University of Waterloo have come up with a new tool that may help put their fears to rest. Their system, called Telex, proposes to circumvent government censors by using some clever cryptographic techniques. Unlike similar schemes, which typically require users to deploy secret IP addresses and encryption keys, Telex would only ask that they download a piece of software. With the program onboard, users in firewalled countries would then be able to visit blacklisted sites by establishing a decoy connection to any unblocked address. The software would automatically recognize this connection as a Telex request and tag it with a secret code visible only to participating ISPs, which could then divert these requests to banned sites. By essentially creating a proxy server without an IP address, the concept could make verboten connections more difficult to trace, but it would still rely upon the cooperation of many ISPs stationed outside the country in question — which could pose a significant obstacle to its realization. At this point, Telex is still in a proof-of-concept phase, but you can find out more in the full press release, after the break.
As hacking techniques evolve more and more, hacks are being done without the malicious programs touching the hard drive. All of these processes reside inside the memory of the victim computer. When this happens memory forensics becomes necessary. In this post I’m going to show a few of the volatility modules that can be used to find running processes, unknown network connections, and the DLLs associated with each process that are found inside of computer memory. First I’m going to make sure I’m in the directory that has my memory images Once I know I have the right images to analyze I use the volatility framework to analyze the memory files. Volatility is a free open source suite of software that is used for advanced memory forensics. It is supported by the Volatility Foundation. The website for the volatility foundation can be found at: http://www.volatilityfoundation.org/ First I’m going to check for open network connections. This is odd because this computer should not have any active network connections at all. So this is the first indication that something is wrong. Next I dig a little deeper and I use volatility to display a list of all the running processes. The pslist module is used to do this. In windows each executable (.exe) has dynamic link libraries (DLLs) associated with it. These are located inside of the .exe file. Volatility can be used to see each DLL that is inside of an executable. The dlllist module is used for this task. I found an interest DLL in one of the executables. I decided to Google it to see if it was something odd. This is a small taste of what memory forensics is. It is a growing field and the more complex hacking attacks get the more rouge processes may be located in memory. Thanks for reading!
The lock-and-key icon was broken. The site-authentication image was not there. A security message popped up, warning that the site was not properly certified. And still, more than half of them entered a password and tried to log in. That's the bottom-line finding of a new study from researchers at Harvard University and MIT, who conducted a live test of banking users to measure the effectiveness of browser-based authentication and anti-phishing features earlier this year. The research is scheduled to be presented at the IEEE Symposium on Security and Privacy next month. In the study, 67 customers of a single bank were asked to perform common online banking tasks. As they logged in, they were presented with increasingly conspicuous visual clues that suggested they might be about to enter a phishing or other fraudulent site. In the first test, the researchers "broke" the HTTPS security key. The lock-and-key icon at the bottom of the screen clearly was not in one piece, and the URL showed "http" rather than "https." After seeing these cues, all (100%) of the participants proceeded to log in anyway. In the second test, the researchers removed the site authentication image from the users' browser screens. These images, typified by Bank of America's Sitekey, are supposed to authenticate the site for the user by presenting a pre-selected image that the user can recognize. The researchers did not reveal which site authentication image technology was involved in the test. When both the HTTPS security key and the site authentication image were displayed in an unsecured state, only 3 percent of the participants stopped the logon process before typing in their passwords. The rest of the users -- 97 percent -- went ahead and logged on. In the third test, the researchers presented the participants with a browser "warning page" stating that there was a problem with the target site's security certificate. Users were then given the option of closing the page or continuing to the Website. In the presence of the broken HTTP key, a non-secure URL, an absent site authentication image, and a strongly-worded pop-up warning, 53 percent of the participants chose to continue to the banking site. Only 47 percent chose to abandon the logon before they had typed their passwords. "We confirm prior findings that users ignore HTTPS indicators," the researchers say in the study. "No participants withheld their passwords when these indicators were removed. We also present the first empirical investigation of site authentication images, and we find them to be ineffective." The tests were done on Microsoft's IE6 browser and, therefore, did not evaluate the effectiveness of the new anti-phishing features in IE7, where color-coded URLs and pop-up warning screens are a new feature. "Very few of the participants had seen the warning pages before," the researchers conceded. "Now that IE7 is widely available, users may see warning pages often enough to become complacent about heeding them." But the study findings support some experts' skepticism that anti-phishing warnings, such as the new Extended Validation SSL, will have much impact on users' behavior. A study conducted by Microsoft and Stanford University in February has already suggested that EV SSL doesn't work. (See EV SSL: Dead on Arrival?) "Prior studies have reported that few users notice the presence of HTTPS indicators such as the browser lock icon," the study notes. "Our results corroborate these findings and extend them by showing that even participants whose passwords are at risk fail to react as recommended when HTTPS indicators are absent." Tim Wilson, Site Editor, Dark Reading
List of HTTP status codes Retrieved December 20, The server failed to fulfil a request. The client browser tries to use a client certificate that was revoked by the issuing certification authority. Home users This article is intended for use by support agents and IT professionals. Status codes are issued by a server in response to a client's request made to the server. The first digit of the status code specifies one of five standard classes of responses. The message phrases shown are typical, but any human-readable alternative may be provided. Microsoft Internet Information Services IIS sometimes uses additional decimal sub-codes for more specific information, however these sub-codes only appear in the response payload and in documentation, not in the place of an actual HTTP status code. All HTTP response status codes are separated into five classes or categories. The first digit of the status code defines the class of response. The last two digits do not have any class or categorization role. There are five values for the first digit:. An informational response indicates that the request was received and understood. It is issued on a provisional basis while request processing continues. It alerts the client to wait for a final response. The message consists only of the status line and optional header fields, and is terminated by an empty line. This class of status codes indicates the action requested by the client was received, understood and accepted. This class of status code indicates the client must take additional action to complete the request. Many of these status codes are used in URL redirection. A user agent may carry out the additional action with no user interaction only if the method used in the second request is GET or HEAD. A user agent may automatically redirect a request. A user agent should detect and intervene to prevent cyclical redirects. This class of status code is intended for situations in which the error seems to have been caused by the client. Except when responding to a HEAD request, the server should include an entity containing an explanation of the error situation, and whether it is a temporary or permanent condition. These status codes are applicable to any request method. User agents should display any included entity to the user. The server failed to fulfil a request. Response status codes beginning with the digit "5" indicate cases in which the server is aware that it has encountered an error or is otherwise incapable of performing the request. Except when responding to a HEAD request, the server should include an entity containing an explanation of the error situation, and indicate whether it is a temporary or permanent condition. Likewise, user agents should display any included entity to the user. These response codes are applicable to any request method. Microsoft's Internet Information Services web server expands the 4xx error space to signal errors with the client's request. The nginx web server software expands the 4xx error space to signal issues with the client's request. Cloudflare 's reverse proxy service expands the 5xx series of errors space to signal issues with the origin server. From Wikipedia, the free encyclopedia. Retrieved 16 December Retrieved January 8, Retrieved April 1, Retrieved 16 October Semantics and Content - 5. Retrieved 27 September Retrieved October 24, Retrieved December 20, Retrieved August 30, Retrieved 6 September Auto-suggest helps you quickly narrow down your search results by suggesting possible matches as you type. All posts Previous Topic Next Topic. Everything worked for 3 moths without any problem, but now and only at one user is problem with running flows, when user click on button which run flows he gets ""Service returned error.: User has same privilieges like other users in Dynamics and also in O Any ideas where can be a problem? Report Inappropriate Content Message 1 of 7. Connecting to Data Forum Help. Can the user create flows based on other connectors? Best regards, Mabel Mao. Report Inappropriate Content Message 2 of 7. I try verifiy connecting to other services by flows at this user. Report Inappropriate Content Message 3 of 7. Report Inappropriate Content Message 4 of 7. Report Inappropriate Content Message 5 of 7. User cant run these flows, but other users with same privileges can run these flows.
Frequency-based Deep-Fake Video Detection using Deep Learning Methods Keywords:Deep Fake, Deep Learning, CNN, LSTM, Fake Videos Deep Learning (DL) is an advanced and effective technology widely used in diverse industries, including medical imaging (MI). Data Mining (DM), Image Processing (IP), and Machine Vision (DM). Deep-fake uses DL technology to alter videos to render them indistinguishable from the original humans. The effectiveness of deep-fake has recently obtained significant attention from researchers, and numerous DL-based techniques have been developed to identify deep-fake videos. In this paper, a novel deep-fake video detection method is proposed. The Deep Fake Detection Challenge (DFDC) and Face Forensic datasets were used in the research. In addition, frequency-based frame extraction was conducted on each video during the preprocessing stage. Convolutional Neural Networks (CNN) Long Short-Term Memory (LSTM) - CNN techniques were used to identify fake videos. The LSTM-CNN approach achieved an accuracy of 82%. To identify fake videos using DL techniques, this work will be helpful to researchers. How to Cite This is an open Access Article published by Research Center of Computing & Biomedical Informatics (RCBI), Lahore, Pakistan under CCBY 4.0 International License
You sell a simpler box where security is the primary factor. A lot of grandmas and older people might go for something that only does AOL, mail, web browsing and maybe printing and digital photos. That might solve part of the problem (consumer side) but not the issue that the article was about. It does not solve the real issue. Making a grandma-friendly, secure, e-mail and download-only box would not do what the article suggests is happening. It might keep grandma from getting infected with the latest worm, but she will still get progressively less useful bandwidth from her modem. Grandma might have a 256Kbps DSL modem. She might even be fairly lucky and after dropping the malformed packets and garbage already out there, get a 200Kbps rate right now. But next year it might be 150Kbps, then 100Kbps as a few million script-kiddies are scanning for the next generation of BackOrafice trojans. Then she'll go buy a faster connection, because her Internet connection is slower than she wants. Her new connection will give her more visible speed, but would still be dropping a majority of the packets. I've seen the issue first hand. I'm with a small business, where we have a shared T1 line. Our upstream provider performs some packet filtering, but not much. After we pay for the data through our T1, we filter it. We drop malformed packets, packets from reserved and unassigned addresses, source-routed packets, and so on. We detect and block portscans and other obvious attacks at that point as well. We average a 7-10% packet loss through that filter daily. Next, we run SpamAssassin at a high filter level (15) along with attachment and virus blocking of emails, which collectively drop thousands of e-mail messages daily. Additionally our computers are running ad-filtering programs that save us a lot of bandwidth, but ads still slip through. If we were to assume that all the ads also got through, that is about 20-25% of our bandwidth wasted in complete junk, and that percentage has been increasing for the past two years that I have been watching it. Next we have a bunch of legitimate, but unwanted, traffic. That includes file sharing and trojan ports, incoming http, mail, telnet, DNS, ftp, rpc, and other assorted ports. We get a few hundred of these each day, and the number is always growing. Some might be people in the company trying to use NetMeeting or something, even though it is against policy. Some may be legitimate errors, while the remaining others are probably probing for systems to attack. The article says that the problem is this growing collection of junk -- currently about a quarter of our bandwidth -- which will quickly kill the Internet unless there is a change. Unfortunately, I agree with the author of the article; unless we see some fundamental changes, it will become unusable. There are a number of good ideas already out there as to what that may be. One idea that I like is to remove the anonymity of end-to-end, while preserving the end-to-end functionality. Every handler of every packet signs the packet, and drops packets from sources they do not trust or with invalid signatures. The sender cannot deny sending the message, each handler signs the packets and cannot deny that they handled it, each handler can state that they directly know who they received it from, and that all end-points can verify the sources. That allows any message not properly signed and not properly addressed to be dropped, and allow for law enforcement or system admins to find out who the attackers are, or exactly which machines have been compromised. The only significant drawbacks to that system are the resources involved in all the digital signatures and the loss of anonymity. I can only see a few reasons for anonymous speech (whistle-blowers, victims of crime, etc.) but there are other anonymous outlets for them. Online, I think non-repudiation should be built in, so long as you have encryption tools available. Your boss/government/police/mafia could know that you said something, but not know what it was. Until that level of fundamental infrastructure change spreads across the Internet, making a grandma-friendly Internet console isn't enough. The DDoS attacks on everything from spam blacklists, litigous companies like RIAA and SCO, honest mistakes like U. Wisconson's time servers, and script-kiddie behavior will continue to degrade the Internet. The spammers clogging up mailboxes and usenet will degrade the Internet. Tomorrows worms, along with todays worms on unpached systems, will continue to degrade the Internet. More people with cable-modems downloading movies will degrade Internet performance. In short, continuing our course will be just a little worse until we hit a very-near critical threshold. Then our performance will be like a figher jet slamming into a wall of jello. We need to change course, or face some serious performance losses.
Introduction to FirewallD on CentOS Better known as the Dynamic Firewall Manager, the FirewallD is a complete firewall solution that is by default, already installed and enabled on CentOS 7 servers. As a firewall solution, FirewallD acts as a frontend controller while at the same time, it controls the network traffic rules through the IP (Internet Protocol) tables. When compared to earlier firewall versions, FirewallD has unique features in the sense that, it makes use of zones and services, other than the chain and rules which characterized the previous versions (Pelz, 2016). Additionally, unlike the previous versions, FirewallD is uniquely featured to manage rulesets dramatically, which allows updates, without having to break existing sessions and connections. Although CentOS 7 servers support both FirewallD and IP tables, experts suggest starting using the FirewallD instead of the iptables since the iptables may be disconnected in the near future. How to Configure FirewallD in CentOS Usually, FirewallD is configured using XML files, with the exception of very specific configurations. During configuration, the FirewallD configuration files are located in two unique directories; which include This directory holds all the default configurations, such as the default zones and common services. Experts advise that, you should avoid updating these directories since the configuration files are usually overwritten, every time each FirewallD package is updated. /etc/firewalldThis is the directory that holds the system configuration files. When configured, these files usually overwrite the default configurations. Below is the process of installing and managing the FirewallD on CentOS Although FirewallD is by default installed in the CentOS 7, it usually is inactive, and needs to be controlled. The process of controlling it is, however, the same as that of other systemD units. ----# yum install firewalld -y---- After the installation of the FirewallD, check whether the iptables service is running or not. If it is running, you need to stop and mask it. Using the following command ----# systemctl status iptables# systemctl stop iptables# systemctl mask iptables---- Next, start and enable the FirewallD services: ----# systemctl start firewalld# systemctl enable firewalld---- Checking all the zones of FirewallD ----# firewall-cmd --get-zones---- Stop and disable al FirewallD services ----# systemctl stop firewalld# systemctl disable firewalld---- Check FirewallD service status ----# systemctl status firewalld---- Finally, reload FirewallD configuration ----# firewall-cmd --reload---- (Rackspace, 2016). FirewallD vs. Iptables With the support of network or firewall zones, which define the trust levels of network interfaces or connections, FirewallD provides a dynamically managed firewall on the CentOS. Iptables, on the other hand, are programs which allow a user to configure the firewall security tables which are provided by the Linux kernel firewall and the chains. This is provided, so as to enable a user to effectively add or remove firewall rules so as to meet their required security requirements. For the execution of the iptables rules, one has to have the root privileges since they are only configured by system analysts, system administrators or the IT manager (Petersen, 2016). In the Linux Kernel, the Netfilter framework is utilized, so as to provide various networking related operations which are performed using iptables. In CentOS, both FirewallD and the Iptables serve similar purposes, which is packet filtering. However, the two cannot be used simultaneously on the CentOS. Therefore, it is important that one of them is turned off, while the other is running. Similar to a majority of Linux distributions, the CentOS7 makes use of the netfilter framework while inside the Linux kernel, so as to have access of the packets which flow through the network stack. By so doing, this process provides the necessary interface, which manipulates and inspects the packets so as to implement a firewall system. Comparing FirewallD and Iptables One observable difference between FirewallD and Iptables is that the iptables command is usually used by FirewallD itself, however, the iptables service is not, by default, installed in CentOS 7. While it is possible to choose between working with FirewallD or the iptables, choosing to work with FirewallD over iptables has two main differences. Firstly, unlike the iptables which makes use of chains and rules, FirewallD uses zones and services. And secondly, FirewallD has the capability of managing rulesets dynamically which allows for updates without having to break the existing sections and connections. Additionally, FirewallD is based on XML configuration. While some people may think that it is easier to configure the firewall in a programmatic manner, the iptables can achieve this configuration as well, using a different way, other than XML (Ellingwood, 2015). Advantages of FirewallD over Iptables Basically, FirewallD is the new concept as well as the default tool that manages the host based firewall in CentOS 7. In earlier versions of CentOS, the iptables were primarily used to manage the firewall. Although the iptables services still exist, it is not advisable to use them in the management of the firewall. In this regard, firewallD has various advantages over the iptables. For instance, iptables uses three different services for the IPv4 (iptables), IPv6 (ip6tables), and software bridging (ebtables). FirewallD, on the other hand, makes use of a single service for all the three settings. Another key advantage of FirewallD over the iptables is the fact that FirewallD makes use of the DBus messing system which enables the user to add or to remove either the FirewallD rules or ports, from running firewall. With this feature, it is easy to run the FirewallD without having to restart it every other time when changes are introduced. This feature is however, not available in iptables and therefore, we can conclude that, FirewallD is the most efficient and convenient tool when it comes to firewall management. The Rules of FirewallD The rules involved in FirewallD can be designated as either immediate rules or permanent rules. In cases where a rule is added or modified by default, this modifies the behavior of the firewall that is currently running. The following are the various rules that are involved with FirewallD Exploring the Defaults Exploring the Alternative zones Adjusting the default zones The Commands Involved in FirewallD In CentOS, FirewallD has various commands that are used to perform different functions. The following are the different FirewallD commands that are used in the execution of various functions. Thus, when the user executes another boot, the old FirewallD rules are reverted. Commands used for starting the firewall and enabling a boot $ sudo systemctl enable firewalld$ sudo systemctl start firewalldThis command is used only if the firewall is already running and enabled. However, one can easily check whether the firewall is already running through the use of a command that employs the state argument. $ sudo firewall-cmd state Commands used for finding out about Zones $ sudo firewall-cmd --get-default-zone This command is used for finding out which zone is selected as the default $ sudo firewall-cmd --get-active-zones The command that is used for finding out the specific rules that are associated with the public zone $ sudo firewall-cmd --list-all --zone=public public (default, active)interfaces: eth0 eth1sources:services: dhcpv6-client http https sshports: 1025/tcpmasquerade: noforward-ports:icmp-blocks:rich rules: Commands used for Setting up Zones In cases where the firewall is completely restarted, the following command is used to revert the interface to the default zone; $ sudo firewall-cmd --zone=internal --change-interface=eth1 Commands Used for Defining a Service When creating different FirewallD rules, one can create their service by placing a file in '/usr/lib/firewalld/services/' by using the command line below $ sudo cp /usr/lib/firewalld/services/http.xml /usr/lib/firewalld/services/myservice.xml $ sudo vim /usr/lib/firewalld/services/myserver.xml (Rackspace, 2016) The Security Concepts for Firewall D Similar to other firewalls used on CentOS, FirewallD ha three basic security concepts. These concepts include; Zones, services, and ports. Also known as a network, a FirewallD zone is the security concept that defines the trust levels of the interface used to make a connection. FirewallD provides several predefines zones. For the easier firewall management, FirewallD categorizes every incoming traffic in Zones, based on the interface and the source address. In a real scenario, upon the arrival of a packet in a system, FirewallD first initiates the process by checking the source address of the packet, so as to find out whether the packets address belongs to any specific zone. If the packet that has arrived belongs to a particular zone, it is filtered by that specific zone and hence allowing the user to define and activate multiple zones even in cases where there is only one Network Interface (NIC) available on that system. FirewallD sets the default zone to public zone, although any other zone can be set as default. Like Zones, services are basic concepts found on FirewallD. Usually, services make up the secondary key elements in FirewallD concepts. The most appropriate way to manage firewall rules is through the use of services in zone files. In this case, the services are used in creating various pre-defined rules for the related network services in the zone files. Different common services are used in default zone files, and they include; SSH, DHCPv6, IPP-client, Samba-client, Multicast DNS (MDNS). Similar to the zones, services also have their specific configuration files which are essentially used for defining the specific ports, either TCP or UDP port that is filtered. Moreover, if it is a requirement, the services explain the particular kernel module that must be loaded. Ports are the FirewallD concepts that are either open or closed. FirewallD, therefore allows the users to manage network ports directly. For instance, even if a particular service is not installed in a system, it is possible to open or even close its associated port in the firewall. For example, port 22, which is associated with the SSH service can be opened or closed even the SSH service is not installed in the system. Ellingwood, J. (2015, June 18). How To Set Up a Firewall Using FirewallD on CentOS 7 \| DigitalOcean. Retrieved from https://www.digitalocean.com/community/tutorials/how-to-set-up-a-firewall-using-firewalld-on-centos-7 Pelz, O., & Hobson, J. (2016). CentOS 7 Linux server cookbook: Over 80 recipes to get up and running with CentOS 7 Linux server. Birmingham, UK: Packt Publishing. Petersen, R. (2016). Firewalls. In Fedora Linux Servers with Systemd: Second Edition (2nd ed.). Surfing Turtle Press. Rackspace. (2016, October 1). Using Firewalld on CentOS 7 (and Fedora) - Public Cloud Forum - Solutions & Questions - The Rackspace Community. 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Golang (Go) is a relatively new programming language, and it is not common to find malware written in it. However, new variants written in Go are slowly emerging, presenting a challenge to malware analysts. Applications written in this language are bulky and look much different under a debugger from those that are compiled in other languages, such as C/C++. Recently, a new variant of Zebocry malware was observed that was written in Go (detailed analysis available here). We captured another type of malware written in Go in our lab. This time, it was a pretty simple stealer detected by Malwarebytes as Trojan.CryptoStealer.Go. This post will provide detail on its functionality, but also show methods and tools that can be applied to analyze other malware written in Go.
In a smart home system, multiple users have access to multiple devices, typically through a dedicated app installed on a mobile device. Traditional access control mechanisms consider one unique trusted user that controls the access to the devices. However, multi-user multi-device smart home settings pose fundamentally different challenges to traditional single-user systems. For instance, in a multi-user environment, users have conflicting, complex, and dynamically changing demands on multiple devices, which cannot be handled by traditional access control techniques. To address these challenges, in this paper, we introduce Kratos, a novel multi-user and multi-device-aware access control mechanism that allows smart home users to flexibly specify their access control demands. Kratos has three main components: user interaction module, back-end server, and policy manager. Users can specify their desired access control settings using the interaction module which are translated into access control policies in the backend server. The policy manager analyzes these policies and initiates negotiation between users to resolve conflicting demands and generates final policies. We implemented Kratos and evaluated its performance on real smart home deployments featuring multi-user scenarios with a rich set of configurations (309 different policies including 213 demand conflicts and 24 restriction policies). These configurations included five different threats associated with access control mechanisms. Our extensive evaluations show that Kratos is very effective in resolving conflicting access control demands with minimal overhead, and robust against different attacks.
Written by Eric Wyatt (last updated March 16, 2020) My computer is connected to my network and internet using a Wi-Fi connection. Normally this connection works perfectly fine. I can access the files on my network drive, surf the web, and retrieve email—all the things I need to do on a daily basis. Other times my network has issues. When it comes to Wi-Fi networks this is not uncommon. What would be helpful is some type of report that tells me what is going on with my Wi-Fi network. Fortunately, Windows 10 includes a Wireless Network Report which can be used to help understand and diagnose connection issues. To access the Wireless Network Report, you will need to run a command in Command Prompt. Start by pressing the Windows key and typing (without quotes) "CMD." Do not press Enter yet; Windows should show you a few options on the screen. You need to run Command Prompt as an Administrator. Either right-click on the Command Prompt search result and choose "Run As Administrator" or press Ctrl+Shift+Enter. Regardless of the approach, Command Prompt launches in Admin mode. You will be able to tell it is in Admin mode if the resulting Command prompt window shows "\Windows\system32>" as the prompt. (See Figure 1.) Figure 1. Command Prompt showing that it is being run in Admin mode. To run the report, enter the following command: netsh wlan show wlanreport Once you press Enter the Wireless Network Report is generated. The report is provided in an HTML file that you can then open and review in a web browser of your choice. Command Prompt displays the location where the report can be found. Typically, the report should be located in this location: Note that the drive letter could be different depending on your computer. Refer to the location provided by your computer on where to find the report. (See Figure 2.) Figure 2. Command Prompt showing the location where the Wireless Network Report is saved. The report provides data relating to the previous 48 hours. The data is grouped based on Wi-Fi sessions. (See Figure 3.) Figure 3. Wireless Network Report. The information provided will be able to help aid you in discovering issues that may help you diagnose or identify connection issues that might arise from your Wi-Fi network. This tip (13748) applies to Windows 10. Using Command Prompt to generate file listing the contents of a directory is quick and easy. Here's how to do it.Discover More You may have the need to perform repetitive operations or group several commands together to run as a batch. In such ...Discover More Displaying all the files a folder contains is an easy task in Windows. One way you can display the files is using command ...Discover More
Ransomware has become a menace for both consumers and enterprises, and malware authors appear determined to take the threat to the next level by adding new capabilities, such as distributed denial of service (DDoS) functionality. Such is the case with FireCrypt, a recently spotted ransomware family capable not only of encrypting victims’ files, but also of launching a DDoS attack against a URL hardcoded in the source code. The malicious app continuously connects to said URL, but also downloads content from it and saves it to the local machine’s %Temp% folder, ultimately filling it up with junk files. Discovered by the MalwareHunterTeam, the FireCrypt ransomware is built using a command-line application that also allows the author to create, modify basic settings and save samples in the form of executables. Called BleedGreen, the tool is said to be low end, as it doesn’t enable the modification of settings such as the Bitcoin address for payments, ransom value, contact email address, and more. However, the builder can disguise the executable under a PDF or DOC icon, and can slightly alter the ransomware’s binary so that the new file would feature a different hash. This technique is usually used to create polymorphic malware that is more difficult to detect by standard anti-virus programs. The ransomware’s author attempts to trick the potential victim into launching the .exe file, which triggers the infection process. When that happens, FireCrypt immediately kills the Task Manager (taskmgr.exe) process and starts encrypting user’s files using the AES-256 encryption algorithm. The ransomware targets 20 file extensions. FireCrypt keeps the original file names and extensions, but appends .firecrypt to all encrypted files’ names. As soon as the encryption process has been completed, the malware drops a ransom note on the desktop. The ransom note appears identical to that used by the Deadly for a Good Purpose Ransomware, which was discovered in October 2016, when it was still under development. According to security researchers, the two ransomware families are closely related, with only a few changes seen in their source code. The Deadly for a Good Purpose Ransomware, for example, wouldn’t encrypt files if the infected computer’s date wasn’t 2017. Both families use the same Bitcoin address, and FireCrypt is believed to be a rebranded version of the original malware. After dropping the ransom note, FireCrypt proceeds to the DDoS activities, which are currently targeting the official portal of Pakistan’s Telecommunication Authority. The malware connects to http://www.pta.gov(.)pk/index.php and downloads the content to a file in the %Temp% folder. It does that repeatedly, which results in the %Temp% folder filling up fast. The researchers analyzing the ransomware say that the targeted URL cannot be modified using the ransomware’s builder, and that the so called DDoS attack against the website isn’t efficient. For it to cause real damage, the malware would have to infect thousands of computers at the same time, and would also need for all infected machines to be connected to the Internet simultaneously.
This can be used to defeat Content Security Policy, if you have that enabled. If there were an actual XSS vulnerability in your web application, an attacker might add something like <script>window.location = 'https://some-phishing-site.example.com';</script>. Without Content Security Policy blocking unsafe inline scripts this would work, but with a proper Content Security Policy this would be blocked by browsers. <script src="/.well-known/acme-challenge/window.location%20%3D%20%27https%3A%2F%2Fsome-phishing-site.example.com%2F%27%3B%2F%2Fx"></script> and defeat that security measure. text/plain due to historical reasons.) Now, you have to use Content Security Policy for this to even be an issue, and even if you do it’s minor in the grand scheme of things, but comprehensive security scanners are right to point out reflection of user input like this even if it is sanitized.
Teams can mitigate or completely remove threats and security vulnerabilities with the following core concepts. Docker’s networking is a complex part of the Docker infrastructure, and it is essential to understand how it works. It’s important to know what Docker Network Drivers are, for example: By default, one container network stack does not have access to another container. However, if you configure a bridge or host to accept traffic from any other containers or external networks, you can create a potential security backdoor for an attack. You can also disable inter-container communication using a set flag — icc=false within Docker daemon. Set Up Resource Limits It’s important to set up memory and CPU limits for your Docker container because Docker has a container that does not provide this option by default. This principle is an effective way to prevent DoS attacks. For example, you can set up a memory limit to prevent your container from consuming all memory. The same applies to CPU limits. Additionally, there is an option to set up resource limits on a Kubernetes level — this will be covered in greater detail in the Kubernetes Hardening Guidelines section below. Avoid Sensitive Data in Container Images This principle is quite important to move all sensitive data out of the container. You can use different options to manage your secrets and other sensitive data: - Docker secrets allows you to store your secrets outside of the image. - If you run Docker containers in Kubernetes, use Secrets to store your passwords, certificates, or any other sensitive data. - Use cloud-specific storage for sensitive data — for example, Azure Key Vault or AWS Secrets Manager. Vulnerability and Threat Detection Tools Vulnerability scanning tools are an essential part of detecting images that may contain security pitfalls. Moreover, you can also integrate properly selected tools into the CI/CD process. Third-party vendors and some common open-source tools offer this sort of functionality. Some examples of these open-source tools can be found in the About Container Security and Threat Detection section. To protect your images, create an additional security layer and use images from protected registries. Here are a few examples of open-source registry platforms: - Harbor – An open-source registry with integrated vulnerability scanning. It is based on security policies that apply to Docker artifacts. - Quay – An open-source image registry that scans images for vulnerabilities. Powered by RedHat, Quay also offers a standalone image repository that allows you to install and use it internally in your organization. Below, we will dive into how it scans for vulnerabilities within containers. Principle of Least Privilege This principle means that you should not execute containers using admin users. Instead, you should create users that have admin access and can only operate with this particular container. Groups can also add users there. Read more about it in the Docker Engine Security documentation. Below is an example of how to create the user and group: RUN groupadd -r postgres && useradd --no-log-init -r -g postgres postgres Also, alongside creating users and groups, please be sure to use the official verified and signed images. To find and check images, use docker trust inspect. Find more options and tools in the section below: Threat Detection Tool Selection Criteria for Containers. Linux Security Module To enforce security, implement the default Linux security profile and do not disable the default one. For Docker, you can use AppArmor or Seccomp. Security context rules in Kubernetes can also be set up with allowPrivilegeEscalation. This option controls the privileges that the container possesses. Also, the readOnlyRootFilesystem flag sets the container root filesystem to read-only mode. Static Image Vulnerability Scanning Now that we know how threat detection tools can work together and the strategies that we can use, let’s define what it means to adopt static image vulnerability scanning, secret scanning, and configuration validation. Static security vulnerability scanning is based on the Open Container Initiative (OCI) format. It validates and indexes the images against well-known threats and vulnerability information sources, like CVE Tracker, Red Hat security data, and Debian Security Bug Tracker. Static security vulnerability scanning mechanisms can be used for scanning several sources, like: - Container image - Filesystem and storage - Kubernetes cluster Static image vulnerability scanning can also scan misconfigurations, secrets, software dependencies, and generate the Software Bill of Materials (SBOM). An SBOM is a combination of open-source, third-party tools and components within your application that contains license information of all components. This information is important for quick identification of security risks. Below, we’ve included a list of open-source tools that cover the logic explained above. This is a representation of only a few of the many tools that can be used: - Clair – A security vulnerability scanning tool with an API for development integration purposes. It also creates your own divers to extend and customize Clair functionality. Clair has several Indexer, matcher, notifier, or combo models. - Trivy – A security container scanner based on the CVE threat database. Trivy can be installed on your PC or in the Kubernetes nodes, using brew, and other package managers, like: apt-get install trivy yum install trivy brew install aquasecurity/trivy/trivy To execute image scanning, run the following command: $ trivy image app-backend:1.9-test Another key to static image vulnerability scanning is the Security Content Automation Protocol (SCAP). SCAP defines security compliance checks for your infrastructure based on Linux. OpenSCAP is a tool that includes complex security auditing options. It allows you to scan, edit, and export SCAP documents, consisting of the following components and tools: - OpenSCAP Base – For vulnerability and configuration scans oscap-docker – For compliance scans - SCAP Workbench – A graphical utility to facilitate the execution of typical OpenSCAP tasks Below, you can see an example on how to run the validation process of the SCAP content: oscap ds sds-validate scap-ds.xml Static image validation is an important part of the threat detection process. However, static image scanning cannot detect the misconfiguration in the YAML and JSON configuration, and it may cause outages in complex YAML configs. Therefore, having an easy and automated method involves configuration validation and scanning tools like Kubeval. We can introduce configuration validation that can solve issues with static configuration and simplify the automation process. As an example, we will incorporate Kubeval, an open-source tool used to validate one or more Kubernetes configuration files, often used locally as part of a development workflow and/or within CI/CD pipelines. To run the validation, use the following example: $ kubeval my-invalid-rc.yaml WARN - fixtures/my-invalid-rc.yaml contains an invalid ReplicationController - spec.replicas: Invalid type. Expected: [integer,null], given: string $ echo $? The main goal of secrets scanning is looking into the container images, infrastructure-as-code files, JSON log files, etc. for hardcoded and default secrets, passwords, AWS access IDs, AWS secret access keys, Google OAuth Key, SSH keys, tokens, and more. Management Console and Sensor Agents A management console is a UI tool that builds a security infrastructure overview and provides vulnerability and threats reports. On the other hand, sensor agents are a tool that scans cluster nodes and gathers security telemetry. Thus, sensor agents report telemetry to the management console. For example, to install sensor agents within the AKS cluster, adhere to the following: helm repo add deepfence https://deepfence-helm-charts.s3.amazonaws.com/threatmapper helm show readme deepfence/deepfence-agent helm show values deepfence/deepfence-agent # helm v2 helm install deepfence/deepfence-agent \ --set managementConsoleUrl=x.x.x.x \ To install the management console within your AKS cluster, use the following command: helm repo add deepfence https://deepfence-helm-charts.s3.amazonaws.com/threatmapper helm install deepfence-console deepfence/deepfence-console The installation completes two operations: Both commands are quite simple and can be easily integrated into an IaC process.
A recently discovered critical vulnerability presents yet another case study for the shortcomings of the isolation/virtual machine model for cybersecurity. The vulnerability, CVE-2019-14378, has a severity of 8.8, and was first published in the National Vulnerability Database on July 29th, 2019. The vulnerability affects QEMU, the popular open source machine emulator and virtualizer. Short for “Quick Emulator”, QEMU is an embedded C/C++ code software that acts as an interface between a guest system and the actual hardware it uses. Known as “hypervisors,” this method allows machines to stay separate from other machines using the same host, to protect themselves in the event another machine is infected. Using a “virtual machine” also allows you to test out different software and apps not used by your host system – including suspected malware - without worrying that it’ll affect your physical system. But what happens when a vulnerability allows a hacker to break out from one hypervisor and execute code on the host computer itself? This is the case with CVE-2019-14378, which can allow a malicious actor to run malware on the host computer from a virtual machine. The flaw could allow hackers to carry out “virtual machine escape,” letting the guest operating system attack the host operating system that runs QEMU, execute code at the QEMU level, or crash QEMU process altogether. In other words, an embedded vulnerability in one stack can lead to compromised components elsewhere in the system. The vulnerability also reveals how even if the coding languages you use are safe from arbitrary code execution – as is the case with Java – once an attacker manages to penetrate the app that uses C/C++, they can exploit this vulnerability to break out of the hypervisor and send malware to a completely separate virtual machine. In sum, C/C++ code is everywhere, and security architectures can still be vulnerable to hacks that target C/C++ hypervisors like QEMU, even if they don’t use C/C++ code. The QEMU vulnerability is by no means the first example of how virtual machines can be hacked. There are many examples related to open source components (ex. Linux KVM) and proprietary ones. For instance, at the Pwn2Own security competition in 2017, a group of white hat hackers from the Chinese internet security firm Quihoo 360 needed less than 90 seconds to demonstrate a successful escape from a VMWare workstation. They carried out the escape by first exploiting a heap overflow bug in Microsoft Edge web browser, and then they “exploited a bug within the VMware hypervisor to escape from the guest operating system to the host one. All started from, and only by, controlling a website," Qihoo 360 Executive Director Zhen Zheng told reporters following the successful hack. Mitigation: Using Runtime Integrity While hypervisors and virtual machines can be an effective line of defense, they are useless if their proper functionality and integrity is not guarded during runtime. For that reason, standards such as NIST 800-53 and ANSI/ISA‑62443 specify integrity requirements. One key method to achieve that is by adding Embedded Runtime Integrity controls, which in this case will do exactly that – ensure the isolation and separation work as intended.
Threat defense tools [that] use a mix of vulnerability management, anomaly detection, behavioral profiling, code emulation, intrusion prevention, host firewalling and transport security technologies to defend mobile devices and applications from advanced threats. Mobile devices are more than just small computers in continuous use with perpetual connections to the Internet. The operating paradigm of these devices calls for new approaches to ensure the data processed by them remains secure while maintaining productivity. Skycure’ risk-based mobile security approach is designed from the ground up to defend against all threats that put business data at risk of exposure, theft and manipulation, while respecting users’ need for privacy, productivity and a great mobile experience. Defense against all attack vectors Apps are the lifeblood of every mobile device, and a key area of vulnerability. Malware can be delivered through unapproved, third-party app stores (sometimes via first-party app stores as well), personal computers or wirelessly via cellular, Wi-Fi or Bluetooth. Malware can look exactly like legitimate apps with no obvious indication of bad behavior. Examples of Malware Risks: Multi-layered detection and analysis based on a broad set of parameters, including signatures, user behavioral, static/dynamic analysis, source origin, structure, permissions, and 3rd party blacklists. Crowd-sourced intelligence helps to identify legitimate and malicious apps On-device detection and initial incremental app analysis, coordinating with the cloud-server as necessary for secondary analysis Use Mobile App Reputation Service (MARS) strategies to determine app risk Block installation of apps identified as suspicious or malicious Mobile devices, unlike PCs, connect to tens or hundreds of different networks in the course of a week or a day, dramatically increasing the risk of exposure to malicious Man-in-the-Middle network-based attacks, or even just misconfigured routers that innocently expose sensitive business data to anyone who may come across it. Examples of Network Risks: Patented Active Honeypot technology instantly determines if any new network connection is properly configured and trustworthy. Crowd-sourced intelligence helps to identify legitimate and malicious networks. Under attack, automatically stop communicating with sensitive corporate resources using Selective Resource Protection (SRP). Non-sensitive communications remain active for personal productivity. Secure Connection Protection (SCP) automatically activates Skycure or 3rd party VPN to encrypt all communications only for the duration of the attack. No software is perfect. Hackers work diligently to identify the weak points that may be exploited before the developers discover them and patch them in updates. Vulnerabilities may be exploited through multiple entry points, including messaging, web links, malware, networks and others. Skycure continuously monitors platform integrity through a broad array of checks and inspections Machine learning assists in anomaly detection and behavioral profiling to determine malicious behavior and unauthorized activities within the device. Skycure’s unique OS Upgradability feature informs IT teams of the available security updates event before Apple and Google Mobile devices are much more likely to be lost or stolen than traditional computers, providing hackers with physical access to the device. EMM partners typically provide some of the basic physical security measures, such as lock and wipe, or Skycure offers lightweight MDM functionality if the customer does not have an EMM. Examples of Physical Risks: Stolen device - unauthorized access Tight integration with all of the leading EMM vendors Bi-directional communications about device compliance for policy enforcement Skycure provides limited MDM functionality when no EMM is in place. Learn about all of the mobile threat vectors in the SANS Institute white paper.
Last week, Roshen wrote how we do code reviews. I want to go a step forward and discuss the role of automated code scanning in these code reviews. When we encounter an application with over 200,000 lines of code, we know that we will not have time to read every line of code. Nor is it necessary to read every line of code. As our code review process showed, we start with the Threat Profile and then figure out which sections of code to review. That helps us focus our efforts on the areas of code that an attacker would exercise. That smaller area is still fairly large, so every bit of automation helps. Before we dive into the role of automated code scanning, let’s look at how most modern code review scanners work. [Brian Chess’ and Jacob West’s "Secure Programming with Static Analysis" is a great book on the subject.] There’re two basic strategies code scanners take: In one very powerful approach, code scanners trace the path of an input from the source to its destination through all the transformations it takes. For example, the input could be the amount of funds to be transferred in a transaction. The input starts off from the user’s browser, is validated by pieces of code and then is used to construct a SQL statement which is executed against the database. The code scanner analyzes the path taken from source to destination (often called the sink) and then predicts if a malicious input would get through. For example, could the user send a malicious SQL snippet and execute that on the server for SQL Injection? This approach of tracing the input from source to the sink is useful to find code that is vulnerable to SQL Injection and Cross Site Scripting attacks. A second approach is to look for patterns of insecurity in the code - calls to insecure functions, error conditions not handled, null pointers, etc. This approach is simpler, but it generates more false alarms than the first approach, and requires further manual analysis to confirm the finding. Notice that in all these approaches, the code review scanner is unaware of the context of the application. It does not know, nor care, whether the application is an online banking site or an e-Commerce site, or an online game. The scanner applies its algorithms independently of the context of the applications. The blissful ignorance of context is both a strength and a weakness. The scanners are able to apply certain general principles that apply to a vulnerability - an input from the user being reflected back to the browser without escaping the < and > symbols, for instance - without trying to understand the context. That’s a good thing. The disadvantage is that entire classes of vulnerabilities that require understanding the context are outside the purview of the scanner - for instance, siphoning off funds in a banking application, or flouting the rules of chess in an online gaming site. We thus use the scanner for finding some standard vulnerabilities - dynamic SQL queries, reflected inputs, unhandled exceptions etc. These are the basis for common attacks like SQL Injection, Cross Site Scripting, and others. Once the scanner identifies code snippets as candidates for these vulnerabilities, we analyze them manually to confirm the flaw. For attacks that exercise the business logic - usually different variable manipulation attacks - we analyze the code manually. What about finding backdoors with code scanners? Since scanners are unaware of context, they usually don’t recognize backdoors that have been either purposely or inadvertently inserted in the code by the developers. Looking for backdoors manually is an interesting challenge. We will cover that in a different post.
Uncovering Criminal Bulk Registration Activities with Bulk Domain Name Checkers To propagate cyberattacks, threat actors use domain generating algorithm (DGA) as an evasion tactic. This algorithm, executed through various subroutines, involves switching or dropping thousands of domains in seconds. The relative ease with which cybercriminals can purchase domains in bulk makes it possible for them to accomplish DGA-enabled attacks. Dirt-cheap prices and lack of identity verification enable hackers to own domains while also staying anonymous. In fact, registrars typically offer privacy protection services at a small cost or for free, which nefarious actors may take advantage of to conceal their location and details. Additionally, the introduction of the Temporary Specification for Generic Top-Level Domain (gTLD) data has led to masking or redacting WHOIS data, which, of course, benefits not just those who wish to protect their privacy, but also those with malicious intent. How Cybercriminals Use Bulk Domains According to Malwarebytes, DGA is designed in a manner that makes it easy for hackers to change a variable or two without having to rewrite huge chunks of code, all while avoiding detection. DGA has three components: - Seed: The seed is any number, such as a specific time, date, or foreign exchange rate. - Time-based element: The time-based element refers to a condition that changes over time, such as events or trending topics. - TLDs: The TLDs involved are pseudo-random-looking domains that the algorithm dynamically generates by the thousands. Attackers register only a few of these domains for use. An example of a DGA-created domain looks something like this: t3622c4773260c097e2e9b26705212ab85[.]ws. A Dyre banking trojan used this particular domain. Malware and botnets commonly use DGA domains to query and pivot to communicate with command-and-control (C&C) servers. Once a malware strain compromises a computer, for instance, it begins to query multiple DGA domains to obfuscate C&C traffic. Summary of Bulk Domain Abuse Findings The following trends have emerged from our review of existing papers on bulk domain misuse: - 1. The most abused domain name extensions are .xyz, .cloud, .top, .tokyo, and .us, according to a study by the Interisle Consulting Group. Two of these domains (i.e., .xyz and .top) have been consistently found in the top 20 blocklists maintained by Symantec and Spamhaus in the past two years. To date, new TLDs like .buzz, .country, .link, and .download have also made it to popular watchlists. - 2. Attackers share the same resources. It only takes one mail server or domain to find out the nest of domains and subdomains they use. Often, these domains have a strong connection with affiliate ad networks or potentially unwanted programs. Hackers are also likely to use IP address spaces and Autonomous System numbers (ASNs) that are home to known threats. - 3. Incomplete WHOIS details are better than nothing. Incomplete WHOIS records can still guide investigators as they study attacks. Partial results reveal a lot about an attacker’s infrastructure, and analysts can use this data to identify other email and IP addresses or domains connected to an event. - 4. Long-term monitoring is needed to uncover abusive repeated registrations and how domains with high entropy figure in attacks. Indeed, a Danish study last year found that re-registrations for abused .dk domains and the use of high entropy domains in ongoing attacks were irregular. One reason is that DGA has become increasingly sophisticated and harder to detect. Future studies also have to widen the scope of their datasets to entire zones to improve the quality of samples. - 5. Similar to the last point, it is critical to monitor parked domains even if they’re not actively abused. According to the Interisle study, some domains don’t make it to a blocklist right away following registration. This finding implies that hackers buy and hold on to domains for later use. - 6. One of the hallmark characteristics of domains registered in bulk is the presence of random-looking strings. These strings are often the result of automation, suggesting that a registrar-owned name generator may have been used to create them. How Bulk Domain Name Checkers Can Help Thwart Attacks Registrars, cybersecurity professionals, and antimalware vendors can evaluate known and undiscovered risky domains with the help of a bulk domain checking solution. One example of this is Bulk WHOIS Search, which provides bulk WHOIS records for multiple domains. With the tool, users can: - Block malicious domains effectively: Users can quickly validate whether the traffic they’re receiving comes from legitimate sources or blacklisted sites. WhoisXML API has indexed over 6.7 billion historical WHOIS records from authoritative sources to provide the most accurate results. - Monitor domains for brand research and protection: Brand managers can rely on Bulk WHOIS Search to curb fraud and trademark abuse. They can use the application to routinely search for domain names that resemble or infringe their assets. The API can also be used to obtain WHOIS records for electronic discovery and domain disputes. - Resolve security incidents on time: Bulk WHOIS Search simplifies the process of querying WHOIS records for multiple domains found in firewall logs. The tool can also be used to reveal patterns when changes to WHOIS records are made, such as those concerning creation dates, contact names (before privacy), and registrars. Complete WHOIS data is invaluable to security professionals to respond timely to cyberattacks. When used with other threat intelligence solutions, bulk domain checking tools like Bulk WHOIS Search facilitates the swift detection of criminal actors’ servers and domains.Read the other articles
Serial Data Communication ProtocolsWhen multiple on-board computers need to communicate with each other, they must speak the samelanguage (protocol) at the same speed (baud rate). Starting in 1996, U.S. EPA regulations require that all automobile manufacturers establish a commoncommunications system for emissions related controllers. As it turned out, there were four differentprotocols used with a common data link connector (DLC). This section describes the four differentcommunication protocols used by most automobile manufacturers since 1996. Starting in 2008, U.S. EPA regulations require that all automobile manufacturers use a single commoncommunications protocol for emissions related controllers. This section describes the new standardizedcommunication protocol; Controller Area Network (CAN).The most significant result of these regulations is that the regulation provides the scan tool manufacturers This is the end of the preview. Sign up access the rest of the document.
It should come as no surprise when payloads generated in their default state get swallowed up by Defender, as Microsoft have both the means and motivation to proactively produce signatures for open and closed source/commericial tooling. One tactic to get around these is to generate heavily obfuscated, compressed, or encrypted payloads which are unpacked at runtime. However, highly entropic payloads can be just as problematc. Daniel Bohannon and Lee Holmes also wrote a paper called Revoke-Obfuscation: PowerShell Obfuscation Detection Using Science which shows several methods for detecting obfuscated PowerShell scripts. A philosophy that has stuck with me is to only make the minimum changes necessary to circumvent a particular static signature - i.e. solve the problem with a scalpel rather than a sledgehammer. This post will present a methodology for identifying “bad bytes” in a payload and finding their location within the compiled binary. To demonstrate, I will use ThreatCheck and Ghidra to analyze and modify a Beacon payload generated from Cobalt Strike. This is the easy part. ThreatCheck works by splitting the binary up into little chunks and scanning each one with Defender. It will attempt to find the smallest possible chunk that triggers a positive result and prints an array of bytes to the console. ThreatCheck was able to identify a block of code that Defender detects as malicious, but there is no context about which part of the payload it is. This is where Ghidra comes into play. Load the payload into a new project and have Ghidra run through its automated analysis. Then use the Search Memory function to find a sequence of bytes output from ThreatCheck. ThreatCheck always attempts to print 1024 bytes to the console by working its way backwards from the end of the “bad byte” range. So even though 1024 bytes are displayed, it’s not an indication that the entirety was malicious. Since the bad bytes are always at the end of those displayed, use a hex sequence from the bottom rather than the top. In this example, I’m searching for 8A 54 15 00 32 14 07 88 14 03 48 FF C0 EB E7 48. I have a single result at 004015d1 and clicking on the row will display the code main Ghidra window. The “Listing” view shows the CPU instructions in a simple list and the “Decompile” view attempts to reverse the code of the function back to its original source. Now we know that the offending block of code is likely this for loop inside The loop comes after a call to VirtualAlloc but before a call to CreateThread. After searching through Cobalt Strike’s Artifact Kit source code, we come across the spawn function located in patch.c. The loop is responsible for decoding the Beacon shellcode prior to execution and writing it into the allocated memory region. All we need to do is modify the loop so that it compiles to a different byte sequence (how you do that is up to you). Then, once the payload has been regenerated, Defender will no longer match on that static signature. This was a singular example of how to analyse and modify a Beacon payload from Cobalt Strike, but the same methodology can be applied to any payload generating tool for which you can access the source code. This post demonstrates that complex manipulations are not required to bypass static signatures and why defenders should not soley rely them to detect “well known” tooling.
Add a trusted IP address to allow connection to a network device such as a computer or printer in ESET Remote Administrator (6.x) If you are unable to connect to another computer or device, such as a printer on your network, you can add these devices to the trusted range of IP addresses defined on the computer you are trying to connect from. Endpoint users: Perform these steps on individual client workstations Open the ESET Remote Administrator Web Console. - Click Admin → Policies → New policy (or Policies → Edit to edit an existing policy). - Expand Settings and select ESET Endpoint for Windows from the product drop-down menu. - Click Firewall, expand Advanced, select Automatic mode from the Filtering mode drop-down menu and then click Edit next to Zones. - Select Trusted zone and click Edit. - Type the trusted IP adress(es) in the Remote computer address field. - Click Save and assign the policy to the designated host or group. The IP addresses used below are examples; you must enter the actual IP address of the computer/device that you are connecting to.
Need to Answer according to each question separately. Q1) Search “scholar.google.com” or your textbook. Include at least 250 words in your reply. Indicate at least one source or reference in your original post. Discuss ways organizations have built a CSIRT. What are the components of building an effective and successful CSIRT team? 2. Using a Web browser, look for the open-source and freeware intrusion detection tools listed in the chapter. Next, identify two to three commercial equivalents. What would the estimated cost savings be for an organization to use the open-source or freeware versions? What other expenses would the organization need to incur to implement this solution? 3. Using a Web browser, search on the term intrusion prevention systems. What are the characteristics of an IPS? Compare the costs of a typical IPS to an IDP. Do they differ? What characteristics justify the difference in cost, if any? 4. Using a Web browser, visit the site www.honeynet.org. What is this Web site, and what does it offer the information security professional? Visit the “Know your Enemy” whitepaper series and select a paper based on the recommendation of your professor. Read it and prepare a short overview of your class. 5. Using Table 5-4 and a Web browser, search on a few of the port numbers known to be used by hacker programs, such as Sub-7, Midnight Commander, and Win Crash. What significant information did you find in your search? Why should the information security manager be concerned about these hacker programs? What can he or she do to protect against them? 6. Using the list of possible, probable, and definite indicators of an incident, draft a recommendation to assist a typical end-user in identifying these indicators. Alternatively, using a graphics package such as PowerPoint, create a poster to make the user aware of the key indicators.
Niara’s user and entity behavior (UEBA) analytics use supervised and unsupervised machine learning techniques to detect anomalous behaviors and find attackers without up-front configuration. Supervised learning models, trained on large volumes of real world data, are applied to quickly surface indicators of compromise that would otherwise remain undetected. Niara’s unsupervised machine learning models ensure that the system is self-learning, continually adapting and accurately identifying anomalies even as attacks evolve. While Niara’s machine learning models deliver value immediately upon deployment, analyst-provided feedback enables the platform to transparently adapt to the uniqueness of the local environment in a learning loop. Niara automatically learns the local enterprise context through analyst classification on alerts (e.g., the development server admin regularly downloads large files, hence those activities should not be interpreted as anomalous) and delivers remarkably noise-free results, which is not possible with solutions that cannot adapt. Niara’s user and entity behavior (UEBA) analytics use security information in packet, flow, log, file, alert and threat feed data, to provide the most accurate information for attack detection. Analytic modules include authentication, remote access, resource access, file, protocol, and peer-to-peer analytics, enabling Niara to not only detect anomalies, but more reliably attribute malicious intent to them. Analytics are presented graphically using interactive visualizations. And with integrated forensics, Niara makes it easy to get complete context on why something was flagged as high risk. By providing Entity360 risk profiles that profile entities (i.e., users and hosts), Niara enables comprehensive attack detection – e.g., discovering compromised headless devices, anomalous access to servers and applications, etc. Entity risk profiles provide a consolidated visual representation of all security-relevant information associated with an entity (e.g., results of user behavior analytics or UBA), making it easy for analysts of all experience levels to observe anomalies and patterns. Niara’s use of unsupervised and supervised learning models enable anomalous behaviors to be linked to malicious intent more reliably. Niara’s analytics modules are multi-dimensional, profiling multiple orthogonal behaviors to make the system less prone to false positives. The outcome? Analysts can make better decisions because they have high confidence that any detected anomalies are indeed real. A big data foundation allows Niara to ingest diverse data sources (i.e., packets, flows, logs, files, alerts, threat feeds) regardless of volume, fuse it into a single stream while simultaneously reducing its size, distill it into graphical summaries that provide rich context, and correlate it all back to entities for unparalleled visibility across an organization. Niara provides cost effective horizontal scalability and the ability investigate across time as far as needed, be it weeks, months, or years. Convergence of analytics with forensics makes advanced attack detection and incident response more efficient
Document Type : Primary Research paper Universidad César Vallejo, Lima, Perú Universidad Nacional Federico Villareal, Lima, Perú Universidad Nacional Federico Villareal, Lima, Perú Universidad Femenina del Sagrado Corazón, Lima, Perú Universidad César Vallejo, Lima, Perú The objective of the study was to compare computer security software technologies based on intrusion detection systems in cyberspace in order to provide information to technicians or specialists to opt for the most optimal and quality service for their different criteria and technical qualities, such as: (a) Year of inception, (b) Countries Implemented, (c) Versions, (d) Type of software, (e) Operating System, (f) Cost, (g) Programming Language, (h)Definition, (i) Features and (j) Benefits. These criteria may benefit users to implement these IDS (Snort, Ossec, KFSensor, Spencer) in their projects or entities with hardware that allows them to maintain the care of their network based on rules and alerts that can be managed with levels of complexity depending on the type of malicious attack or anomaly detected and opt for a more optimal solution for the benefit of maintaining information security.
Introduction to Zero Trust Zero Trust is a cybersecurity approach that assumes no user or device on a network can be trusted. This means that all network elements, whether internal or external, must be treated as potential threats and have their access to resources verified before being allowed in. Zero Trust networks are designed with multiple layers of security to maintain complete control over the system, rather than relying on a single point of authentication or authorization. This helps to ensure that any unauthorized access attempt is blocked by default. Benefits of Zero Trust for Cybersecurity Zero Trust offers many advantages over traditional cybersecurity models regarding protection against threats. By constantly verifying network traffic in real time, Zero Trust provides an effective security solution that is both difficult to breach and easy to maintain. By verifying all traffic connections coming into the network, Zero Trust drastically reduces the chance of malicious actors gaining access to sensitive information. Zero Trust is designed to be adaptive and agile, allowing it to respond quickly to changes in the network. This will enable it to stay one step ahead of ever-evolving threats and helps protect delicate data from being compromised. Zero Trust also eliminates the need for costly and time-consuming manual configurations, as it can be quickly and easily deployed with minimal technical expertise. This makes it an ideal choice for companies of any size looking to increase their cybersecurity without breaking the bank. How is Zero Trust different from traditional cybersecurity? Traditional cybersecurity models rely on perimeter-based defense systems to protect networks from outside threats. This means that users have full authority over the system once they have access, leaving it vulnerable to malicious actors. Zero Trust eliminates this by assuming all traffic is potentially dangerous and verifying each request before granting access. This helps prevent unauthorized access and eliminates the need for manual configurations. Unlike traditional cybersecurity models, Zero Trust does not rely on a single point of authentication or authorization, making it much harder to breach. It also allows for more segmentation and granular control over resources, ensuring only authorized connections are granted access. This makes it an ideal choice for companies of all sizes looking to increase their cybersecurity posture. Adam:ONE Zero Trust The SME Edge utilizes a patented AI Zero Trust technology to protect your business: Adam:ONE. Adam:ONE manages all incoming and outgoing connections on your network in real-time and, utilizing its powerful AI DTTS (Don’t Talk To Strangers) technology, filters out all of the bad connections before they get to your devices. This ensures that all traffic is properly identified, validated, and authorized before being granted access. If a connection is not known as safe, it will be blocked by default, significantly reducing your business cybersecurity risk. Adam:ONE Zero Trust also offers granular control over resources, allowing you complete control over what individual devices do and do not have access to, even at specific times of the day. How the SME Edge can help your business The SME Edge is a complete cybersecurity package that includes Zero Trust connectivity, a business-grade hardware package with a warranty, and a complete cybersecurity deployment package, only available from Nerds On Site.
Microsoft windows represents the vast majority of home PC and a big number of servers as well. Because of its widespread and the complexity of its code (and probably the complexity of the coding processes...) a lot of vulnerabilities are discovered and exploited on this O.S. Windows is the main target of virus and malwares. Bankers, ransomers,ID stealers, D.O.S and spam bots, are the kind of malwares used by criminal organization to make millions of dollars. And nearly all this malwares target the Windows system. This section is focusing on threats targeting the Windows system and the security countermeasures.
shortest path between the targeted set of clients and that server. CCN content can be supplied by anything that has a copy and every CCN node can use any and all of its interfaces simultaneously to locate and retrieve a copy. Thus hiding content is exponentially more difficult for the attacker. It must establish a filtering perimeter around its targets that covers all paths to all possible copies of the consent. Any copy that makes it through the perimeter immediately becomes a new source that will virally propagate the content to all interested clients. Dro wning (DDo S) attacks can be mounted against sources of CCN content but are substantially more difficult than they are with TCP/IP. The flow balance between Interest and Data prevents any sort of Data flooding, so attackers must attack via Interest packets. Say an attacker marshals a horde of zombies to simultaneously generate interests in some ContentName. If they all use the same name, the Interests will be aggregated (at most one pending Interest in a name is ever forwarded over any link) and no flood will result. So they must all use different names under the targeted prefix. If the different names refer to actual ContentObjects, those objects will be cached everywhere along the paths from the content source(s) to the zombies; thus the flood near the source will quickly clear as Interests are satisfied by downstream cached copies of the Data.i If the zombie’s names are randomly generated then their Interests will never be satisfied by a matching Data and will time out. Thus every intermediate node learns that many bogus Interests are being generated for the targeted prefix. Nodes can decide to temporarily rate limit such Interests (similar to the push-back strategy used against TCP/IP DDoS) or simply prioritize them lower than Interests that are resulting in Data responses.j In either case the effect of the attack on legitimate traffic is minimized. 4. 5. Policy controls CCN also provides tools that allow an organization to exercise control over where their content will travel. Routers belonging to an organization or service provider can enforce policy-based routing, where content forwarding policy is associated with content name and signer. For example, PARC might have a “content firewall” that only allows Interests from the Internet to be satisfied if they are requesting content under the / parc.com/public namespace. An organization could also publish its policies about what keys can sign content under a particular name prefix (e.g., PARC could require that all content in the / parc.com namespace be signed by a key certified by a /parc. com root key), and have their content routers automatically drop content that does not meet those requirements, without asking those routers to understand the semantics of the names or organizations involved. Finally, Interests i This does result in a distributed cache poisoning attack that must be addressed in the CCN node’s cache replacement policy. j A CCN content router has a limit on the number of pending Interests it will allow on any link (generally related to the bandwidth × delay product of that link). The router can choose if it wants to hold or discard arriving Interests over the limit and how it selects Interests up to the limit. could in certain cases be digitally signed, enabling policy routing to limit what namespaces or how often particular signers may query. In this section we describe and evaluate the performance of our prototype CCN implementation. Our current implementation encodes packets in the ccnb compact binary XML representation using dictionary-based tag compression. Our CCN forwarder, ccnd, is implemented in C as a userspace daemon. Interest and Data packets are encapsulated in UDP for forwarding over existing networks via broadcast, multicast, or unicast. Most of the mechanics of using CCN (ccnd communication, key management, signing, basic encryption and trust management) are embodied in a CCN library. This library, implemented in Java and C, encapsulates common conventions for names and data such as encoding segmentation and versioning in names and representing information about keys for encryption and trust management. These conventions are organized into profiles representing application-specific protocols layered over basic CCN Interest-Data. This architecture has two implications. First, the security perimeter around sensitive data is pushed into the application; content is decrypted only inside an application that has rights to it and never inside the OS networking stack or on disk. Second, much of the work of using CCN in an application consists of specifying the naming and data conventions to be agreed upon between publishers and consumers. All components run on Linux, Mac OS X™, Solaris™, FreeBSD, NetBSD, and Microsoft Windows™. Cryptographic operations are provided by OpenSSL and Java. 5. 1. Data transfer efficiency TCP is good at moving data. For bulk data transfer over terrestrial paths it routinely delivers app-to-app data throughput near the theoretical maximum (the bottleneck link bandwidth). TCP “fills the pipe” because its variable window size allows for enough data in transit to fill the bandwidth × delay product of the path plus all of the intermediate store-and-forward buffer stages. 9 CCN’s ability to have multiple Interests outstanding gives it the same capability (see Section 3. 1) and we expect its data transfer performance to be similar to TCP’s. To test this we measured the time needed to transfer a 6MB file as a function of the window size (TCP) and number of outstanding Interests (CCN). The tests were run between two Linux hosts connected by 100 Mbps links to our campus ethernet. For the TCP tests the file was transferred using the test tool ttcp. For the CCN tests the file was pre-staged into the memory of the source’s ccnd by requesting it locally.k This resulted in 6278 individually named, signed CCN Data packets (ContentObjects) each with 1KB of data (the resulting object sizes were around 1350 bytes). k This was done so the measurement would reflect just communication costs and not the signing cost of CCN content production. l Since CCN transacts in packet-sized content chunks, the TCP window size was divided by the amount of user data per packet to convert it to packets.
Traditional network security relies on a strong defensive perimeter around a trusted internal network to keep bad actors out and sensitive data in. In an increasingly complex networking environment, maintaining a robust perimeter is increasingly difficult. Zero trust security is emerging as a preferred approach for enterprises to secure both their traditional and modern, cloud-native applications. Zero trust network architecture inverts the assumptions of perimeter security. In a zero trust network, every resource is protected internally as if it were exposed to the open internet. To establish zero trust security guidelines for industry and the U.S. federal government, the National Institute of Standards and Technology (NIST) establishes zero trust security guidelines in a series of publications starting with SP 800-207 on zero trust architecture in general and its companion SP 800-204 series on security standards for microservices. Here are NIST’s core zero trust architecture principles and the Kubernetes and Istio reference architecture recommended to apply them in practice. The Six Principles of Zero Trust Networking All communication should be secure, regardless of network location. Network location and reachability do not imply trust. Access requests inside an enterprise-owned or other private network must meet the same security requirements as communication from any other location. A rubric for a zero trust system is that you could expose it to the open internet and it would still be secure, with no unauthorized access to systems, data, or communication. All communication should be encrypted. Encryption on the wire prevents eavesdropping and also ensures messages are authentic and unaltered. This implies implementing at least TLS for all communication, with mTLS and associated secure workload identities as a best practice for service-to-service communication. Access to every resource should be authenticated and authorized based on dynamic policy. Service identity and end-user credentials are dynamically authenticated and authorized before any access is allowed. The dynamic context of the access request should be part of the access decision. This may include behavioral attributes like deviations from observed usage patterns or the state of the requesting asset like software versions installed, network location, and time/date of the request. When access is granted, it should be granted with the least privilege required. Access to resources should be bounded in space. The perimeter of trust around resources should be as small as possible—ideally zero. Access should be mediated by a policy enforcement point (PEP) in front of every resource that is capable of retrieving and enforcing access decisions. This should apply to all inbound, outbound, and service-to-service access. Access to resources should be bounded in time. Authentication and authorization are bound to a short-lived session after which they must be re-established. This ensures that access decisions are made frequently and with the most recent context available. Access to resources should be observable. As much information as possible should be collected and used to improve security posture. This allows the integrity and security posture of all assets to be continuously monitored and policy enforcement continuously assured. Also, insights gained from observing should be fed back to improve policy. Why Zero Trust Security Is Better Network reachability is not authorization. Unlike perimeter security, access to a service is not granted solely because that service is reachable. It must be explicitly authenticated and authorized as well. Limited blast radius of perimeter breaches prevents lateral movement by attackers. Authenticated and authorized workloads are protected from perimeter breaches. Bounding in time limits the risk of compromised credentials. Fine-grained policy. Bounding in space allows for high granularity of policy enforcement. Frequent policy evaluation. Bounding in time with dynamic policy enforcement on short-lived sessions ensures authorization is based on up-to-date policy. Secure, authentic communication. Encryption and strong workload identity limits reconnaissance and provides for authenticity of communication. Real-time and auditable assurance of security posture and regulatory compliance. Fine-grained observability allows real-time assurance and post-facto auditability of policy enforcement plus the necessary data for troubleshooting and analysis. How to Implement Zero Trust Security in Kubernetes with Istio: a Reference Architecture for Modern Microservices Applications As a companion to NIST’s standards for zero trust architecture in general, NIST has also published standards for how to apply zero trust principles specifically to microservices applications. Those standards, co-written by Tetrate founding engineer Zack Butcher, are codified in NIST’s SP 800-204 series. In the standard, NIST establishes a reference platform consisting of Kubernetes for orchestration and resource management with the Istio service mesh to provide the core security features. Kubernetes Security Gaps As Kubernetes is primarily focused on orchestration, resource management, and basic connectivity, it leaves zero trust networking security concerns to be addressed by other parties. The main networking security gaps in Kubernetes are (NIST SP 800-204B, §2.1.1): - Insecure communications by default - Lack of a built-in certificate management mechanism needed to enforce TLS between pods - Lack of an identity and access management mechanism - Firewall policy that operates at OSI L3, but not L7 and, therefore, unable to peek into data packets or to make metadata-driven decisions Service Mesh Fills Kubernetes Security Gaps: the Security Kernel for Microservices Applications To augment Kubernetes for security, Istio acts as a security kernel in the NIST reference architecture. Istio satisfies the three requirements of a reference monitor (NIST SP 800-204B, §5.1). Istio is: - Protected from modification - Verified and tested to be correct The Envoy data plane provides reference monitors by way of non-bypassable policy enforcement points (PEPs) in front of each service and at each ingress and egress gateway. The service mesh code is independent of the application so its lifecycle can be managed independently and it can’t be modified at runtime. And, the mesh is a tightly controlled element of the system that can be hardened with more eyes and closer inspection (NIST SP 800-204B, §5.1). And, as a dedicated infrastructure layer, Istio offers: - A unified way to address cross-cutting application concerns; - Standard plugins to quickly address those concerns and a framework for building custom plugins; - Simplification of operational complexity; - Easy governance of third-party developers and integrators; - Cost reduction for development and operations. To learn more about how to implement zero trust architecture, from a co-author of the federal security standards, read Zack Butcher’s Zero Trust Architecture white paper. For an in-depth guide to NIST’s security recommendations and how Tetrate can help you implement the standard, check out Tetrate’s Guide to Federal Security Requirements for Microservices. If you’re looking for the fastest way to get to production with Istio, check out our open source Tetrate Istio Distro (TID). TID is a vetted, upstream distribution of Istio—a hardened image of Istio with continued support that is simpler to install, manage, and upgrade. For organizations operating in a federal regulatory environment, Tetrate Istio Distro is the only distribution of Istio with FIPS-verified builds available. If you need a unified and consistent way to secure and manage services across a fleet of applications, check out Tetrate Service Bridge (TSB), our comprehensive edge-to-workload application connectivity platform built on Istio and Envoy.
Collusion attacks in Internet of Things: Detection and mitigation using a fog based model Source of Publication SAS 2017 - 2017 IEEE Sensors Applications Symposium, Proceedings © 2017 IEEE. This paper discusses the problem of collusion attacks in Internet of Things (IoT) environments and how mobility of IoT devices increases the difficulty of detecting such types of attacks. It demonstrates how approaches used in detecting collusion attacks in WSNs are not applicable in IoT environments. To this end, the paper introduces a model based on the Fog Computing infrastructure to keep track of IoT devices and detect collusion attackers. The model uses fog computing layer for real-time monitoring and detection of collusion attacks in IoT environments. Moreover, the model uses a software defined system layer to add a degree of flexibility for configuring Fog nodes in order to enable them to detect various types of collusion attacks. Furthermore, the paper highlights the possible overhead on Fog nodes and network when applying the proposed model, and claims that the Fog layer infrastructure can provide the required resources for the scalability of the model. Yaseen, Qussai; Jararweh, Yaser; Al-Ayyoub, Mahmoud; and Al Dwairi, Monther, "Collusion attacks in Internet of Things: Detection and mitigation using a fog based model" (2017). Scopus Indexed Articles. 1342.
Anomaly detection is an important task in machine learning, where the goal is to identify items that are significantly different from the majority of the data. In the case of unsupervised anomaly detection, the algorithm is not given labeled data to learn from. Instead, it must identify anomalies purely based on the patterns in the data itself. There are several approaches to unsupervised anomaly detection, including statistical methods, clustering, and neural networks. Each approach has its strengths and weaknesses, and the choice of method depends on the specifics of the problem at hand. Statistical methods are often used in unsupervised anomaly detection because they can be relatively simple to implement and interpret. One common approach is to fit a probabilistic model to the data, such as a Gaussian distribution. Any data point that falls far outside the range expected by the model is considered an anomaly. Another statistical technique for anomaly detection is the use of density-based methods, such as the Local Outlier Factor (LOF) algorithm. These algorithms identify anomalies as any data point that has a significantly different local density than its neighbors. Clustering algorithms are a popular choice for unsupervised anomaly detection because they can identify clusters of data points that are significantly different from the majority of the data. One common approach is to use a density-based clustering algorithm, such as DBSCAN, to identify dense clusters in the data. Any data point that falls outside these clusters is considered an anomaly. K-means clustering is another popular clustering algorithm that can be used for anomaly detection. In this approach, the data is divided into k clusters based on their similarity. Any data point that does not fit well within any of these clusters is considered an anomaly. Neural networks have become an increasingly popular tool for unsupervised anomaly detection in recent years, especially with the advent of deep learning. One approach using neural networks is to use an autoencoder, a type of neural network that tries to reconstruct the input data as accurately as possible. Any data point that the autoencoder does not reconstruct well is considered an anomaly. Generative adversarial networks (GANs) are another type of neural network that can be used for unsupervised anomaly detection. In this approach, the GAN is trained on a dataset of normal data, and any data point that the GAN cannot generate well is considered an anomaly. This approach has been shown to be effective in detecting complex anomalies, such as those in image data. Unsupervised anomaly detection can be a challenging task, especially when the anomalies are rare and difficult to detect. One major challenge is in choosing the appropriate algorithm for the problem at hand. Depending on the specifics of the data, some algorithms may be more effective than others. Another challenge is in setting the threshold for what is considered an anomaly. In many cases, it is not clear what threshold should be used, and different thresholds may result in different sets of anomalies being detected. A third challenge is in evaluating the performance of unsupervised anomaly detection algorithms. Since there is no labeled data to compare the results to, it can be difficult to determine how well the algorithm is actually performing. Unsupervised anomaly detection is an important task in machine learning, with many different approaches available. The choice of method depends on the specifics of the problem at hand, and no single approach is guaranteed to be effective in all cases. However, by understanding the strengths and weaknesses of different algorithms, it is possible to develop effective solutions to a wide range of anomaly detection problems. © aionlinecourse.com All rights reserved.
AppSolid is a cloud-based service designed to protect Android apps against reverse-engineering. According to the editor’s website, the app protector is both a vulnerability scanner as well as a protector and metrics tracker. This blog shows how to retrieve the original bytecode of a protected application. Grab the latest version of JEB (2.2.5, released today) if you’d like to try this yourself. Once protected, the Android app is wrapped around a custom DEX and set of SO native files. The manifest is transformed as follows: - The package name remains unchanged - The application entry is augmented with a name attribute; the name attribute references an android.app.Application class that is called when the app is initialized (that is, before activities’ onCreate) - The activity list also remain the same, with the exception of the MAIN category-filtered activity (the one triggered when a user opens the app from a launcher) - A couple of app protector-specific activity are added, mainly the com.seworks.medusah.MainActivity, filtered as the MAIN one Note that the app is not debuggable, but JEB handles that just fine on ARM architectures (both for the bytecode and the native code components). You will need a rooted phone though. The app structure itself changes quite a bit. Most notably, the original DEX code is gone. - An native library was inserted and is responsible for retrieving and extracting the original DEX file. It also performs various anti-debugging tricks designed to thwart debuggers (JEB is equipped to deal with those) - A fake PNG image file contains an encrypted copy of the original DEX file; that file will be pulled out and swapped in the app process during the unwrapping process Upon starting the protected app, a com.seworks.medusah.app object is instantiated. The first method executed is not onCreate(), but attachBaseContext(), which is overloaded by the wrapper. There, libmd is initialized and loadDexWithFixedkeyInThread() is called to process the encrypted resources. (Other methods and classes refer to more decryption routines, but they are unused remnants in our test app. 1) The rest of the “app” object are simple proxy overrides for the Application object. The overrides will call into the original application’s Application object, if there was one to begin with (which was not the case for our test app.) The remaining components of the DEX file are: - Setters and getters via reflection to retrieve system data such as package information, as well as stitch back the original app after it’s been swapped in to memory by the native component. - The main activity com.seworks.medusah.MainActivity, used to start the original app main activity and collect errors reported by the native component. The protected app shipped with 3 native libraries, compiled for ARM and ARM v7. (That means the app cannot run on systems not supporting these ABIs.) We will focus on the core decryption methods only. As seen above, the decryption code is called via: m = new MedusahDex().LoadDexWithFixedkeyInThread( getApplicationInfo(), getAssets(), getClassLoader(), getBaseContext(), getPackageName(), mHandler); Briefly, this routine does the following: - Retrieve the “high_resolution.png” asset using the native Assets manager - Decrypt and generate paths relative to the application - Permission bits are modified in an attempt to prevent debuggers and other tools (such as run-as) to access the application folder in /data/data - Decrypt and decompress the original application’s DEX file resource - The encryption scheme is the well-known RC4 algorithm - The compression method is the lesser-known, but lightning fast LZ4 - More about the decryption key below - The original DEX file is then dumped to disk, before the next stage takes place (dex2oat’ing, irrelevant in the context of this post) - The DEX file is eventually discarded from disk Retrieving the decryption key statically appears to be quite difficult, as it is derived from the hash of various inputs, application-specific data bits, as well as a hard-coded string within libmd.so. It is unclear if this string is randomly inserted during the APK protection process, on the server side; verifying this would require multiple protected versions of the same app, which we do not have. A dynamic approach is better suited. Using JEB, we can simply set a breakpoint right after the decryption routine, retrieve the original DEX file from disk, and terminate the app. The native code is fairly standard. A couple of routines have been flattened (control-flow graph flattening) using llvm-obfuscator. Nothing notable, aside from their unconventional use of an asymmetric cipher to further obscure the creation of various small strings. See below for more details, or skip to the demo video directly. Technical note: a simple example of white-box cryptography The md library makes use of various encryption routines. A relatively interesting custom encryption routine uses RSA in an unconventional way. Given phi(n) [abbreviated phi] and the public exponent e, the method brute-forces the private exponent d, given that: d x e = 1 (mod phi) phi is picked small (20) making the discovery of d easy (3). The above is a simple example of white-box cryptography, in which the decryption keys are obscured and the algorithm customized and used unconventionally. At the end of the day, none of it matters though: if the original application’s code is not protected, it – or part of it – will exist in plain text at some point during the process lifetime. The following short video shows how to use the Dalvik and ARM debuggers to retrieve the original DEX file. This task can be easily automated by using the JEB debuggers API. Have a look at this other blog post to get started on using the API. The Jar file aj_s.jar contains the original DEX file with a couple of additions, neatly stored in a separate package, meant to monitor the app while it is running – those have not been thoroughly investigated. Overall, while the techniques used (anti-debugging tricks, white box cryptography) can delay reverse engineering, the original bytecode could be recovered. Due to the limited scope of this post, focusing on a single simple application, we cannot definitively assert that the protector is broken. However, the nature of the protector itself points to its fundamental weakness: a wrapper, even a sophisticated one, remains a wrapper. - The protector’s bytecode and native components could use a serious clean-up though, debugging symbols and unused code were left out at the time of this analysis. ↩
There are many reasons to go directly to vps windows. Nowadays, many programmers, developers, amateurs are tempted by this system and have not been disappointed at all. And you will know why? The first advantage of this brand new server is this power that can be exploited from the machine. Disk footprint and memory are minimized. Do not forget to mention that this allows to offer a field of impact to computerization. This implies that it is possible to place more virtual machines on the same server. Many features are provided: the creation of a compute node or storage, the establishment of a DNS server and an ultra-lightweight HTTP server and the execution of a server application. And the most impressive thing about all this is that the launch time gets faster. It is also important to note that storage capacity will also increase. More space to store mailboxes, files, various information, tools, etc. ; it's that the majority of users are looking for. And with windows vps, we can enjoy a more economical, expandable and high-performance alternative. Practical and advantageous, is not it? Feeling safer is an opportunity to feel freer, too. Data, information, various contents, identities, etc. ; many are the uses that would like to see all these protected points. And with the windows vps, no need to worry. A function of this system makes it possible to ensure the integrity of the software of the server but also, makes it possible to ensure that any modification does not put in question the level of confidence which one grants often to the machine. Securing virtual machines has become an essential point that must be prioritized. And opt for this system would be advantageous. Ensure that no attack can affect the system, the contents in the machine but also, the machine itself, ensure that the network is never saturated, prioritize the protection of all data that the user does not encounter no leakage or loss, etc. ; many are the benefits.
American journal of Engineering Research (AJER) A Mobile Ad-hoc NETwork (MANET) is an autonomous network. It is a collection of mobile nodes that communicate with each other over wireless links. From last few years, the interest in the area of Mobile Ad-hoc NETwork (MANET) is growing due to its practical applications and requirement of communication in mobile devices. In the comparison to wired or infrastructure-based wireless network, MANET is vulnerable to security attacks due to its fundamental characteristics, e.g., the open medium, dynamic network topology, lack of clear lines of defense, autonomous terminal, lack of centralized monitoring and management.
Fugue, the company empowering engineers to build and operate secure cloud systems that are compliant with enterprise policies, announced it has open-sourced Regula, a tool that evaluates Terraform infrastructure-as-code for security misconfigurations and compliance violations prior to deployment. Regula rules are written in Rego, the open-source policy language employed by the Open Policy Agent project and can be integrated into CI/CD pipelines to prevent cloud infrastructure deployments that may violate security and compliance best practices. “Developers design, build and modify their own cloud infrastructure environments, and they increasingly own the security and compliance of that infrastructure,” said Josh Stella, co-founder, and CTO of Fugue. “Fugue builds solutions that empower engineers operating in secure and regulated cloud environments, and Regula quickly and easily checks that their Terraform scripts don’t violate policy—before they deploy infrastructure.” Regula initially supports rules that validate Terraform scripts written for AWS infrastructure and includes mapping to CIS AWS Foundations Benchmark controls where relevant. Regula also includes helper libraries that enable users to easily build their own rules that conform to enterprise policies. At launch, Fugue has provided examples of Regula working with GitHub Actions for CI/CD, and with Fregot, a tool that enables developers to easily evaluate Rego expressions, debug code, and test policies. Fugue open-sourced Fregot in November 2019. Regula can identify serious cloud misconfiguration risk contained in Terraform scripts, many of which may not be flagged by common compliance standards. The initial release of Regula includes rules that can identify dangerously permissive IAM policies and security group rules, VPCs with flow logs disabled, EBS volumes with encryption disabled, and untagged cloud resources. View the full set of initial Regula rules here.
After a short night due to social events and business related tasks, I joined the Google offices to follow a bunch of interesting presentations. If Botconf offers a great set of presentations, that’s also a good place for networking and to talk about infosecurity topics while having very nice food! Here is my wrap-up for the second day which was of the same quality as yesterday. The first one was about DGA: “DGArchive – A deep drive into domain generating malware” by Daniel Plohmann. As usual, it started with a review of the DGA, nothing new basically (it was already covered yesterday). Last year, Daniel made a lightning talk about his project and, today, he presented the results of his research. A small history of DGA: - The first one was in 2006 (Sality which dynamically generated a 3rd-level domain part) - In July 2007, Torpid and Kraken were discovered - In 2008 – 2009, Szribi and Conficker DGA is a key feature in modern malwares. Why is it so broadly used? - Aggravation of analysis (make this more difficult) - Evasion (to avoid blacklisting) - Asymmetry (attackers needs only one when defenders must block all) - Feasibility (domains are cheap) And, more important, they are annoying security researchers! The idea of the research was to reverse DGA, generate all of them and build a database to perform queries and statistics. The goal behind this was to look for a domain and the database returns the associated malware. Until today, Daniel identified: - 43 families - 280 seeds - 20+M domains Many DGA uses long domains names (as the opposite of business domains which must be as short as possible). An important element are seeds that influence the generation of domains. The process implemented by Daniel is: - Matching (automatically detected new seeds) In the next part of the presentation, Daniel explained how domains are generated per malware family with lot of details. Then, the next question was: What about the domain registration? Based on whois databases, he was able to identify characteristics of domains, sinkholes, mitigations, pre-registration, domain parking, etc. The question about DGA is: are they reliable? What about collisions between algorithms and are they risks to generate valid domain names. In this case, this could have a disastrous effect for the owner of the valid domain! Yes, collisions are possible. But not enough to help to classify the malware based on the generated domains. The next talk focused on the Andromeda botnet. Jose Miguel Esparza presented “Travelling to the far side of Andromeda”. This was not a talk about reversing the bonet (because a lot of information are already available) but more a talk about the people behind it. A few words about Andromeda: - It started in 2011 - It is modular and versatile - Ping C&C regularly asking for “tasks” (new malwares, plugins, etc) - Spread via classic ways - Current version is 2.10 It evolved with new features like anti-analysis and a list of blacklisted process (even python.exe and perl.exe). Parameters are send in JSON with the last release. Note also that communications occur over XMPP and not IRC anymore to rebuild the binaries (standard communications remains over HTTP). Malware developers also leave some messages from time to time like fake urls containing “fuckyoufeds” :-). An interesting feature: it does not infect computers located in some regions like Russia (the localization is based on the keyboard layout). There is a real business behing Andromeda and the botnet is sold with terms of service that are worse then the ones of Google of Facebook! Here is an idea of the current prices: - A bot v2.x: $500 - To rebuild the bot: $10 - SOCKS5 module: free - Formgrabber module: $500 - Key logger module: $200 - TeamViewer module: $500 And the botnet is still alive, some statistics: - 10750 samples - 130 botnets - 474 builder IDs - 42K C&C URLs Conclusions: the project is still alive and the business ongoing. It is used by serious criminal gangs and has interesting custom plugins. A nice overview! After the morning coffee break, Nikita Buchka and Mikhail Kuzmin presented “Whose phone is in your pocket?”. Android is a nice target for malwares. In Q3 2015, 1.5M+ malicious apps were detected. A trend is the attacks that use superuser privileges. Most malicious apps are adware, the infection occurs via trojanized ads. They explained how the advertisement model works on Android and, most important, how it can be abuse by attackers. Even if a campaign is abused to spread malwares, brands are still happy because they are promoted, so what? Most adware try to root the devices to get persistence. How? The security model of Android is based one: - A RO system partition But they are problems: - Binder IPC mechanism -> data can be hijacked - Root user exists … and it can break the model. “zygote” is a daemon whose purpose is to launch Android apps. To install a malware, the procure is based on the following steps: - Obtain root access (easy on old versions) - Remount the system partition in RW mode - Install the malicious apk - Remount it in RO mode When adware is not enough, other malicious code can be installed. A good example is Triada: it comes with SMS trojan, banking trojan, update module, communication with C&C. They explained how the malware infects the device. And what about mitigations? - The malware cannot be uninstalled (RO partition) - One solution is to “root” your own device (not recommended) - Flash a stock firmware (not easy without technical skills + lost of data - Dealt with? The next talk topic was again DGA: “Building a better botnet DGA mousetrap: separating mice, rats and cheese in DNS data” (Josiah Hagen). The fourth (4!) talk covering DGA… I think that we are now aware of this technique to obfuscate communications between bots and their C&C… Just that this time, it involved machine learning. A private joke started in the afternoon about a potential name change from “Botconf” to “DGAconf“… Apostolos Malatras did an interesting talk about mobile botnets and more precisely, about building a lab to study them (“Building an hybrid experimental platform for mobile botnet research”). If the previous talk focused on how malwares compromised Android devices, this talk reviewed how botnets installed on those infected devices work. In fact, it’s the same as a regular botnet: devices are waiting for commands from the botmaster. Keep in mind that mobile devices are also computers, they have the same features but they contain a rich set of information about the owner (read: lucrative gains ahead). They are also connected to other computers, to corporate networks. They have nice sensors and more and more are used as mobile wallets! The technical particulates of mobile devices are: - They use dynamic ip addresses - There are many constraints by mobile networks - There are a lot to of different os versions (is it really bad?) - The size of the screen can be a vulnerability (did the user click on the right link?) - Sensors can be used as side channels About the botnets, they are different architectures: centralised, hierarchical , hybrid and P2P. Those must be covered in the lab. This one is must meet certains goals: it must be generic to support many experiments, it must be scalable, extensible and with a sufficient usability. Apostolos reviewed the different components of the architecture (Java technologies, Android emulator, Android debug bridge, XML configuration files and Sensor simulator to create events). The goal is to test mobile botnet and observe their operations. It also execute events based on scenarios: What happend when the mobile does that or that… The next question which comes immediately in mind is: “how long will it take before mobile malware developers will implement test to bypass Android emulators? In fact it’s quite trivial to do (just via the IMEI number!). Have a look at the following paper for more details. Just after Apostolos, Laurent Beslay introduced the “Mobile botnet malware collection” which was more a tribune to the EU services. They are recruiting and started a program to exchange information about mobile botnets. After a delicious lunch, Paul Jung came on stage to present “Box botnets”. Good news: no IDA slides in his presentation! 🙂 All the story started with a strange HTTP request seen in a log file! Attackers try constantly to infect websites with malicious scripts hidden in other files like GIF files. This code is often obfuscated using str_rot13(), gzuncompress(). Decoding them is easy using online tools like ddecode.com/phpdecoder. Important warning from Paul: most sites which provide online services like this one keep a copy of the data you uploaded. Keep this in mind if your data are sensitive! So, how to infect a host? The scenario requires: - A PHP enabled UNIX web server - A weak CMS - A direct access to the wild Internet (for back connections) Based on this description, popular targets are VPS! Then also implement some tricks like change the process name, they intercept all signals preventing the process to be killed. They also always have a “snitch” function to leak server info via email or a specific HTTP request. Once infected, the machine being part of the botnet can: - Execute stuff (difficult with modern distro which runs the webserver under its own user) - Perform maintenance tasks (change channel, rename bot) - Send spam - UDP/TCP/HTTP flooding - And… seek for other servers to compromise! By using multiple search engines (Paul found 37 of them!), they search for new potential victims. The next part of the talk focused on who’s behing such bots. The team is called Toolsb0x. This is not a state of the art way to compromize computers but… it still works! Then, we switched to a deeper talk with many assembler code: “Malware instrumentation: application to Regin analysis” by Matthieu Kaczmarek. Modern pieces of malware are very complex today. Why Regin? Because it’s a botnet. The network topology is a botnet. Keep in mind that communications can be performed in a mix of UDP, TCP, cookies, files, USB sticks… You also need a window open to the world. On top of the network, there is a trust overlay. Each node has a private key and a list of trusted public keys. In the botnet, each node has also a virtual IP address. The design is a service oriented architecture with: - An orchestrator - Core modules (take care of crypto, compression, VFS, networking, etc) - Additional modules (probes, agents, etc) After multiple slides explaining the techniques behing Regin, Matthieu gave a demo of a communication between two Regin modules… The demo was the exchange of a “hello” message between two nodes. It looked so simple but the amount of time and effets spent to reverse all the stuff is so huge! An impressive work! After the coffee break, Mark Graham presented “Practical experiences of building an IPFIX based open source botnet detector”. What’s was Mark’s problem: How to effectively detect botnets in cloud providers? According to Mark, the cloud is a nice place to look for botnets activities. The first part of the talk was an introduction to IPFIX (which honestly I was not aware of!). Everybody knows Netflow (created by Cisco in 2009) but IPFIX is almost unknown (based on the Botconf audience). What are the issues related to Netflow? - Host escape - Intra VM attacks - VM escape In 2013, IPFIX was invented. A big advantage of IPFIX is the required storage. Mark did some tests and a file transfert resulted in a 3.1GB PCAP file but… only 43KB IPFIX file! PCAP can be compared to phone call where IPFIX can be compared to the phone bill (who, when, how long). More precisely, IPFIX was developed to fix the following issues: - Vendor independent - Multiple protocols (not only UDP) - More security - Ready for next generation (IPv6, multicast, MPLS) The second part of the talk covered the development of sensors based on Xen & OVS (Open vSwitch). Mark explained the issues he faced with the different version of the required components. Once built and configured, the next issue was to find the right location to connect probes. The visibility of the network is a key! Once the right number of probes connected at right places, we can find useful information but there are still limitations to the system: - Deep packet inspection (discarding the payload as a cost…) - Encryption / VPN traffic : payload is not an issue but PDU headers within a VPN tunnel has an impact The solution proposed by Mark was to create an extended template now with DNS and HTTP parameters (like cookie, age, via, referer). A nice talk which make me learn about IPFIX! The next presentation focused on the threat landscape in Brazil with Tal Darsan (“The dirty half-dozen of the Brazilian threat landscape”). What’s going on in Brazil today? They use Delphi, VB script and C#. They are using packers: CPL and VBE trends. Themida packer. They have a unique fraudster underground community, a comprehensive attack vectors with a naive approach and they bundle legit tools for malicious purposes. You can buy trainings to learn how to fraud. So, what are the most popular vectors? - Image based phishing attacks. Tal explained the Boleto attack. - Fake browsers: used to steal bank credentials (dropper is delivered via a small size downloader (banload) - Overlay attack (similar to the fake browser – create an overlay of the browser content – browser not replaced) - Remote overlay : MITM attack created with… VNC A nice review of the threats in Brazil! For your information, here is a website where you can buy services to learn “hacking“: http://www.hackerxadrez.com.br/ Ya Liu presented the last talk for today: “Automatically classifying unknown bots by the register messages”. The idea of this research was to categorise botnets based on the messages then exchange with their C&C once a new computer is infected. As many variants of malwares are discovered daily, new techniques must be found to classify them. Most malwares can be grouped into well-known families like zbot or darkshell. They have one point in common: they need to communicate with C&C. The idea of Ya was to analyze how they register themselves to the C&C (the first action performed after a successful infection). Register messages contain information like hostname, IP, CPU, OS, version, etc. Ya reviewed how such information is encode and sent to the C&C. Interesting research! The second day finished with a session of lightning talks (12 x 3 minutes of speed talks) just before the usual social event. This year is was on the top floor of the French National Library with a very nice view on Paris by night:
Preventing Baseline Drift, and Preventing Pirated Software from Being Installed Russell Smith, Security Expert, IT consultant About this Webinar Watch this Windows security webinar now.For years organizations have been deploying customized images of Windows to PCs, not only to expedite software installation and provide a default configuration, but also to reduce support costs. A standardized image helps prevent issues arising, but when they do, they can be resolved faster if the configuration of the device is in a known state. Unfortunately, the prevalence of administrative rights and lack of application control allows users to modify system settings and install unwanted software, quickly moving devices away from a default set of configuration standards. In this webinar, Russell Smith discusses how to overcome some of the challenges of removing administrative privileges from end users, and the options of implementing application control. You'll learn: - The challenges related to using standard user accounts in Windows, and how to overcome them. - How Group Policy and Group Policy Preferences can be used to prevent baseline drift. - The built-in options for implementing application control.
Zero Trust Security Best Practices: How to Implement a Solid Defense Strategy Change is inevitable when it comes to security concerns. Every day, thousands of new cybersecurity risks and threats emerge. These cybersecurity threats are getting advanced uncontrollably while they are growing in size. This is the main reason why stricter privacy and security standards are getting enforced. New times demand new measures. The technology and tools in cybersecurity are advancing to combat sophisticated threats and protect networks. The latest developments in technology also shape the current cybersecurity trends. Now, the latest trend in cybersecurity remains Zero Trust security since it offers foolproof support with its “trust none, verify all” approach. As a whole, Zero Trust follows a stricter approach to maintaining cybersecurity and protecting company assets. Also, Zero Trust can efficiently solve issues regarding excessive security tools, user accountability concerns, and security of rapidly changing network perimeter. Now that enterprises run their businesses on-premise and in the cloud, the dynamic changes in network perimeter are non-trivial. With Zero Trust security, it is easier for businesses to ensure security throughout these dynamic changes. Businesses can only reap the full benefits of Zero Trust security as long as it’s properly implemented and utilized. In this sense, we will present the best practices for building a solid defense technology with Zero Trust security. Best Practices for Zero Trust Security Like every other strong technology, Zero Trust security is also built with pillars. If one of these pillars is missing, Zero Trust can’t perform as efficiently. In this case, pillars are the best practices of Zero Trust to build a robust defense. Identify The Protection Surface Understanding what to protect gives businesses ideas about how to actually protect them. Company data is the core component of Zero Trust security. That’s why the protection surface should be determined first and foremost. This practice establishes a foundation for implementing Zero Trust security efficiently. Businesses must tightly secure their valuable data and information on their networks. In order to do that, businesses have to identify their critical data and where it’s stored to properly understand the protection surface. Map Out The Assets, Connections, and Infrastructure of Your Network Once businesses understand the protection surface, the next thing they should do is map the infrastructure of their network, which includes users, devices, assets, connections, access, software, and services. This process entails understanding where security controls are required. So, mapping applications in use, network data traffic flow, connections, used devices and services should be comprehensive. The mapping process also helps to determine and evaluate the conditions of company assets. For instance, the most vulnerable assets are those connected to the Internet. So, assets with Internet connections should be evaluated thoroughly with this practice. Companies can also identify vulnerabilities while mapping out their network infrastructure and implement Zero Trust security effectively. Microsegment the Network After understanding what to protect and mapping out the network infrastructure, companies should implement network segmentation for better Zero Trust security. Microsegmentation is required in Zero Trust security to reduce the attack surface, prevent lateral movement and implement extensive security measures around critical data. When the protection surface is micro-segmented, tools and technologies such as firewalls and intrusion prevention systems can be utilized more effectively to monitor data flows, detect and respond to malicious activity, and protect network assets and sensitive data. So, microsegmentation allows companies to establish a healthy environment for Zero Trust implementation. Keep in mind that these tools are also components of Zero Trust security. So, additional security solutions should be enhanced and secured properly. Make Use of Multifactor Authentication Only using passwords to verify the credentials of authorized users is proven to be inadequate. Nowadays, passwords can be easily stolen or guessed. On top of this, cybercriminals sell these stolen passwords in bulk on the black market and dark web as well. That’s why strengthening the authentication process is necessary. In this sense, companies must implement two-factor authentication or multifactor authentication to protect their critical assets. Multifactor authentication enhances the process of verifying the identity of privileged users to ensure it is in fact them accessing critical data and preventing them from accessing other unrequired information. Because of the fact that MFA requires more steps for authentication, cybercriminals can access the company network with just stolen credentials. So, MFA prevents unauthorized access to sensitive data in the networks. Also, MFA is a crucial tool especially to ensure cloud security with Zero Trust. Overall, Zero Trust security is stronger with the implementation of MFA. Apply The Principle of Least Privilege The principle of least privilege (PoLP) indicates the access levels of users in a Zero Trust environment. The principle of least privilege is a principle that only grants access to a minimum amount of resources for users to perform a certain task or function. When PoLP is combined with Zero Trust security, not only do users have to verify their identity, but also have limited access to particular data and can do so much with them. So, the attack surface on the protected data can be mitigated while restricting lateral movement. Additionally, just-in-time privileged access can be enabled by expanding PoLP. Just-in-time privileged access restricts users’ authorization to a specific time frame, meaning that their privileges can expire for a certain period. Implement Zero Trust Policies Another pillar of building a robust defense technology with Zero Trust security is policies. Zero Trust policies of your business should address the identified key risks and vulnerable areas of the network, and strengthen the security of the network. The latest trend in cybersecurity, Zero Trust security, is a great technology for maintaining the security of critical information and valuable assets of business networks. With its “trust none, verify all” philosophy, Zero Trust accepts cybersecurity threats are everywhere and combats them accordingly. To unlock its full potential and build a solid defense system, businesses must implement the best practices.
To get employees more involved in securing their Apps accounts, Google has tried to simplify how they monitor log-in activity and configure security settings. It's key for Apps users to get more engaged in this manner, because that way they complement the efforts of their company's IT department and of Google itself. "Security in the cloud is a shared responsibility," Eran Feigenbaum, security director at the Google for Work team, wrote Monday in a blog post. "By making users more aware of their security settings and the activity on their devices, we can work together to stay a step ahead of any bad guys," A new dashboard gives users a snapshot of all the devices that have been used to access their account in the past 28 days, including any currently signed in, along with their approximate location, and displays prominently a link for changing their password if they notice any suspicious activity. Users can also revoke a device's access to the account. In addition, Google has rolled out a wizard designed to guide users through the steps to activate or adjust security settings and features. The wizard takes into account domain settings and preferences established by IT administrators for their employees, so that users are only able to make choices based preset permissions.
This chapter attempts to cover everything you ever wanted to know about media processing resources and media connection processing, but were afraid to ask. It might not answer all the questions you have on the subject, but it should at least discuss the salient points and provide insight into how media streams are controlled and handled by Cisco CallManager. Software applications such as Cisco MeetingPlace are not discussed in this chapter. Although MeetingPlace is a very powerful and useful system, has many useful functions and uses CallManager to connect calls to its conference bridges, it does not register with CallManager and cannot be controlled by CallManager directly. Because CallManager cannot allocate or control conference bridges or any other facilities provided by MeetingPlace, it is not discussed in this chapter; this chapter focuses on devices controlled directly by CallManager. There are two signaling layers within CallManager. Each signaling layer has distinct functions. The Call Control Layer handles all the normal call signaling that controls call setup, teardown, and call routing. The second signaling layer is the Media Control Layer, which handles all media connection signaling required to connect the voice and video paths or media streams of the calls. This chapter focuses on the Media Control Layer and is divided into two major sections: Chapter 3, "Station Devices," and Chapter 4, "Trunk Devices," cover call control signaling for both phones and gateways. Figure 5-1 shows the block structure of CallManager. Figure 5-1. CallManager Block Structure Diagram Figure 5-1 highlights the software layers and blocks within CallManager that are described in detail in this chapter. Other blocks are touched on lightly but are not highlighted because they are not covered in detail here. The software in the Media Control Layer handles all media connections that are made between devices in CallManager. The Call Control Layer sets up and controls all the call signaling connections between call endpoints and CallManager. The Media Control Layer directs the devices to establish streaming connections among themselves. It can insert other necessary media processing devices into a call and create appropriate streaming connections to those devices without the Call Control Layer knowing about them. The Media Control Layer becomes involved in a call when the Call Control Layer notifies the Media Control Layer that a call has been connected between two endpoints. The Media Control Layer then proceeds to establish the media streaming connections between the endpoints as required to set up the voice path for that call. In some cases, the media streaming connections are established before the call is connected. CallManager connects the media streams early such as when a call is destined for the public switched telephone network (PSTN) through a gateway. The caller then hears the progress tones and announcements from the PSTN telling them what happened to the call such as ringback tone, busy tone, "The number you have called is not a working number", or "All circuits are busy now. Please hang up." If the endpoints in the call report video capabilities, CallManager checks the locations bandwidth and if it allows video, it automatically attempts to open a video channel between the endpoints for the call. Whether or not video is actually sent on that channel depends on the video mute setting of the endpoint devices involved and whether sufficient bandwidth is available. The blocks highlighted in the Protocol/Aggregation layers of Figure 5-1 are those that control the media processing devices. They provide the device interface and handle all communication between the devices and CallManager. The Media Resource Manager (MRM) is a software component in CallManager that handles all resource allocation and de-allocation. When call processing or a supplementary service determines that a media processing resource of a particular type is needed, the request is sent to the MRM. The MRM finds an available resource of the requested type, allocates the resource, and returns the resource identification information to the requestor. Cisco CallManager Architecture Manageability and Monitoring Call Detail Records Appendix A. Feature List Appendix B. Cisco Integrated Solutions Appendix C. Protocol Details
The free tool, called DOM Snitch, is designed to sniff out potential security holes in Web applications' client-side code that could be exploited by attacks such as client-side scripting, Google said on Tuesday. In addition to developers, DOM Snitch is also aimed at code testers and security researchers, the company said. The tool displays DOM (document object model) modifications in real time so developers don't have to pause the application to run a debugging tool, according to Google. DOM Snitch also lets developers export reports so they can be shared with others involved in developing and refining the application, Google said. Google is working on DOM Snitch and on server-side code testing tools such as Skipfish and Ratproxy because it believes that the number of security holes in Web applications is growing along with their overall sophistication and complexity.
Data Loss Prevention Data Loss Prevention (DLP), is a technology that protects data from hackers, viruses, and other threats. File transfer protocol. DLP is a more effective strategy for companies, as it can be used on a wider scale. DLP is a security strategy that helps companies detect, prevent and respond to cyber-attacks. DLP can also be used to remove unwanted data that could compromise the security of the system. Data leakage prevention solutions are often used to prioritize and classify data security. These are the common features of DLP: Monitoring: Provides greater visibility into who and where is accessing the system’s data. Filtering: Data is filtered to limit suspicious or unidentified activity. Reporting: Recording and maintaining reports is possible. Analyse: Identifying weaknesses and suspicious behavior and providing context to security teams. These aspects can be used to prevent data loss and manage it efficiently. How does DLP work DLP consists of two main technical approaches to working on the network. Contextual analysis: The DLP technique is used to format metadata and properties of the document, such as headers, sizes, references, etc. Content awareness: This is the process that determines whether sensitive information is in a document. The whole document is read and analysed. Modern DLP solutions combine both to provide better cyber security outcomes. This is used to examine the data context and if it is not sufficient or does not meet the needs, then content awareness can be used to explore the data. Multiple techniques can be used to trigger content analysis. * Ruler-based/Regular expression: This is the most common technique for data loss prevention. It involves the analysis and interpretation of documents. The rules and regular expressions that will be used to analyze the content. If you are looking for credit card numbers or social security numbers, this is an example. This technique acts as a filter, and configures and processes results. It can be combined with other techniques to achieve the desired result. * Database Fingerprinting: Also known by exact data matching. This creates a fingerprint of the data and searches for exact matches in the database dump or with any current running database. * Exact file matching. It creates a hash from the entire file/document, and searches for the file that matches the fingerprint or hash. This technique is extremely accurate, but cannot be used on files with multiple versions. * Partial document matching: Searches for a partial or complete match on files with multiple versions of forms filled out by different users. * Conceptual/Lexicon – Combining lexical rules, taxonomies, and dictionaries, the DLP solution can identify concepts containing sensitive information in unstructured data. * Statistical Analysis: Machine learning algorithms can be used to analyze data. The algorithm will address sensitive data or data that violates policies. * Pre-built categories: Includes rules and dictionaries for sensitive information, such as HIPAA protection or PCI protection. These pre-built devices will not be used. Data loss prevention can be divided into three types. Each type delivers the same results using different methods. Types of DLP Network DLP: Data Loss Prevention in-Network helps to create a secure perimeter around data that is moving. Network DLP is a network that monitors all incoming and outgoing data. It determines whether data should be protected, monitored, blocked, or both. Benefit: DLP can apply to any device connected to the network. Endpoint DLP monitors all endpoints, i.e. Servers, computers, laptops and mobile phones as well as any other device where data is used, saved, moved or stored. USB connectors can be used to connect phones and computers, while pen drives can be used to copy or transfer data. Benefit: DLP software protects data no matter what network it is, whether it’s a company network or a public one. Cloud DLP: This DLP network service provides greater visibility and protection for sensitive information that will be imposed upon SaaS and IaaS clouds services. Cloud data loss prevention network service also includes social security. Data such as emails, financial details, and contacts will be encrypted, with admin access. Benefit: No need for hardware or software. This data loss protection server is more powerful than other DLP solutions. Learn more about cyber-attack prevention protocols. Data Loading: The Advantages
Over 1,000 iOS Apps Found Exposing Hardcoded AWS Credentials Security researchers are raising the alarm about mobile app developers relying on insecure practices that expose Amazon Web Services (AWS) credentials, making the supply chain vulnerable. Malicious actors could take advantage of this to access private databases, leading to data breaches and the exposure of customers’ personal data. Scale of the problem Researchers at Symantec’s Threat Hunting team, part of Broadcom Software, found 1,859 applications containing hard-coded AWS credentials, most of them being iOS apps and just 37 for Android. Also Read: Battling Cyber Threats in 4 Simple Ways Roughly 77% of those applications contained valid AWS access tokens that could be used for direct access to private cloud services. Additionally, 874 applications contained valid AWS tokens that hackers can use for accessing cloud instances containing live-service databases that hold millions of records. These databases typically contain user account details, logs, internal communication, registration information, and other sensitive data, depending on the type of the app. The threat analysts highlight three notable cases in their report where the exposed AWS tokens could have had catastrophic consequences for both authors and users of the vulnerable apps. One example is a business-to-business (B2B) company providing intranet and communication services to over 15,000 medium-to-large companies. The software development kit (SDK) the company provided to clients to access its services contains AWS keys, exposing all private customer data stored on the platform. Another case is a third-party digital identity and authentication SDK used by several banking apps on iOS that included valid cloud credentials. Due to this, all authentication data from all customers of those banks, including names, dates of birth, and even biometric digital fingerprint scans, were exposed in the cloud. Finally, Symantec found a sports betting technology platform used by 16 online gambling apps, that exposed its entire infrastructure and cloud services with admin-level read/write permissions. Why is this happening? The issue with hard-coded and “forgotten” cloud service credentials is basically a supply chain problem, as the negligence of an SDK developer can impact an entire collection of apps and services that rely on it. Mobile app development relies on ready-made components instead of creating everything from scratch, so if the app publishers don’t run a thorough check on the SDKs or libraries they use, a security risk is likely to propagate into their project. As for developers hard-coding the credentials in their products, this is a matter of convenience during the development and testing process and skipping proper code review for security issues. Referring to reasons why this is happening, Symantec highlights the following possibilities: - Downloading or uploading assets and resources required for the app, usually large media files, recordings, or images - Accessing configuration files for the app and/or registering the device and collecting device information and storing it in the cloud - Accessing cloud services that require authentication, such as translation services - No specific reason, dead code, and/or used for testing and never removed Failing to remove these credentials when the software is ready to be deployed by clients is a matter of carelessness and the result of the absence of a checklist-based release process that includes security, too.
To help ensure the security of Kubernetes, OWASP has published the Kubernetes Top 10. The list contains the top ten risks that need to be considered when using Kubernetes. Kubernetes is the preferred platform for cloud application development and deployment. It enables organizations to build, manage, and operate competitive services with a single platform. As its popularity increases, so does the risk of security vulnerabilities. To help ensure the security of Kubernetes, OWASP has published the Kubernetes Top 10. The list includes the top ten risks that need to be considered when using Kubernetes. The risks range from vulnerabilities in the container image to unsecured API calls to insecure configurations and lack of security policies. Kubernetes users should use this list as a reference to understand what risks they need to avoid to protect their applications. These include using secure container images, setting strict access policies, using encrypted connections and regularly reviewing security configurations. Kubernetes is a powerful platform that offers many benefits to developers and organizations. Adhering to the OWASP Kubernetes Top 10 can ensure that applications remain secure while taking advantage of Kubernetes. Insecure Workload Configurations is a vulnerability in the Kubernetes container orchestration system categorized as CWE-836 (Improper restriction of operations within the bounds of a memory buffer). This vulnerability occurs when a user or application can access and modify the configuration of a workload without proper authorization. This could result in malicious actors gaining access to sensitive data or making unauthorized changes to the system. In addition, this vulnerability can be exploited to gain access to the underlying infrastructure, such as the host operating system or other services running on the same system. Reference: Supply chain vulnerabilities are a type of IT vulnerability that can occur when a malicious actor is able to gain access to a system through a third-party vendor or supplier. This type of vulnerability is particularly relevant in the context of Kubernetes, as it is a platform commonly used to manage and deploy applications. According to the Common Weakness Enumeration (CWE) directory, supply chain vulnerabilities are classified as CWE-502, which is defined as "the use of components with known vulnerabilities." In addition, the OWASP Testing Guide recommends that organizations "ensure that all components used in the system are from trusted sources and are updated regularly." Overly permissive RBAC configurations are a vulnerability in Kubernetes, identified as CWE-732: Incorrectly Assigning Permissions to Critical Resources. This vulnerability occurs when an administrator assigns overly permissive roles and permissions to a user or group, allowing them to access resources they should not have access to. This can lead to unauthorized access to sensitive data or the modification or deletion of critical resources. Lack of centralized policy enforcement is a vulnerability in Kubernetes known as CWE-732: Incorrect Permission Assignment for Critical Resources. This vulnerability occurs when the Kubernetes cluster does not have a centralized policy enforcement system to ensure that all nodes in the cluster follow the same security policies. This can result in nodes having different security policies, which can lead to unauthorized access to sensitive data or resources. According to the OWASP test guide, this vulnerability can be identified by examining the cluster's security policies and ensuring that all nodes follow the same policies. Inadequate logging and monitoring is a vulnerability in Kubernetes classified as CWE-778. This vulnerability occurs when Kubernetes does not have adequate logging and monitoring capabilities. This can lead to a lack of visibility into the system, which in turn can lead to security issues. In addition, this vulnerability can lead to a lack of accountability and the inability to detect malicious activity. According to the OWASP test guide, insufficient logging and monitoring can lead to a lack of visibility into the system, which in turn can lead to security issues. Broken Authentication Mechanisms is a vulnerability in the Kubernetes system that allows attackers to gain access to the system by bypassing authentication mechanisms. This vulnerability is classified as CWE-287, which is defined as "Authentication Bypass Through User-Controlled Key" in the Common Weakness Enumeration (CWE) directory. According to the OWASP Testing Guide, this vulnerability is caused by the lack of proper authentication mechanisms such as passwords, tokens, or other authentication methods. Missing network segmentation controls is a vulnerability in Kubernetes that can lead to unauthorized access to the system. This vulnerability is classified as CWE-732, which is defined as "Insufficient network message volume controls". It occurs when the system does not have adequate network segmentation controls, allowing attackers to gain unauthorized access to the system. This can lead to data loss, system compromise, and other malicious activities. (CWE Directory, 2020) According to the OWASP Testing Guide, this vulnerability can be identified by testing for the presence of network segmentation controls such as firewalls, access control lists, and other network security measures. Secrets Management Failures in Kubernetes is a security vulnerability that occurs when secrets such as passwords, tokens, and certificates are not properly managed. This can lead to the secrets being exposed to unauthorized users, resulting in a data breach. This vulnerability is classified as CWE-798: Use of hardcoded credentials. It is also listed in the OWASP Testing Guide as a high risk vulnerability. Misconfigured cluster components can have a significant impact on the security of a Kubernetes cluster. If not fixed, attackers can gain unauthorized access to the cluster, spy on sensitive data, and launch denial-of-service attacks. This can lead to loss of data, disruption of services, and financial losses. Outdated and vulnerable Kubernetes components are a vulnerability in the Kubernetes container orchestration system. This vulnerability is classified as CWE-400: Uncontrolled Resource Exhaustion. It occurs when Kubernetes components are not updated to the latest version, making them more vulnerable to attacks. This can lead to a denial-of-service attack, where malicious actors can consume resources and crash the system. In addition, outdated components can also be exploited to gain access to the system, allowing attackers to gain control of the system and its data. The OWASP Kubernetes Top 10 project is an important tool for improving the security of Kubernetes clusters. It identifies the top ten security risks that can occur when using Kubernetes clusters. These risks include insecure configuration, insecure credential storage, insecure use of APIs, insecure use of containers, insecure use of networks, insecure use of Kubernetes objects, insecure use of Kubernetes roles, insecure use of Kubernetes clusters, insecure use of Kubernetes services, and insecure use of Kubernetes applications. By eliminating these risks, through, for example, the guidance of the Kubernetes Security Cheat Sheet, organizations can ensure that their Kubernetes clusters are secure and reliable.
Activating packet rules Activating the packet rules that you create is the final step in configuring packet rules. You must activate or load the rules that you created in order for them to work. However, before you activate your rules, you should verify that they are correct. Always try to resolve any problems before activating your packet rules. If you activate the rules that have errors or that are ordered incorrectly, your system will be at risk. Your system has a verify function that is automatically invoked any time you activate your rules. Because this automatic feature only checks for major syntactical errors, you should not rely solely on it. Make sure to always manually check for the errors in your rules files as well. When filter rules are not applied to an interface (for example, you are only using NAT rules, not filtering rules), a warning (TCP5AFC) appears. This is not an error. It only verifies whether using one interface is your intention. Always look at the last message. If it says the activation is successful, the messages above it are all warnings. After your packet rules have been configured and activated, you might need to periodically manage them to ensure the security of your system. For instructions on how to activate your packet rules, use the Packet Rules Editor online help. Packet rules can also be activated by using the Load/Unload IP Filter (LODIPFTR) CL command. The LODIPFTR command is used to load or unload Internet Protocol (IP) filter rules.
List Archive: gentoo-security Note: Due to technical difficulties, the Archives are currently not up to date. provides an alternative service for most mailing lists.c.f. bug 424647 On Monday 08 November 2004 07:47 am, Peter Simons wrote: > Since most of you seem to be believe that the bug is really > not that serious, I am certain this will worry you not in > the least. I assume that you intend to 'blow the whistle' because you are incapable or unwilling to submit a patch for the issue yourself? I agree that there is a lot of room for improvement in the portage security system. Signed ebuilds are a good start, but without ways to verify those signatures from a second source (presumably a different portage mirror), signed ebuilds don't buy much security. I wouldn't waste your time hypothesizing about a man in the middle attack. While MOTM attacks are theoretically possible on many many protocols, they are not a serious threat, because of the scale on which they must be undertaken, and the general care taken to keep core routers secure. Small scale MOTM attacks (like from a disgruntled employee) are certainly more feasible, and more common, but still require a fair degree of sophisication. Such an attacker for a small-scale MOTM attack probably has the sophistication to undertake a different, easier exploit. Others have already pointed out that Gentoo is a community based distribution. We help each other. Picking fights with volunteers has probably taken about as much time as it would have taken you to look at the python code and at least propose a code design for a patch, even if you can't code it [email protected] mailing list
Most criminals aren’t bold enough to attempt breaking into a property in broad daylight. However, what sunlight can’t accomplish, locks, alarms, and surveillance systems typically can. These measures may be enough to protect your physical assets, but what about those assets that exist only in the digital realm? Cybercrime is a 24-hour a day, 365-days-a-year threat that doesn’t wait for closing time to rear its ugly head. Hackers are always scheming to break into your systems and get away with your sensitive financial data. They don’t even need to be sitting at a keyboard to do it, either — automated bots and passive email scams can do the work for them any time of the day or night. Cybercriminals can exploit your weaknesses in several ways, whether through a tiny crack in your system’s security or by tricking an employee into unknowingly giving up his or her credentials. Protecting yourself and your clients requires a vigilant solution, one that is constantly scanning for threats and adapting in an instant to nullify them. Fortunately, there is an answer to this dilemma. Systems enhanced with artificial intelligence can provide the protection you need to protect your business, your customers, and your reputation. How Artificial Intelligence Enhances Your Information Security What makes AI such a powerful protector is its ability to adapt and learn from experience. This machine learning enables it to be more vigilant against potential breaches than even people. For example, one of the most common vectors that thieves use to crack IT security systems is phishing schemes. By sending emails that appear at first glance to be official, criminals can surreptitiously install malware onto your servers or fool employees into giving away their login information voluntarily. With AI keeping watch over your network, advanced algorithms can catch and flag these Trojan horses before they reach your staff’s inboxes. AI’s ability to identify patterns and abnormalities also proves useful when monitoring user requests. If an attempt to access sensitive information appears to be suspicious in any way, the system can shut down or limit that individual immediately, preventing any breaches until the request can be verified as legitimate. Even if there isn’t anything unusual going on, AI programs can work to probe your cybersecurity and find any weaknesses. This means you can be alerted to a potential flaw in your armor before a malicious actor has an opportunity to use it. Criminals who stalk the virtual realm don’t need the cover of darkness to ply their trade. They don’t even need to be in the same time zone. Safeguarding your most valuable data means having protection that never needs to sleep, eat, or go on vacation. Software armed with artificial intelligence could be the ideal solution to this persistent problem because it never stops working to keep you safe. To learn more about the threats you face and how these applications can deflect or defeat them, take a look at the accompanying resource. Courtesy of Donnelley Financial Solutions.
This is very similar to Gendarmerie Nationale (French) in the sense that the bad files are practically located in the same directories. For this one, look in these directories: - %userprofile%\local settings\temp\<random 10 letter folder> - For example: Mlqjqjqjq Note: The .exe in each folder listed is exactly the same in terms of MD5 hash, but the actual Name of the randomized .exe is different (both are randomized). First step is remove the Windows lockout portion of this infection. Boot off a diagnostic CD/DVD such as Hiren, or slave the hard drive to another PC with a bootable Windows OS. Having seen this type of infection before, I just went into the suspected folders above and deleted the two bad .exe files from there. Once this is done, you should be able to boot to the Windows desktop again. If you'd like to use some type of scanning tool and know how to analyze the log, I'd recommend Farbar Recovery Scan Tool (FRST). \|Back in Windows\| Great, we are back to the Windows desktop! Wait... why are all my files encrypted?! Similar to ACCDFISA, this type of ransom trojan has two main features. 1) Lock you out of Windows (See Figure 1.a above) 2) Encrypts the majority of your files Do not fret, the expert personnel at Kaspersky have created a tool called RannohDecryptor designed to decrypt and restore your files with ease! \|Kaspersky RannohDecryptor in action\|
\|Warning, many anti-virus scanner have detected cypher File Extension Ransomware as threat to your computer\| \|cypher File Extension Ransomware is flagged by these Anti Ransomware Scanner\| \|Anti Virus Software\|\|Version\|\|Detection\| \|MalwarePatrol\|\|3.4.343817\|\|Ransomware.Win64.cypher File Extension Ransomware.BB\| \|CrowdStrike Falcon (ML)\|\|2.114632\|\|Variant of Win32/Ransomware.cypher File Extension Ransomware.C\| \|Suggestion: Remove cypher File Extension Ransomware Instantly – Free Download\| cypher File Extension Ransomware infects vaultcli.dll 6.1.7600.16385, msadcer.dll 2.81.1117.0, mqmigplugin.dll 6.0.6001.18000, AppIdPolicyEngineApi.dll 6.1.7600.16385, qedit.dll 6.4.2600.1106, tcpmonui.dll 5.1.2600.0, softpub.dll 5.131.2600.0, CORPerfMonExt.dll 2.0.50727.312, corpol.dll 7.0.6001.18000, NlsLexicons0046.dll 6.0.6000.20867, upnpui.dll 5.1.2600.2180, INETRES.dll 6.0.6001.22621 Do ransom note message appear from cypher File Extension Ransomware virus? Ransomware belongs to these cypher File Extension Ransomware family – YouAreFucked Ransomware, Serpico Ransomware, .ttt File Extension Ransomware, Kaenlupuf Ransomware, Nuke Ransomware, Ecovector Ransomware, ProposalCrypt Ransomware, RSA 4096 Ransomware, Alcatraz Ransomware Does cypher File Extension Ransomware targets all files saved in hard drive? Windows Error caused by cypher File Extension Ransomware are – 0x0000004F, 0x8024401A WU_E_PT_HTTP_STATUS_BAD_METHOD Same as HTTP status 405 – the HTTP method is not allowed., 0x00000025, 0x8024401F WU_E_PT_HTTP_STATUS_SERVER_ERROR Same as HTTP status 500 – an error internal to the server prevented fulfilling the request., 0x00000079, 0x0000006B, 0x8024C002 WU_E_DRV_NOPROP_OR_LEGACY A property for the driver could not be found. It may not conform with required specifications., 0x000000A7 Solution To Delete cypher File Extension Ransomware Automatically from OS Click to download cypher File Extension Ransomware Scanner and follow the steps to install it on OS to detect cypher File Extension Ransomware Step 1 Select the language step 2 After that, you need to select and click on Install and scan option. There is also an option for custom installation in OS. Step 3 This will initiate installation process on OS. This will take some time. Once installed, click on the icon to view dasboard of cypher File Extension Ransomware Scanner. You need to select scan now options Once scanning is completed, all the malware including cypher File Extension Ransomware will be listed on OS After completion of the scan, cypher File Extension Ransomware will be detected and you need to Delete cypher File Extension Ransomware If you are finding any difficulties in Removal cypher File Extension Ransomware, kindly chat with experts using Customer Support Service. You can also find setting option for automatic options for Delete cypher File Extension Ransomware from OS Method 1 : Solution To Restart OS in Safe Mode to Delete cypher File Extension Ransomware Assistance For Windows XP/Vista/7 - Step 1- Press “Start” menu and then click “Restart” button. - Step 2- After this Keep pressing “F8 button” until your OS start booting. - Step 3- Now you will see “Advance boot menu” on your OS screens that you have to select . - Step 4- At the very end Select “Safe Mode With Networking” Option then press Enter button at last . Assistance For Restart Windows 8/10 in Safe Mode with Networking to Delete cypher File Extension Ransomware - Step 1-Firstly you open “Start” menu,after which press the “Shift key” and click on the “Restart” button. - Step 2-Next is to click on the”Troubleshoot”option as shown in the below image - Step 3- Select the “Advanced” Options similarly as shown in the image. - Step 4- Carefully select the “Startup Settings” option. - Step 5- Now you have to choose “Enable Safe Mode option” and then click Restart button. Step 6- At the very last press “F5 button” to Open “Safe Mode With Networking” option. Method 2 : Solution To End cypher File Extension Ransomware Related Process From Task Manager - Step 1-At first you have to Press “ALT+Ctrl+Del” buttons all together on your keyboard. - Step 2-Next is to Select Windows Task manager as shown option from screen. - Step 3- Select this last Step to end the malicious process shown in task manager and click on End Task button to kill cypher File Extension Ransomware Method 3 : Proven Solution To Delete cypher File Extension Ransomware using Control Panel Assistance For Windows XP - Step 1- you have to Go the Start menu on your OS and then select Control Panel. - Step 2- then simply Click on Add or Remove programs option as shown. - Step 3- At last go to Find and Delete cypher File Extension Ransomware from your OS as shown below. Assistance For Windows 7 - Step 1- Click the “Windows key” on your keyboard. - Step 2-Select Control Panel Option from start menu. - Step 3-Select Uninstall a programs option from the Programs menu to Uninstall cypher File Extension Ransomware. - Step 4-Finally select and Delete cypher File Extension Ransomware from your OS. Assistance For Delete cypher File Extension Ransomware from Windows 8 - Step 1- for this you have to Press Win+R button to open Run Box on your OS. - Step 2- then in run command Type “control panel” in Run window and press Enter button to open Control Panel. - Step 3- now you have to Click to Delete cypher File Extension Ransomware - Step 4- now the last Step is to just Right-click after selecting cypher File Extension Ransomware and other unwanted programs and click Delete option to Take Down cypher File Extension Ransomware Assistance For Delete cypher File Extension Ransomware on Windows 10 - Step 1-At first press the start button now go to select Settings option. - Step 2-carefully Choose OS option as shown in the fig. - Step 3-choose the shown Apps and Features option from the options. - Step 4-now look for cypher File Extension Ransomware in your OS and Take Down cypher File Extension Ransomware ASAP. Method 4 : Solution To Delete cypher File Extension Ransomware from Browser cypher File Extension Ransomware Removal From Chrome 57.0.2987 - Step 1- the First thing you have to do is run Chrome 57.0.2987 browser in your OS. - Step 2- Click on customize and Chrome 57.0.2987 control button icon from top right corner of your browser to open Chrome menu. - Step 3- on opened panel look for the more Tools option. - Step 4- you have to open Extension and select all unwanted extension including cypher File Extension Ransomware to Delete it. - Step 5- At last make sure to trash out cypher File Extension Ransomware from Chrome 57.0.2987 by Finally clicking on trash bin icon to Take Down it permanently . Removal From IE 10:10.0.9200.16384 - Step 1 – First open the IE 10:10.0.9200.16384 and Press Alt+T buttons, or Click on Gear Icon from the right-top corner to open Tools menu . - Step 2- Now look Manage Add-ons option then click it. - Step 3 – You have to Select Toolbars and Extensions tab. Listed as shown in the fig - Step 4- Delete all those cypher File Extension Ransomware related add-ons by Clicking on the Add-on the virus will be Disabled. - Step 5- The last Step is to Click More information button to see any leftovers. - Step 6- By clicking on Delete button to Take Down cypher File Extension Ransomware. Solution To Delete cypher File Extension Ransomware from Mozilla Firefox:45.0.1 - Step 1- you have to open Mozilla Firefox:45.0.1 browser in your OS. - Step 2 – Click on customize Mozilla Firefox:45.0.1 browser icon from top right corner of your browser to open Mozilla setting menu , - Step 3- Now look carefully to Add-ons of your desire this will open Add-ons Manager tab. - Step 4- Once the Add-ons Manager tab opened, you can now choose the Extensions or Appearance panel. - Step 5- Here you will see cypher File Extension Ransomware add-on that you want to remove so select it . - Step 6- Click the Delete button on the right side shown in the fig . - Step 7- if you find pops up appearing again on screen click to Restart system this will clear cypher File Extension Ransomware from browser . Solution To Delete cypher File Extension Ransomware in Microsoft Edge In order to Delete the cypher File Extension Ransomware from Microsoft Edge browser you will need to reset your browser home page. Since Microsoft Edge does not have extensions features . For doing so you need to follow these easy Steps : - Step 1- At First you have to open Microsoft Edge browser in your OS. - Step 2- there you have to carefully look for More (…) icon from top right corner which will leads to Settings as shown - Step 3- In this third Step select A particular page or pages from under the Open option as shown in the fig . - Step 4- At last you have to Select Custom option and enter the URL of the page that you like to set as homepage. Method 5 : Solution To manually Delete cypher File Extension Ransomware From Registry Editor - Step 1- For this you have to first Open Run in window by pressing Win + R keys altogether. - Step 2- once opened you have to Type “regedit” and then click OK. Method 6 : Reset Browser : Alternate method to Reset and Delete cypher File Extension Ransomware from your browser Reset Chrome 57.0.2987 to Delete cypher File Extension Ransomware - Step 1- The first thing is to lauch “Chrome 57.0.2987”, click on Chrome menu at the right corner . - Step 2- now you have to click on the “Settings” option from drop down list. - Step 3- select the search box and type RESET in it . - Step 4- And at last you have to click on “Reset” button to Delete cypher File Extension Ransomware. Solution To Reset Mozilla Firefox:45.0.1 of cypher File Extension Ransomware to its default settings - Step 1- first of all launch “Mozilla Firefox:45.0.1”, then click on Firefox menu and then press on Help option. - Step 2- you will have to Select “Troubleshooting Information” option. - Step 4- Now quickly Click on “Refresh Firefox” button from top of page.as shown in the fig - Step 4- when you have clicked the “Refresh Firefox” button dialog box would appear on your computer screen showing that your browser have been reset now . 100% working method to reset Microsoft Edge to block cypher File Extension Ransomware - Step 1- first of all Open your MS Edge browser, now click click on More (…) icon, and select Settings option. - Step 2- you will Now click on view advanced settings option to see more options. - Step 3- Type from keyboard option from “Search in the address bar with” optionto search the files . - Step 4- now you can Enter your favorite search engine url and press Add as default use it as a homepage . Solution To Reset IE 10:10.0.9200.16384 to Delete cypher File Extension Ransomware - Step 1- in order to reset , first you have to Open your IE 10:10.0.9200.16384 browser, and then click on “Tools” menu and further select “Internet Option”. - Step 2- go to choose “Advance tab” and then press the “Reset” button. - Step 3- now you have to Find “Delete Personal Settings” option and afterwards press “Reset” Button. - Step 4- In this last Step you have to click on “Close” Button and then restart your browser now you see a reset browser.
In order to safeguard their reputation or the data of their clients, businesses and organizations must increasingly rely on email authentication. DMARC, or Domain-based Message Authentication, Reporting, and Conformance, is one of the best email authentication techniques. In this post, we’ll define DMARC, discuss its benefits, and walk you through setting it up in three simple steps. What is DMARC? For companies and organizations to safeguard their reputation and improve email security, DMARC is an essential tool. It was created as a response to the increasing number of phishing and email spoofing attacks, which can harm a company’s reputation and cause financial loss. Phishing is a type of cyberattack in which the perpetrator sends an email that appears to be from a reliable source, like a bank or a government agency, in an effort to trick the recipient into disclosing sensitive information, like passwords or credit card numbers. Email spoofing is a similar attack where the attacker sends an email that appears to be from someone else, in an attempt to trick the recipient into taking some action, such as clicking on a malicious link or downloading a malicious attachment. Without DMARC, email recipients couldn’t determine the reliability of an email. This makes it easy for phishing and email spoofing attacks to succeed, as the recipient may believe that the email is from a trustworthy source. This issue is resolved by DMARC, which gives domain owners a way to specify in their DNS records which mechanisms—such as SPF and DKIM—are used to authenticate email messages sent from their domain. This enables email recipients to check the email’s authenticity and reject any messages that don’t pass authentication. SPF (Sender Policy Framework) is an email authentication method that allows a domain owner to specify which mail servers are authorized to send email on their behalf. SPF works by creating a TXT record in the DNS that lists the IP addresses of the servers that are authorized to send email from the domain. After receiving an email, the recipient checks the SPF record to see if the server is listed as an authorized server. If the server is not listed, the email is rejected as a potential phishing or email spoofing attack. DKIM (Domain-Keys Identified Mail) is another email authentication method that uses encryption to sign email messages. Email recipients can use this to confirm that the message came from a trusted server. Before accepting an email, the recipient checks the DKIM signature to see if it was created using a private key associated with the domain. If the signature is valid, the email is considered to be authentic and is accepted. If the signature is not valid, the email is rejected as a potential phishing or email spoofing attack. Domain owners can give email recipients the knowledge they need to verify an email’s authenticity and safeguard their domain from unauthorized use by specifying in their DMARC policy which mechanisms, such as SPF and DKIM, are used to authenticate email messages sent from their domain. How to Set Up DMARC in 3 Easy Steps Setting up DMARC is a straightforward process that can be completed in three easy steps. Here’s what you need to do: Step 1: Verify Your Domain Ownership. The first step in setting up DMARC is to verify your domain’s ownership. This can typically be done through your domain registrar or hosting provider. You’ll need to prove that you are the owner of the domain that you want to protect. Step 2: Configure SPF and DKIM. The next step is to configure SPF and DKIM for your domain. SPF (Sender Policy Framework) is an email authentication method that allows a domain owner to specify which mail servers are authorized to send email on their behalf. Another email authentication method is DKIM (Domain-Keys Identified Mail), which uses encryption to sign email messages and enables recipients to confirm that the message was sent by a trusted server. To configure SPF, you’ll need to create a TXT record in your DNS that lists the IP addresses of the servers that are authorized to send email from your domain. To configure DKIM, you’ll need to create a DKIM public key in your DNS, which can be done using a DKIM key generator. Step 3: Publish Your DMARC Policy The final step is to publish your DMARC policy in your DNS. Your DMARC policy specifies how email receivers should handle messages that fail SPF and/or DKIM authentication. To publish your DMARC policy, you’ll need to create a DMARC record in your DNS. The DMARC record is a TXT record that contains information about your SPF and DKIM configurations, as well as your policy for how email receivers should handle messages that fail authentication. Why Use DMARC? There are several reasons why you should use DMARC: - Protect your reputation: By implementing DMARC, you can prevent your domain from being used for phishing and other malicious email activities, which can damage your reputation. - Reduce the risk of email fraud: DMARC helps to prevent email fraud by providing a way for email receivers to identify and reject messages that fail authentication. - Improve email deliverability: DMARC can improve your email deliverability by allowing you to more effectively manage your email sending reputation. - Enhance email security: DMARC provides a more secure email infrastructure by allowing you to authenticate your email messages and identify any unauthorized use of your domain. In conclusion, DMARC is an essential tool for businesses and organizations that want to protect their reputation, reduce the risk of email fraud, and improve email deliverability. By verifying your domain ownership, configuring SPF and DKIM, and publishing your DMARC policy, you can implement DMARC in just three easy steps. It’s important to remember that DMARC is just one aspect of email security. To ensure complete protection, you should also use encryption and secure passwords, educate your employees about the dangers of phishing and email fraud, and monitor your email system for any suspicious activity. Don’t wait until it’s too late to implement DMARC. Start taking control of your email security today and protecting your domain from unauthorized use. With DMARC, you can be confident that your email messages are being securely transmitted and that your reputation is being protected. Book a free demo!
Scaleability Panel Review INSTITUTE FOR DEFENSE ANALYSES ALEXANDRIA VA Pagination or Media Count: A peer review panel was held at IDA on August 19 and 20, 1993, to address the challenges of network scaleability as it pertains to the Synthetic Theater of War STOW program. The goal of STOW is to conduct a Distributed Interactive Simulation DIS demonstration in 1994 with 10,000 entities live, virtual, and constructive, with 100,000 entities by 1997, over the DSI network. Scaleability addresses techniques for maximizing the number of DIS entities on the network by minimizing the network load, both in terms of bandwidth and packets per second. The panel, which consisted of five network scaleability experts, was presented with the current research being conducted by three separate contractors. The experts provided insights on how STOWs goals could be met. They expressed concern over meeting the requirement for a secure network, given the current network encryption requirements. They recommended T3 circuits as a backbone to handle the network traffic. - Computer Systems
The device id ensures that the mobile account is being accessed from the device that was used to create the account. I stop you right there. This does not, and cannot work, at least with stock hardware. From the server, you may receive a message claiming to originate from a device with a specific ID, but this in no way proves that the said device was really involved in the operation. The fundamental reason for this is that the potential attacker can know, by definition, everything that is not secret, and basic hardware contains no secret -- especially hardware that the attacker has access to. The username and password do not authenticate the device or the application; they authenticate the user. If the user is the potential attacker, then this name and password won't stop him in any way: he knows them, there again by definition. The same goes for a private key embedded in the application code: the attacker can extract it through rather simple reverse engineering, and therefore such a signature proves nothing at all. To have some real device authentication, you need heavy artillery, including some tamper-resistant hardware elements that you will not find, or be able to use, in existing smartphones. All of the above is for the security model where the user is the attacker. In that model, the user wants to access your server, but not from "your" app; instead, the user wants to use his own special client code, which allows him to do some operations that are formally forbidden. This is the security model of most online games: the "attacker" is a game player who wishes to obtain some advantage through a modified client application, for instance by displaying the positions of the other players, known to the client application in order to maintain the game dynamics, but normally not displayed. See the Wikipedia page for some other examples. The bottom-line is that this security model cannot be maintained in the long run, although some mitigation measures can be applied to keep the nuisance to a low level, at least as long as what is at stake does not have a great value. You might want to use another security model where the user is not the attacker, but a potential victim, and you want to protect the user data, his requests to your server and the responses, from malicious alterations from the outside. In that model, SSL is sufficient. That's what SSL was designed for, and it works. A signature from a private key hardcoded in the application code brings no extra safety: since every instance of the app contains the private key, it must be assumed that the attacker already has it. Assuming that the attacker can break through the SSL, then it is easy for him to recompute the signature on the altered data. Fortunately, breaking through the SSL is far from trivial. One way to state it is that a private key which is copied into thousands of application instances, on thousands of mobile phones, cannot be really private. But once it is public, it no longer has any value; a private key is worth only as much as it is private. Then there is a third security model in which the attacker is again the user, but with a distinct goal. Instead of trying to run a modified application (e.g. an application which follows the protocol but leaks some extra information), he tries to send fake, altered requests to the server. In that model, a signature can be useful, if you force the attacker to sign every request. With the user name and password, your server already knows which user it is talking to. A signature on the request (and not a session key, as occurs e.g. in SSL with certificate-based client authentication) can potentially be turned into a convincing proof that could be shown to a judge, if things go legal. For this to work, you must not use one shared private key, but one key per user. It also requires that you can demonstrate that your server could never have obtained a copy of the private key of a user; otherwise, there is no proof. This is a complex issue, and note that I used the word "potentially": legal matters depend on the jurisdiction and cannot be reduced to simple technical tools. Summary: SSL, when used correctly, protects data in transit against alterations and eavesdropping by outsiders. An extra signature with a shared private key does not bring any additional benefit. To protect against a modified client, and/or to authenticate the client device (as opposed to the human user), a signature with a shared private key does not help either. For that, you would need some extra client-side hardware. It may be possible to change the context by trying to make the user responsible for what he sends, but for this, again, a signature with a shared private key won't work.
MISRA C is a set of software development guidelines for the C programming language developed by the Motor Industry Software Reliability Association (MISRA). Its aims are to facilitate code safety, security, portability and reliability in the context of embedded systems. You can use Ocular to examine the software elements and flows in your MISRA C applications to identify complex business logic vulnerabilities that can't be scanned for automatically. This tutorial illustrates the capabilities of Ocular to check your code base for MISRA violations, through the use of the rules 17.6 and 22.422.4 of the MISRA 2012 standard. Rule 17.6 states that the declaration of an array parameter should not contain the static keyword between the . This rule covers the possibility of developers assuming a fixed number of parameters provided to a function. Developers do so to increase performance, but with the risk that a function is called without the correct amount of parameters. Rule 22.4 determines that in MISRA C, there should be no attempt to write to a stream which has been opened as read-only. Writing to a file that is only opened to read causes undefined behavior and thus should be avoided.
Much of the delay in transport networks is caused by incidents. Many indicators are developed to determine vulnerable parts of a network without simulating the network flows with an incident on each of the links. This paper lists indicators proposed in literature and cross compares them. Their values for all links on three networks of different sizes are computed. Among others, the order and the cross correlation of the indicators is compared. For one network the effects are also fully computed, running one simulation per blocked link. Different vulnerability indicators rank the links differently. None of the indicators produces a result similar to the full computation. We conclude that the listed indicators are complementary.
Much of the intrusion detection research focuses on signature (misuse) detection, where models are built to recognize known attacks. However, signature detection, by its nature, cannot detect novel attacks. Anomaly detection focuses on modeling the normal behavior and identifying significant deviations, which could be novel attacks. In this paper we explore two machine learning methods that can construct anomaly detection models from past behavior. The first method is a rule learning algorithm that characterizes normal behavior in the absence of labeled attack data. The second method uses a clustering algorithm to identify outliers. Chan, P.K., Mahoney, M.V., Arshad, M.H. (2003). A machine learning approach to anomaly detection (CS-2003-06). Melbourne, FL. Florida Institute of Technology.
Crash analysis also known as explicit analysis uses a completely different solution method to the other analysis methods we employ. It is based on the speed of sound through the material and the iterations are time dependent on the size of the elements used in the model. This introduces differences in the mesh creation between explicit and normal (implicit) analysis models. We use the explicit method for any analysis that requires significant plastic deformation and for material failure investigations. Using explicit analysis we can model car and rail vehicle crash scenarios as well as explosions situations such as mine blast on a military vehicle. We use the Altair HyperWorks CAE software for all our analysis work.
Sanitisation is the process of filtering out potentially malicious code from user input. The process usually involves removing HTML code that can be executed either on the server or other users' browsers. HTML elements like <u> are harmless. But a Lastly, there is a group of HTML elements that makes requests to external resources. Examples are <iframe>. An attacker can utilise the src attribute of these tags to make requests when the element is loaded.
ThunderX Ransomware Description The ThunderX Ransomware is a file-locker Trojan without ties to any famous families or Ransomware-as-a-Services. The ThunderX Ransomware can block the user's files with its encryption, delete local Windows backups, and create additional files related to the ransoming service. Users with other backups are immune to this extortion attempt virtually, and anti-malware programs can block or remove the ThunderX Ransomware from infected PCs. Thunder Coming from a Mysterious Source Between the many families of file-locking Trojans, individual equivalents are no less hostile to users' files. Although one might look at the ThunderX Ransomware and mistake it for a Dharma Ransomware member or a Hidden Tear remix, it's an independent threat. This new entry into the threat landscape targets business entities' networks with the long-standardized encryption plan and extortion. The ThunderX Ransomware is compatible with modern versions of Windows, and malware experts see no samples dating earlier than late August of 2020. The Trojan encrypts media files on infected systems for blocking them, appends pseudo-extensions to their names (a generic '_locked' string), and creates a ransom note and ID file in the same folders. The encryption's security is unknown and may or may not be vulnerable to third-party decryption for recovering data. The ThunderX Ransomware identifies itself in its ransom note and addresses the victim, assuming that the target is a network. Otherwise, it's very similar to a Ransomware-as-a-Service and includes a free demonstration of the unlocking service. It has no details on its ransom, which might be a ploy for bargaining leverage on the threat actor's part. Sheltering Files from the Worst of Weather Users should beware of depending too much on the Restore Points and local backups for their defenses. The ThunderX Ransomware, like nearly every other file-locking Trojan, will make an effort to delete the Shadow Volume Copies that the Restore Points require for recovery. Offsite backups on cloud services, NAS, and detachable devices are far preferable. Due to its current demographics, malware researchers recommend that Windows users watch most carefully over the infection techniques that tend towards business entities, government offices, and NGOs. E-mail is one often-abused method, with attackers hiding their Trojan-installing exploits inside of attached documents like invoices. Brute-force or dictionary attacks are other possibilities. Administrators should monitor passwords for possible vulnerabilities and be prompt about updating the software associated with their servers. Far more anti-malware utilities than not will delete the ThunderX Ransomware, which has no certificates or any significant code-obfuscating properties. This removal method is preferable for most circumstances, and such tools being powerful for stopping drive-by-download attacks. There's room for smaller threat actors, too, just as any ecosystem includes insects alongside mammalian and reptilian predators. The ThunderX Ransomware is proof positive of it, and another notice that a backup is priceless. Use SpyHunter to Detect and Remove PC Threats If you are concerned that malware or PC threats similar to ThunderX Ransomware may have infected your computer, we recommend you start an in-depth system scan with SpyHunter. SpyHunter is an advanced malware protection and remediation application that offers subscribers a comprehensive method for protecting PCs from malware, in addition to providing one-on-one technical support service. Why can't I open any program including SpyHunter? You may have a malware file running in memory that kills any programs that you try to launch on your PC. Tip: Download SpyHunter from a clean computer, copy it to a USB thumb drive, DVD or CD, then install it on the infected PC and run SpyHunter's malware scanner.
Researchers observed a new Powershell based backdoor via Microsoft office document that infects similar to MuddyWater threat actor hacking tools to steal victims sensitive data and share it via C&C server to the attacker. MuddyWater is a widely known cyber crime group and they active since 2017 and performs various PowerShell script attacks on private and government entities. also it launches the same attack on other countries like Turkey, Pakistan, and Tajikistan in March 2018. Newly discovered Powershell based backdoor contains many similar activities same as Muddywater previous campaign and it distributed via weaponized Word documents named Raport.doc or Gizli Raport.doc. These malicious documents have been uploaded from Turkey in virustotal and it drops backdoor which is written in PowerShell as MuddyWater’s known POWERSTATS backdoor. Also in a new method of attack, Attackers using API of a cloud file hosting provider for Command & Control communication and share the stolen data or provide compromised system access to the attacker. PowerShell-based Backdoor Infection Process A malicious attachment sending via mail looks like a phishing document along with the logo that indicates the Turkish government organizations that help attackers to disguise users into believing the documents are legitimate. Initially, it notifies users as it is an old version and enables the macro to update the new version of the document where the point infection process starts. This macro’s using base52 which is rarely used by the sophisticated threat actors which are used to encode their backdoor. Later a .dll file & a .reg file dropped into %temp% directory once the users enabled the macros. “C:\Windows\System32\cmd.exe” /k %windir%\System32\reg.exe IMPORT %temp%\B.reg After researchers analyse the PowerShell code, they conclude that it was highly obfusticated and contains encrypted code with variables named using English curse words. Initially, the backdoor collects the various sensitive information including OS name, domain name, user name, IP address, and more which is similar that previously Muddywater used to collect. According to Trend Micro research, difference between this and older Muddywater backdoors is that C&C communication is done by dropping files to the cloud provider. When we analyzed further, we saw that the communication methods use files named (hard disk serial number)> with various extensions depending on the purpose of the file . This backdoor activity seems that it mainly targeting the Turkish government organizations related to the finance and energy sectors also if it belongs to Muddywater threat actor group then there is a chance to improve its functionality in future.
Whois Privacy Protection, at times also called Privacy or Whois Privacy Protection, is a service that conceals the real contact info of domain name owners on WHOIS check websites. Without such protection, the name, postal address and email account of any domain owner will be openly accessible. Giving false details during the domain registration procedure or changing the authentic details later will simply not work, as doing such a thing may result in the domain registrant losing their ownership rights. The policies adopted by the Internet Corporation for Assigned Names and Numbers (ICANN), require that the WHOIS information must be correct and accurate all the time. The Whois Privacy Protection service was introduced by domain registrars as an answer to the rising concerns about possible identity theft. If the service is enabled, the domain name registrar’s contact information will be listed instead of the domain registrant’s upon a WHOIS check. Most domains support the Whois Privacy Protection service, even though there are certain country-code extensions that don’t.
Loading in 2 Seconds... Loading in 2 Seconds... Update from ICANN staff on SSR Activities Greg Rattray Tuesday 21 st 2010. As ICANN initiated work with the community on the new gTLD program, the community raised concerns regarding the potential for increased malicious conduct within the new gTLD space. Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. Update from ICANN staff on SSR Activities Greg Rattray Tuesday 21st 2010 As ICANN initiated work with the community on the new gTLD program, the community raised concerns regarding the potential for increased malicious conduct within the new gTLD space. • ICANN initiated malicious conduct study in March 2009 as one of four overarching issues • Malicious conduct study included participation from various sources: • Anti Phishing community and APWG members • Registry Internet Safety Group (RISG) • Security and Stability Advisory Committee (SSAC) • Computer Emergency Response Teams (CERT) • Banking and finance industries • Internet security experts • ICANN concluded and published initial study in October 2009; posted with DAG 3 materials Malicious Conduct & New gTLD Program Study provided nine recommendations related to new gTLD program • Vet registry operators – in DAG • Demonstrate plan for DNSSEC deployment – in DAG • Prohibit wildcarding – Board resolution; in DAG • Remove orphan glue records – in DAG • Require thick WHOIS – in DAG • Document registry level abuse contacts and procedures – in DAG • Expedited registry security request process – in place • Centralize zone-file access – advisory group formed; recommendations provided – seeking community comment; potential implementation • Create a framework for high security zone verification – advisory group underway; technical framework developed;awaiting recommendation • Not new gTLD specific Malicious Conduct Results Recommendation overview • Establish a single point of contact for TLD abuse complaints • Registries provide a description of their policies designed to combat abuse. • Fundamental step in allowing successful efforts to combat malicious conduct Current status • Requirement for all new gTLDs per the latest Registry Agreement Recommendation – Document Registry Level Abuse Contacts and Procedures Recommendation overview • Make registry zone file data available through centralized source • Allows for more accurate and rapid identification of key points of contact • Reduces the time necessary to take corrective action Current status • Zone File Access Advisory Group (“ZFA AG”) created • Created proposal for mechanism to support centralization of access to zone files • ZFA AG completed work on strategy proposal on 12 May 2010 http://www.icann.org/en/topics/new-gtlds/zfa-strategy-paper-12may10-en.pdf • ICANN staff currently planning implementation for recommendations Recommendation – Centralize Zone-File Access Recommendation overview • Create a voluntary program designed to designate TLDs wishing to establish and prove an enhanced level of security and trust • Provides a certification mechanism for TLDs that desire to distinguish themselves as secure and trusted • May benefit certain TLD business models Current status • ICANN formed High Security Zone Top Level Domain Advisory Group (“HSTLD AG) • HSTLD AG to propose an approach to a voluntary HSTLD program • Program operated by a 3rd party • Latest progress on the HSDTLD program available here: • http://www.icann.org/en/topics/new-gtlds/hstld-program-en.htm Recommendation – Draft Framework for High Security Zone Verification Update memo published May 2010 • Located at www.icann.org/en/topics/new-gtlds/mitigating-malicious-conduct-memo-update-28may10-en.pdf • Measures will contribute significantly to security and combating the conduct of malicious conduct within the • Seek to support advisory group efforts outlined on ZFA strategy paper and HSTLD advisory group • ZFA: www.icann.org/en/topics/new-gtlds/zfa-strategy-paper-12may10-en.pdf • HSTLD: www.icann.org/en/topics/new-gtlds/hstld-program-snapshot-2-16jun10-en.pdf All posted as part of the DAG 4 explanatory memos Way Forward DNS CERT Operational Requirements Workshop - April • Posting of Documents • Summary of Comments; Workshop report; List of Consults • Exchange of Letters with ccNSO/GSNO/ALAC • Call for and preparation steps for working group • Discussion within OARC of two-tier model for organization/foundation for DNS security and supporting DNS-CERT Strategic Security Initiatives/DNS CERT: State of Play Topic worth discussing • Need deeper understanding of threats & risks • Understand current response capabilities • Does this overlap with current CSIRT capabilities? • Focus on strengthening CSIRT capabilities • Limited response capabilities in less-resourced regions Strategic Security Initiatives/DNS CERT: Main Themes From formal summary • Work on threat and risk understanding • Continue to work with FIRST/CISRTs; initiate survey with CERT/CC on National CERT perspectives • Recognize desire ICANN not operate; focus on working with others and facilitating dialogue • Discuss workshop and Conficker reports • Support community dialogues on DNS-CERT requirements, organizational and resources Strategic Security Initiatives/DNS CERT: Way Forward DNS Risk Assessment • Security Strategic Initiatives paper suggested ICANN conduct a gap analysis and system-wide DNS Risk Assessment as well as contingency planning and exercising • Risks on the “write” side • Contingency planning & response on response side • Interest in the community for such an assessment, leveraging previous work from ENISA, IT Sector Baseline Risk Assessment, SSAC, others • Seeking dialogue with community on next steps
Today, industrial Internet of Things systems and wireless sensor networks are becoming more widespread. Such systems are used to monitor people, environments, technical devices and other physical objects. The major threat for such monitoring systems is functioning in an unreliable environment, assuming the presence of malicious attacking activity. These threats could lead to a compromise of the system as a whole, its devices and services [1 ]. The system compromise may result in catastrophic consequences, such as disruption of the system functioning, distortion of the collected data or significant delays in their transmission. These impacts can disrupt the processes of notifying the system operator about failures and security incidents, which can lead to hazardous effects. In the context of water treatment systems, the impacts on water level sensors can cause flooding of the reservoir or its shallowing, resulting in violations of the water supply processes involving end consumers. Therefore, there is a need to develop effective models and techniques to identify malicious actions on sensors and the system as a whole. Rapid detection of security incidents will allow an operator to respond to them in a timely manner and avoid or at least minimize negative consequences. Generally, the work presents an approach for attack and anomaly detection that utilizes both machine learning and visualization techniques. Along with the classical machine learning analysis models, it is proposed to use a metric that characterizes the changes in the system for visual exploration of system parameters. This solution also supports validation of the constructed machine learning classifiers by means of the visual analysis and exploration of the system parameters as well as the system state to check the effectiveness of these analysis models. Such ongoing validation allows signaling the need to reconfigure the functioning classifiers due to the possible and expected natural evolution of the target system. The proposed detection mechanisms could be used in real-time and near-real-time modes, thus allowing the generation of alerts of security incidents with acceptable detection quality for a given time period. Thus, the novelty of the proposed approach consists of the combination of the machine learning and visualization techniques that are used in conjunction to monitor both the system state and efficiency of the analysis models. The developed visualization serves as an express assessment of the system state. It could be made to obtain more detailed manual and/or machine-assisted assessments of the system. In addition, the applied visualization contributes to the reconfiguration and improvement of the machine learning classifiers, allowing one to take into account even relatively small changes in the behavior of the target system. Due to the limitations of the available equipment, a specific test bed for the water treatment system was developed. It was built on the principles of the full-scale and simulation modeling of the analyzed industrial process. The full-scale model was developed using Arduino microcontrollers, physical sensors and actuators, including sensors of water level, pressure and water flow, as well as electric valves and a water pump. It is enriched by a set of simulation rules that generate vectors of sensor readings and the state of actuators based on some numerical features of the implemented full-scale model. Combining the full-scale and simulation models made it possible to generate data sets that characterize the normal behavior of the system and several classes of attacks on its sensors. In addition, one should note that, on the physical implementation, we calculated a few important parameters of the modeled processes (including measurements of the time of emptying/filling of tanks and the rate of change of sensor readings). Then, we used the values of these parameters straightforwardly within the software simulator, which more fully describes the analyzed water treatment processes. This explains why both the full-scale model and the software simulator were really needed. Note that the developed machine learning and visualization models were built using the data collected from the developed test bed. Thus, the contributions of the paper consist of An approach combining machine learning and visualization models to monitor the state of a water treatment system; An application of the metric that characterizes the measure of system change to monitor and analyze the state of the system visually; A water treatment test bed that is developed on the principles of the full-scale and simulation modeling of the technological process. The rest of the article is organized as follows. Section 2 represents the state-of-the-art. Section 3 discusses the whole visualization-assisted approach to anomaly and attack detection, while Section 3 details the visualization-driven explanation and analysis component. Section 4 presents a case study and the developed test bed. Section 5 contains the experimental study and discussion, while Section 6 concludes the article. 2. Related Works Currently, the security of the Internet of Things systems and wireless sensor networks has been the subject of a series of works. Some of them deal with aspects related to attacks on the routing protocol. For example, Rehman et al. suggested several ways to detect Sinkhole attacks, i.e., sophisticated routing effects [2 ]. In contrast to existing ones, the specificity of this article is that it concerns elements of attack detection by identifying correlations between sensor readings without considering direct malicious actions on the network protocol level and/or other physical and software parts. The issues of ensuring and assessing the security of Internet of Things systems, robotic complexes and wireless sensor networks, including studies of the impact on device sensors, are becoming increasingly relevant [1 ]. By influencing the system by exploiting one or a few sensors, as the point of the application, the attacker is able to compromise a sensor and devices integrated with it or located near it. In addition, the attacker can interfere with the data transmitted, processed and stored on the network devices and the information services provided. An attack on a sensor can be an element of a complex influence that can lead to various short-term or fatal disruptions in the functioning of the entire system and cause its inoperability. One of the ways to increase the security of such systems is the timely detection of malicious influences and obtaining additional information on them, including the class and source of the attack. In most of the analyzed literature sources, the detection of attacks and anomalies in Internet of Things systems is performed using various intelligent data analysis methods [1 ]. At the same time, the extraction of specific features, the construction of feature spaces, and the appointment of certain learning models, for the most part, are determined by the specific formulation of the problem and its limitations. In particular, the availability or absence of satellite communications in the network determine the short-term loss of connection accompanying this type of connection, especially due to the continuous movement of satellites in the orbit and the possible movement of ground devices of the network [5 ]. Depending on the structure and composition of the system, such losses should be separated from targeted actions of the attacker, for example, ones aimed at noising the GPS channel. Wang et al. [3 ] proposed a way to detect attacks on sensors in a wireless sensor network by introducing a virtual sensor and using a sensor’s fault model to establish inconsistencies between the readings of this sensor and other ones to be considered as attacks. Shin et al. analyzed data from sensors of intelligent vehicle models to detect anomalies by using deep learning methods [1 ]. It is based on quantitative measurements of the readings of eight physical sensors of the car model, and the difference in the values of the sensor readings from the expected values is estimated. In the study, six particular classes of attacks and normal data are used. Each of them represents an attack on one or two of the available sensors. The conducted experiments made it possible to compute the indicators of accuracy and correctness, as well as to determines the training methods that grant the best outcome. ], by using the example of unmanned ground vehicles, some attacks on sensors are detected in conditions of possible transient faults. To distinguish between attacks and transient faults, a static model of the faults (faulty model) is built for each sensor, including the interval of its allowable values and the maximum allowable frequency of its faults. The attacks are detected on the basis of these models by pairwise comparisons of the readings of various sensors. In the process of machine learning, the most appropriate fault model is selected from the available models. Currently, a fairly large number of studies are being conducted on digital water metering and related directions, including issues of water consumption, long medium and short-term prediction of such consumption, resource planning, explanation of user behavior, characteristics of water consumption and detection of leaks by using machine learning and data analysis methods [6 Racity et al. proposed a mechanism for monitoring water quality, including checking for contamination and other characteristics of water [7 ]. At the same time, a particular requirement is established to achieve a high quality of detection in conditions of possible inaccuracies and the absence of some feature’s values. Based on the application of water clustering methods, Raciti et al. built a mechanism for detecting pollution with certain values of the detection quality. ], the correlation between the properties of pollution of terrestrial natural water bodies and geographic characteristics of the location, such as latitude, longitude and height, is considered. In that work, a number of polluting factors (contaminating factors, e.g., water temperature, turbidity, acidity, the presence of oxygen in water, chlorides, etc.) are identified, and they are used to predict specific pollution based on physical parameters. The data analysis is performed using machine learning methods, namely four regression models. A peculiarity of this work is the manual collection and physical and chemical analysis of water to obtain a set of data on the pollution characteristics in various areas of the region under consideration, followed by the use of particular methods of data mining. Artificial intelligence methods are also used to determine the quality of water. In particular, Naloufi et al. proposed a method for predicting the concentration of Escherichia coli bacteria in water bodies without involving complex specific laboratory procedures, which are time-consuming and technically complex and would require higher financial costs [9 ]. Specifically, Naloufi et al. were able to build a machine learning model that, based on 10 simple physical, chemical and weather characteristics that can be easily measured, generates concentration predictions for a given bacterial species by using basic machine learning methods such as SVM, KNN, DT and others. In addition, the authors note the possibility of automating monitoring and elucidating water pollution using wireless sensor networks, such as LPWAN, which allow nodes to operate autonomously for a long time without replenishing energy resources. An anomaly detection process may significantly benefit from the application of the visualization techniques as they allow presenting data in clear and easily perceived form. Numerous research papers are devoted to the design of the visualization techniques applicable to the anomaly detection problem [10 ]. For example, Shi et al. [12 ] reviewed 150 papers and outlined four main application domains for visualization-driven detection of abnormal entity behavior: network communication, social interactions, financial transactions, and travel data. In [13 ], the authors studied different visualization techniques designed specifically for revealing anomalous activity in the network traffic. However, there are only a few works in the field of visualization-assisted anomaly detection in data from physical sensors. This fact could be explained by the fact that all technological processes are formalized, and any deviation from the predefined process could be detected on the basis of a set of established rules, and the exception is constituted by the problem of equipment failure forecasting, where different machine learning and visualization-driven approaches have been proposed [14 Commercial SCADA systems [15 ] and commercial solutions for anomaly detection in industrial IoT systems [17 ] mostly utilize standard visualization techniques such as timelines, gauges or mnemonic object diagrams for graphical representation and analysis of system parameters. The problem arises when analyzing and monitoring the system behavior where an analyst or operator needs to review tens of parameters, and the application of advanced visualization techniques could increase the efficiency of their work. Only a few visual analytics solutions aimed to assist in the monitoring of complex object behavior and anomaly detection are suggested. Janetzko et al. [18 ] explored the capabilities of pixel based techniques with different layouts and line charts to detect patterns and anomalies in energy consumption. In [19 ], the authors adopted matrix-based and RadViz visualizations to analyze anomalies in heating, ventilation and conditioning data. ], the authors applied another multidimensional data projection technique, namely multidimensional scaling, to analyze streaming data from multiple sensors. To be able to apply it, the authors evaluated the pairwise similarity in data streams from sensors and used it to map sensors on the plane. Such projection allowed the authors to represent sensors’ functioning as a trajectory of points on the plane, and anomalies in their behavior could be detected as anomalies in their trajectories. ], the authors proposed an interactive visual analytics system for equipment line monitoring that supports not only smart parameter monitoring but also machine learning model inspection and updates. The latter is achieved by evaluating the characteristics of the training set and current data. To visualize streams of sensor data, the authors use either line charts with the time axis or pixel-based visualization to cope with large volumes of data. Let us note the main peculiarities that distinguish this work from the analyzed existing results in the field: Focus on the subject area of water treatment. In particular, when defining the classes of attacks, the authors considered the nature of the viscosity and fluidity of water, which determines some inertia and often a gradual change in the accumulation and transfer of water, and as a result, sensor readings in the generated time sequences. Building and configuring a set of classifiers as attack and anomaly detection tools based on machine learning methods specific to the problem being solved and the list of critical attacks generated. Application of the visual models as means of visual exploration of the system parameters, and monitoring of the system state. The peculiarity of this component lies in the computation and visualization of the metric that characterizes the changes in the system at some given moment of time. Combination of the proposed visual analysis and machine learning methods, and presentation of the visual-based express evaluation of the system to make decisions on more detailed manual and/or machine-assisted checking of the system state, firstly, and visual validation of the constructed machine learning classifiers by means of visual analysis and exploration of the system parameters as well as the system state to check the effectiveness of these classifiers, secondly. 3. Visualization-Assisted Approach to Anomaly and Attack Detection The suggested approach to anomaly and attack detection in the water treatment system consists of the two key connected components: The scheme of the proposed approach is presented in Figure 1 The attack detection component consists of n binary classifiers that are trained to detect n different classes of the attacks, and one generalized multi-class classifier targeted to detect one of the n specific attacks. The current implementation of the component detects five different classes of the attacks but could be extended to detect novel ones. The following seven supervised machine learning methods were selected as possible candidates for detecting each class of attack and serving as basis for a generalized multi-class classifier: AdaBoostClassifier, RandomForestClassifier, Bayesian classifier, LogisticRegression, Linear SVM classifier, Decision Trees, and RidgeClassifier. A series of experiments on the test data sets made it possible to determine the most effective machine learning model as well as its parameters. The efficiency assessment was conducted using two quality metrics: accuracy and f1-score. Section 5 discusses the experiment settings as well their results in detail. The visualization component supports the visual exploration of the system parameters and monitoring of the system state. The distinctive feature of this component is the calculation and visualization of the metric that characterizes the number of changes in the system at the given moment of time. This metric was firstly introduced in [10 ] and considers a set of selected attributes that are used to evaluate how the system state changes over time. The calculation of the integral metric is presented in Section 3 in detail. To visualize the values of this metric, the line plot with time axis is used. The selected visualization model is simple but intuitively clear to the operator. It provides a natural perception of the situation and allows unambiguous identification of changes in the system that could correspond to the anomalies or attacks in the system behavior. Visualization-Driven Explanation and Analysis Component When designing the visualization of data streams from sensors, the authors kept in mind following challenges identified in [22 Necessity to combine streaming data from diverse sources to support analysis; Support for understanding changes that could be expressed in many forms, starting from changes in parameters’ values between previous and current ones and finishing with deviations in system behavior as a whole; Dynamic nature of data, which are constantly changing and evolving in time. ], the authors suggested representing a state of the system that is defined by a set of sensors as a point in a multidimensional space, and then the functioning of this system could be considered as a trajectory in this space. Such representation allows addressing the first challenge relating to the necessity to combine streaming data from multiple sources. Moreover, in [19 ], it was shown that mapping a system’s trajectory in multidimensional space to the plane enables revealing system behavior patterns as well as anomalies. Different states of the system are characterized by different graphical patterns that vary in point density and scatter. In [23 ], the authors evaluated different metrics that could be used to assess the similarity of the points distribution on the plane in order to detect structural similarity, and they showed that Delaunay triangulation could be used to detect typical patterns as well as outliers when evaluating projections produced by data reduction techniques. Anomalous bursts in the system’s parameters result in larger values of the total square of the triangles obtained by Delaunay triangulation, while smaller values of the total triangles’ square correspond to smoother changes in the system’s behavior. The latter enabled the authors to define a novel metric that characterizes the amount of system change and use it as an integral metric to monitor the state of the system [10 metric is a core metric of the developed visualization system, and its usage addresses the second challenge identified in [22 ], enabling an analysis of changes in the whole system as well as changes between previous and current parameters’ values. The metric is calculated for some given moment of time t and considers n subsequent data points in multidimensional space. The algorithm for calculation metric is given in Algorithm 1. \|Algorithm 1: Integral metric calculation\| Input: n—size of sliding window for sampling a sequence of points, t—moment of time S—a set of m-dimensional data points ordered in time and equipped with timestamps apply data reduction technique PCA to the normalized set S form a subset by selecting n sequential points from the S set that precedes a point with timestamp t construct a Delaunay triangulation for a set . calculate as a total area of obtained triangles of . Currently, to reduce the data dimension, PCA is chosen as it allows revealing the deviations in a systems’ behavior more clearly than other techniques [23 ]. The size of sliding window n is a customizable parameter and could be changed to enable better anomaly detection. Varying the window size, it is possible to control the impact of previous values on the current one. The values of the form a one-dimensional time series, and for this reason, it is natural to use the timeline to visualize it. To correlate system behavior with the results of the ML-based attack detection component and to highlight the periods when the system is under attack, the authors use a background color for the plot. The white background corresponds to the normal mode of system functioning, while the color background indicates that the ML-based attack detection component has detected an attack. In order to enhance the detection of visual signs of an anomaly in the system operation, the authors also propose performing post-processing of the obtained values of the metric. It is possible to apply sliding mean and median filters with a specified width of the filtering window. It should also be noted that the suggested visualization provides an overview of the system functioning, which is why it has to be supplemented by a set of timelines showing each parameter separately. Figure 2 shows the graphical interface of the visualization component, which consists of two main views: view A is used to represent values of the system parameters, and view B is used to visualize the integral metric . These two views are synchronized, and the operator may select different time intervals to analyze and explore data. They could also choose different parameters to visualize and adjust the graphical properties of the plots. Similarly, the operator could adjust the calculation of the integral score metric by manipulating the sliding window size and applying different filters to smooth the values of 4. Water Treatment Case Study A case study modeling water treatment with the use of some available physical and electronic components was constructed. In addition, we developed a software tool expanding its business logic and simulating the system processes. This combined scheme allowed us to measure sensor readings directly and multiply and scale them by means of the simulator [24 The scheme of the case study used in the work is exposed in Figure 3 . The system contains two tanks. One tank is higher than the other (the top one is labeled as the first one and the bottom one as the second tank). Due to the influence of gravity, the water starts flowing from the first tank into the second one. The gate of the water treatment system imitates a controlled tap (electric crane) installed between the tanks. The tap closes when the second tank is full, and then the pump turns on and pumps the water back into the first tank. It simulates the process of lowering the water level on one side of the crane and rising on the other. To measure the water level in the tanks, water level sensors are installed. Each tank has three water level sensors and one sensor measuring the fullness degree. To measure the amount of water pumped between the tanks, in addition to the tap, a water flow sensor is installed. The hardware of the prototype is expressed by an Arduino UNO controller designed to read sensor readings and Raspberry PI for processing them and organizing functions to monitor the system’s status. The software part includes a Web server built using the Python programming language, Django framework and ngnix libraries. This server is used to monitor the readings of sensors and states of the system actuators by a human operator. It should be noted that the developed prototype is a physically closed system. This is intended to facilitate its continued automatic operation in laboratory conditions and model target water treatment and dam systems closer to their reality. The tanks model water bodies on either side of the gate (shutter). When the gate is opened, the water level decreases on one side and increases on the other (water flow from tank 1 to tank 2). When the valve is closed, the water level decreases on one side (water goes further downstream), and on the other side, it increases (pumping from tank 2 back to 1). The pump was introduced in the model mainly to provide long enough working scenarios of the system. The developed simulator allowed us to generate a large number of possible states, which made it possible to speed up the modeling and testing of a variety of attacks, i.e., it is able to simulate attacks of several classes and form sets of various particular system states. For example, if it is necessary to generate a data set containing several hours of system operation, it is necessary to run the system model for the required time and constantly simulate attacks, and when simulating, this process is automated and takes less time. The constructed simulator works as follows: the initial state of the sensors and actuators of the system is set, then the actions occurring in the system are simulated by changing the readings of some sensors over a certain time (for example, half a second), and the related readings of other ones are adjusted. The simulator based on a short recording of sensor readings makes it possible to introduce small deviations into it, concatenating and mixing with other data, to generate longer logs at the output that simulate the operation of the system, thereby increasing the amount of data suitable for experiments. The formation of mixed data, including data of normal behavior and data about an attack of a certain class, is performed by modeling attack data and superimposing it on records of the normal functioning of the system. After that, these data are written to the output file and meta-information about it is formed. The specific values of the parameters, the time it takes for the tanks to be empty and the readings of specific sensors to change were obtained empirically using a full-scale model. Thus, using the simulation model, it became possible to set any initial state of the system, simulate one of the possible attacks and obtain the required set of system state records within a certain time interval. The simulation algorithm is shown in Figure 4 as an activity diagram. The data set is in the form of *.csv file, which contains records of sensor readings and states of actuators at certain points in time. Each time moment of the system operation corresponds to a row of value records separated by a syntactic separator. Here, the time interval between records is fixed and is equal to half a second. During the simulation, seven data sets both with and without attacks were recorded. The constructed data sets include: data containing only normal states of the system; five sets containing normal states together with attack situations of each class, respectively; a set containing all classes of attacks at once and the normal state of the system. The duration of each data set is 1 h (7200 samples). The number of attacks in each file fills 25 min in total, divided into two attacking blocks (i.e., 12.5 min of attacks in each of the two blocks). That is, after an hour of the system’s operation, the attack was modeled on it twice for 12.5 min each. In the data set containing all five attack classes, the time of each attack is the same and is 10 min. presents the fields of the generated data sets. For example, in the generated data sets, a tuple <1; 1; 1; 1; 99.817; 0.6; 0.534; 0; 0; 0; 0.183; 0; 0.0; 0.5; 0; 0> defines the record of the normal state of the system, wherein the first tank is almost completely full, which is indicated by the water level sensors and the fullness sensor from the first tank. The controlled valve is open to degree 0.6. The water flow rate is 0.534, which corresponds to the percentage of the crane opening. The second tank is almost empty, and the time since the start of the system is half a second. The field that reflects an attack is zero, as well as the classAttack field. The recorded data sets include data on five attacks on this system. Their names, attack class number and description of malicious actions are presented in Table 2 In addition, one more class can be introduced, the absence of any attack. This class is marked by label 0. 5. Experiments and Discussion 5.1. Machine Learning Based Detection To detect attacks, machine learning modules contained in the Scikit-learn library and the Python programming language are used. When performing experiments on attack detection with data sets presenting states of the water treatment system, we used the following machine learning modules taken from the Scikit-learn library: AdaBoost classifier (AdaBoostClassifier class); Random Forest classifier (RandomForestClassifier class); Bayesian classifier (MultinomialNB class); LogisticRegression classifier (LogisticRegression class); Linear classifier SVM (SGDClassifier class); DecisionTree (DecisionTreeClassifier class); Ridge Classifier (RidgeClassifier class). The data sets present records of the state of the water treatment system at a definite point in time, i.e., records of the states of the system’s sensors and its actuators. Each of the samples may contain at least one attack, as described above. The following files were taken as input: 0_1.csv (total – 7200 records; normal – 4200; attack – 3000; attack class 1) 0_2.csv (total – 7200 records; normal – 4200; attack – 3000; attack class – 2) 0_3.csv (total – 7200 records; normal – 4765; attack – 2435; attack class – 3) 0_4.csv (total – 7200 records; normal – 4200; attack – 3000; attack class – 4) 0_5.csv (total – 7200 records; normal – 6649; attack – 551; attack class – 5) 0_1_2_3_4_5.csv (total – 7200 records; normal – 2413; attack – 4787; attack classes– 1, 2, 3, 4, 5) The architecture of the used experimental framework for the classification of attacks is shown in Figure 5 . All the samples of the data sets were divided into training and testing sets at ratios of 70% to 30%, respectively. The testing of the trained models was performed using a testing set, and the calculation of classification quality was fulfilled by accuracy and f1-score indicators. For the training phase, the columns containing record identifiers attack classes and attack indicators were excluded in order to avoid overfitting. The time feature was also eliminated because its strong correlation with the resulting variable was revealed. Therefore, the following features were selected: watLevel_R1_3_bool, watLevel_R1_2_bool, watLevel_R1_1_bool, Fullness_R1_perc, Crane_state_perc, Flow_state_perc, watLevel _R2_3_bool, watLevel_R2_2_bool, watLevel_R2_1_bool, Fullness_R2_perc, Pump _state_bool, PumpFlow_state_perc. During the experiments, the selection of the best hyper-parameters for each of the methods was performed using the GridSearchCV library function. As an input, one needs to set a list of parameters for a specific classifier. After that, according to given indicators, namely accuracy and f1-score, the best combination of parameters for a higher indicator is formed. Table 3 presents a list of parameters of the machine learning methods that were fed to the input of the GridSearchCV function. and Table 5 show appropriate parameters for each method with reference to the input data set. The results of the experiments are shown in Figure 6 . It reflects the quality of attack classification by machine learning methods for each input dataset using the f1-score metric. 5.2. Analysis of the Proposed Visualization Efficiency The goal of the experiments conducted with a visualization component was to determine the most suitable parameters for the calculation of the integral metric , i.e., size of sampling window that defines a number of the points used to construct Delaunay triangulation and enables clear identification of the anomaly. The authors also evaluated the impact of smoothing filters on the visual efficiency to reveal specific classes of attacks. The experimental data consisted of five data sets that are described in Section 5.1 To determine the optimal number of data points that are used to construct Delaunay triangulation, the authors calculated and plotted the metric with the following parameters: Distance between 2 points (parameter ), Triangular area by 3 points (parameter ), Delaunay triangulation by 5 points (parameter ), Delaunay triangulation by 10 points (parameter ). For the test data, the data set with the first class of the attack was used. Figure 7 shows plots of the metric for these four settings, and the background color shows the time intervals with the attack. It is obvious that the plots of the metric based on the calculation of triangular squares produce similar patterns of anomalous activity, while the metric based on the calculation of the Euclidean distance between two points gives a slightly different plot (Figure 7 a). It is possible to see the transition period at the beginning more clearly, and the normal period of functioning is also characterized by periodical bursts in the metric values. In contrast, the plots of the metrics based on the triangles’ area allow an analyst to detect normal and anomalous periods clearly: the periods of attack are characterized by high scatter in values and higher frequency of change, and the metric values for normal periods are almost close to zero and change slightly. As all plots produce similar results, the metric based on the calculation of the triangle square is preferable because it is faster to calculate and does not require the accumulation of data, which may be critical for the online monitoring of the system. In the next series of experiments, the authors used the calculated with n set to 3. The next series of experiments was devoted to the evaluation of the efficiency of the metric to determine different classes of the attack. An attack of the first class is clearly seen on the plot of the metric with different visualization settings. Figure 8 shows these plots, it should be noted that the metric is constructed for the whole set of attributes. The plot of the “raw” metric is characterized by a constant change of the metric values, the sliding filters smooth these changes making the start and stop points of the attack more visible. The attack of the second class was not easy to detect as there were no clearly visible changes in the behaviour of the metric when it was constructed for the whole set of attributes. Thus, it was decided to focus only on the parameters that could be potentially impacted by the attack, i.e., parameters that characterize the volume of the water in the reservoir. This allowed authors to reveal some anomalous spikes in the system’s functioning. Figure 9 shows the plot of the obtained values of the metric. It is clearly seen that there is a sequence of spikes at the beginning of the plot that could indicate that the system is in a transient state, reaching its normal functioning mode, and there are four single outliers. When the authors mapped the time intervals of the attack with this plot, it became clear that these spikes indicate the start and stop points of the attack. These spikes are clearly visible even when no sliding filters are applied. Thus, it could be concluded that the patterns of system behavior in the normal state and under a given attack do not differ, which indicates that in this case, the proposed method determines only the fact of anomaly appearance, but not its effect on the nature of system operation. The anomalies of the third and fifth types can be clearly seen on the linear plots without filtering (Figure 10 a) and with sliding median filtering with a window set to 60 (Figure 10 b). A characteristic feature of these attacks is a significant change in the density of points on the plane that results in the higher values of the on the plot as well as in the absence of periods with a small change in the system state (Figure 10 a). This makes median filtering more effective, enabling highlighting such periods more obviously. As in the previous case with an attack of the second class, there are also bursts at the beginning of the graph, which indicates the transient state of the system when it is reaching the normal operating mode. Such moments should be taken into account when applying this method. The anomaly of the fifth type turned out to be more difficult to determine visually, although it is a combination of attacks of classes three and four. In contrast to the previous cases, during this attack, the state of the system does not change significantly in comparison with the normal operation of the system, and periods with an anomalous operation, on the contrary, are characterized by lower values of the . Thus, the anomaly pattern for this attack consists in the smaller range of the metrics’ values. The implemented visualization-driven approach to anomaly detection was also applied to the data set that contains all types of anomalies. Figure 11 shows the results obtained. The upper plot in Figure 11 shows the class of the attack if the system is under attack or zero if there is no anomaly in the system. The lower plot is the plot of the metric. The anomalies of the first, third and fourth types are clearly seen, and these anomalies are highlighted by a background color in Figure 11 . The visual detection of the anomalies of the second and fifth types is much more complicated. Thus, it is required to apply filtering with a sliding average filter with a window of 60 to reveal the attack of the second class, while the attack of the fifth class was still difficult to determine visually. The possible reason for this failure could be in the artificial origin of the data: the periods with anomalies successively replace each other, and there are almost no periods with normal functioning of the system except for the first one, but it corresponds to the transition period of the system when it reaches the normal operational mode. The analysis of the experimental results with the machine learning models that are given in Figure 6 showed that the performance metrics are very high for some classes of attacks. To avoid overfitting during the experiments, the initial data set was divided into training and testing subsets (with respect to 70/30). This was applied in all series of experiments, including data sets with attacks of the first and second classes. The possible reason for such a high detection rate is the low complexity of these attacks and the high separability of the classes. The latter is proved by good visibility of the periods with attacks when they are visualized using the proposed graphical model. With an increase in the attack complexity as well as their number in the input data set, the performance metrics of machine learning methods slightly decrease but still remain quite high. This proves the efficiency of the proposed solutions. The implemented series of experiments showed that the proposed visualization technique allows constructing the graphical patterns of the anomalous behavior of the water treatment system. These patterns are formed by the metric and characterized either by the values of the change metric or by the change rate of these values. It allows identifying points when the functioning of the system changes, which could be used as a trigger to start manual and/or machine-assisted checking of the system state. Nevertheless, the conducted experiments revealed the limitations of the approach. It was shown that it is required to apply different pre-processing techniques such as median filtering and window size setting in order to reveal different attack scenarios. To solve the first problem, the authors currently recommend implementing the following steps: Visualize the “raw” plot of the metric for the whole set of attributes. Apply filter “sliding average filter” to highlight time periods when the rate of the metric change is higher in comparison to others. Apply filter “sliding median value” to highlight time periods when the values of the metric are higher in comparison to others If no signs of anomaly are detectable, group attributes based on their semantic relationships and perform steps 2–3. The comparative analysis of the proposed approach with the existing ones showed that with regard to visualization, the proposed approach is close to the solutions described in [19 ]. Similarly to [21 ], the authors use a timeline to monitor the system’s behavior and machine learning behavior. However, to construct the line chart, the authors introduce a specific preprocessing of data from multiple sensors that, in some sense, is close to [19 ]. Unlike [20 ], the authors represent the behavior of the whole system by a point in a multidimensional space and then apply the Delaunay triangulation to assess the amount of changes in system behavior at a given moment of time. As the proposed metric incorporates a set of system parameters, the developed visualization is able to form situational awareness of the water treatment system state. The problem of the attack and anomaly detection in cyber-physical systems, such as water treatment systems, electric power stations, etc., is of great practical importance, as malicious activity may result in a significant impact on the environment and human safety. In the general case, attacks on sensors of a wireless sensor network are characterized by the complexity of identifying such attacks and their differences from various software and hardware/software failures. In addition, they are characterized by the complexity and potential ambiguity of interpreting the analyzed data and classifying them as traces of an attack without involving additional data from alternative protection mechanisms. The paper proposes a visualization-assisted approach to anomaly and attack detection in a water treatment system constructed on the basis of a wireless sensor network. The distinctive feature of the proposed approach is a combination of the machine learning and visualization techniques. The former refers to automated attack detection based on supervised learning on the labeled data sets with five attack classes and mixed data. The latter is used to assist in anomaly detection and its explanation and the monitoring of the system state. The authors propose visualizing a metric that characterizes the amount of change in the system state for a given period. As its calculation is based on a set of system parameters, it could be considered as an integral and be used in forming the situation awareness of the analyst. To evaluate the proposed approach, a water treatment test bed was developed. It includes a software/hardware prototype of the system that models water treatment processes both on physical equipment and microcircuits, as well as a software simulator that allows generating a sufficient amount of initial data of the normal functioning of the system and when the system is under attack. In particular, such simulation made it possible to model five classes of attacks on system sensors and combinations of several attacks. The obtained data sets were used to train and test classifiers that implement attack detection and evaluate the efficiency of the visualization component. The conducted experiments showed the high values of the detection quality metrics for the machine learning methods applied. It was also shown that the proposed visualization is able to reveal different anomalous scenarios and determine graphical patterns corresponding to them. It allows detecting points of interest that are considered as a starting point of the manual or machine-assisted “root-cause” analysis of the anomalies. However, the experiments also identified certain limitations in terms of the visualization. They relate to the parameters’ fine-tuning procedure for calculation and visualization of the proposed metric. The enhancement of the metric calculation procedure and elaboration of the recommendations for its application is included in the scope of future works. Another direction of the future work relates to the enhancement of the test bed and extension of the modeled attack scenarios.
What Do These Different Terms & Services Mean? Maybe you are new to the information security space or are looking for some definitions in everyday language that detail the services we are discussing. If so, then the content below is just what you’re looking for. \|Unauthenticated Scan\|\|Authenticated Scan\|\|Authenticated Manual Testing\| \|Basic Vulnerability Checks\| \|Thorough Automated Vulnerability Checks\| \|Business Logic Flaws\| When we discuss application testing, we often talk about testing your application as an authenticated user (working login/password) and as an unauthenticated user. We strongly prefer to perform testing from both perspectives to give you a complete idea of your application’s risk. If we were to only perform unauthenticated testing, this may give your organization a false sense of security as many applications have the majority of their functionality available after the user has authenticated/logged in to the app. Additionally, sometimes functionality that is available to authenticated users can be mimicked or reproduced by an unauthenticated user, meaning that vulnerabilities may be leveraged by both authenticated users of the system (insider threat, etc. ) as well as unauthenticated attackers. Every application has various functions for which they are built. For example, a banking application may allow a user to view their balance, move funds between accounts, open new accounts, request a loan, etc. Testing applications for business logic flaws is the process of seeing if the tester can trick the application into performing actions which fall outside the designed functionality. In the banking application example, testing might involve trying to withdraw or send money from an unauthorized account, create additional users for an account you do not own, view the balance of an account that is not yours, etc. Attackers often try to steal session tokens because if they successfully steal a user’s session tokens, they may be able to impersonate that user. Because HTTP is a stateless protocol, stealing a user’s session tokens is often enough to be able to perform functions as the compromised user. Because session tokens are of such high importance in a web application, protecting them and ensuring the logic surrounding session management is robust is of the utmost importance in your web application. Using the example of a banking application again, there are often several different types of functions available, such as banking client, bank teller, bank manager, IT administrator, etc. Using the most common account type, a banking client, it is very important to ensure that user Bob Smith cannot see John Doe’s banking information. Additionally, it is also important that Bob Smith, a normal banking client, cannot perform the functions of a bank manager, IT administrator, etc. \|Vulnerability Scan\|\|Penetration Test\|\|Red Team Assessment\| \|Physical Security Testing\| A vulnerability assessment is a security test that uses automated tools in order to quickly identify a large range of vulnerabilities. A vulnerability assessment is generally a detective test, meaning that vulnerabilities are detected, but are not exploited. We take the additional step of manually validating findings wherever possible to ensure there are minimal false positives included in the results. A penetration test includes the steps involved in vulnerability testing, but takes things a step further by attempting to exploit vulnerabilities or leverage other weaknesses in a client’s network/application to gain additional access to their environment. In addition to exploiting vulnerabilities, this type of testing may include brute-force testing to identify accounts with weak passwords as well as privilege escalation, which can allow an attacker with an initial foothold on the network/application to gain access to additional information and/or systems. The goal of this testing is often to gain elevated privileges (domain/enterprise administrator) and/or to gain access to sensitive data/systems on a client network/application. These terms can apply across multiple types of engagements, but pivoting is the process of using an initial foothold on a network or application (access to a user’s desktop, for example) to attempt to gain access to additional systems/information. Privilege escalation is the act of attempting to leverage a vulnerability or logic flaw in order to gain access to a user/process that has more privileges than what you started with, allowing you to gain access to more privileged information/access than the initial user/process can access. This type of assessment can be done in a variety of ways and is very much dependent on the outcomes our client is looking for, but is designed to be an adversarial simulation where our engineers perform the types of tests that may happen in the real world. From vulnerability exploitation to breaking into a facility to the use of social engineering and/or malware, this is as close to a no-holds-barred assessment as you can get.
It looks like you are already aware of the 1st part of this question. For most purposes any non-volatile storage which may have held he data you consider sensitive should be included (solid state drives, hard drives, EPROMS, USB keys etc) but volatile memory should not. These storage devices could be in printers, fax machines, routers, switches, any computing platform. A key prerequisite is understanding what you consider sensitive - eg the configuration of a router may need to be protected to avoid weakening network security, or devices storing personal or account data may come under DPA in the UK, or GLB or HIPAA in the US. A general rule of thumb is to look to the organisation's data classification policy as a guide and destroy data storage which comes under data protection requirements. The in-house/outsource question could come down to just how sensitive the data is. I recently sat in an excellent presentation on data destruction in the military, where complete outsource was not an option, and complete destruction was a requirement, so the use of grinders which could take entire hard drives down to dust was approved. For many organisations who use hard disc encryption, a provider who carries out multiple overwrites to the extent that recovery is unfeasible may be sufficient. This will depend on both the level of sensitivity and the type of agent who may be trying to recover the data. If an attacker has an electron scanning microscope, they may be able to retrieve useful data off a hard disc platter which has been broken into pieces - but that is only likely to happen if the data is known to be of extremely high value. Either way, auditable reporting of the destruction is essential - so you can evidence you received all the devices, and destroyed them, along with the destruction mechanism and final disposal details.
Improving Network Security Data gained from intrusion detection can be used to improve network security by preventing future attacks and help determine how to respond to security incidents. IDS add another line of defense behind firewalls and antivirus software. Future attacks can be prevented when IDS provides detection and record logs. Many IDS even go a step beyond transmitting alarms and respond to security incidents. Thus, the correct options are a and d. Route traffic more efficiently is not one of the goals of IDS. Thus, the choice ‘b’ is incorrect. Shield IP addresses on the network can be performed by using proxies, but not by data gained from IDS. Thus, the choice ‘c’ is incorrect.
Here I present some examples of BitTorrent protocol interactions. Wireshark can be used to analyze BitTorrent protocol interactions in TCP/IP. Remember that BitTorrent’s peer protocol operates over TCP or uTP. At the time of writing, Wireshark could identify correctly a uTP connection, but unfortunately would not decode its contents as a BitTorrent protocol session. It decodes it fine for TCP/IP connections. The Handshake message flows in both directions, this means that each peer sends an handshake message to the other. “Extended” message examples In these messages we can see which extensions are supported by a peer / downloader. Port, Interested, Unchoke example A request for a piece of a file: The reply with the piece’s data contents: Not Interested example Downloader Peers screenshots Usually, when a peer is connected to another one, the remote peer appears in the “Peers” tab for a torrent. Most virtualization platforms provide some sort of mechanism of communication between the the hypervisor and its guest virtual machines. “Open VM Tools” is a set of tools that implements such communication mechanisms for VMware™ virtual machines and hypervisors. In this book we analyze each of these these tools and APIs, from high-level usage to low-level communication details, between the guest and the host. This information can be used for a better understating of what actually happens when using a guest machine with these tools. It can also be used as inspiration for using and extending guest-hypervisor communication and penetration testing. Just published a new tool vmhost_report.rb (and a paper about it) for VMware hypervisor fingerprinting. The tool is released with an open source license (GPL), you can use it freely. In the paper, I show you how to determine hypervisor properties (such as hypervisor version or virtual CPU Limits) by running commands in the guest operating system, without any special privileges in the host machine running the hypervisor. This can be useful for penetration testing, information gathering, determining the best software configuration for virtualization-sensitive and virtualization-aware software. I have developed a reporting tool vmhost_report.rb that unifies all the presented methods, by running them all in sequence and gathering the information in a useful report that can be run from any guest system. Currently, Linux and Nested ESXi are supported. You can run it as “ruby vmhost_report.rb“. It will return a lot of useful information in the vmhost_report.log file. These reports can be used to learn a lot about VMware internals or a particular guest system or network. You can find report examples in the Paper’s “Annex A”. Some of the described methods can be used even if the VMware Tools are disabled or not installed, or if some of the methods are disabled by host configuration. Some of the methods require “root” privileges, while others do not need it.
Applications of Artificial Intelligence, technology that adds intelligence to the computer to enable it to perform tasks autonomously, is increasingly inserted in technological innovations. The trend is for exponential growth in its adoption in the coming years with the arrival of 5G and the expansion of edge computing networks — providing the necessary boost for cloud computing to continue evolving. An interesting point about the use of technology is its application in businesses of the most diverse segments. Whether you are working in the Finance sector, running a teaching network, or managing e-commerce, you can take advantage of all the opportunities it offers. Are you curious about how to adopt it in your business? To inspire you, we have listed below five Artificial Intelligence applications impacting the user experience and, of course, the results of companies. Check out! As technology advances and is applied by companies, there is a counterpoint: the evolution of cyber threats. Sophisticated and much more harmful nowadays, attacks like DDoS and Hijacking, always executed in real-time, require monitoring at all times. Combating this type of risk is not something tangible. However, mitigation can (and should) be carried out to curb the cybercriminal’s action or, if the problem has taken on more significant proportions, to mitigate the damage. Therefore, 24/7 monitoring is essential; more than that, it needs to be done with the help of advanced technologies. Using algorithms, artificial intelligence enters the scene to identify suspicious or abnormal behavior. When detection happens, the security team at the ready can react to the event as soon as it manifests itself. Due to the high degree of effectiveness, the tendency is for all software-based security mechanisms to operate using Artificial Intelligence. Supply chain (or supply chain) is an activity aimed at the logistics sector. It consists of managing materials and products, covering the end-to-end process — from manufacturing to delivery of the item to the customer. Examples: acquisition of inputs; Could the above activities not be optimized if you insert Artificial Intelligence and thus automate everything possible and feasible? Companies in the logistics sector not only understand the value of this but are already benefiting from the advantages offered by technology. Imagine a product storage warehouse in a distribution center. Artificial Intelligence can be applied to virtually all elements that contribute to the progress of the process: vehicles, packaging, storage, thermometer, mapping, control, etc. For example, sensors can issue notifications of inappropriate temperatures for a package. With this, an autonomous vehicle follows the best route to reach it, pick it up, and move it from position to the most favorable space. Improving the user experience is a common goal among all companies operating on the web. From the consumer’s point of view, customer service usually defines satisfaction most of the time. Therefore, improving yourself in this regard is an essential attitude to conquer (and retain) customers. So how about applying Artificial Intelligence and ensuring excellent results? In recent years, many companies have adopted, for example, the chatbot. It is a type of robot capable of providing service with intelligence to the point of recognizing customer credentials and data, as well as serving them in a way that is very similar to what a human being does, but with availability 24 hours a day and more. The benefits of using robots to serve customers are not limited to cost reduction but also include taking advantage of the fees of each employee, who is no longer overloaded with activity and is dedicated to the functions that must add value to the business. With the expansion of fintech, which are technology startups focused on finance, Artificial Intelligence was boosted to automate a series of operations relevant to the client and, simultaneously, costly when assigned to a professional. A typical example of this is investment advice provided by a robot. The practice allows the reduction of talent costs, such as agents and investment managers, making room for a mechanism that is available 24 hours a day and performs accurate analyzes based on market facts. Therefore, if you work (or plan to work) in the financial sector, know that Artificial Intelligence can be leveraged in several ways. Although some of them no longer represent a competitive differential, innovations should be considered. Predictive analytics are predictions based on data, information, and trends, among other factors, which allow companies to make more intelligent and more accurate decisions, like the robot agents we mentioned in the previous topic. Artificial Intelligence is also applicable in this sense: as there is a wide range of things that today are done using technological resources, the computers themselves can identify, for example, whether a component of the IT infrastructure requires maintenance or how a particular user is browsing the products on the site. Two types of cases that are well-known in the market are medical diagnoses which, through data analysis, make it possible to predict illnesses and identify the most appropriate solutions. Another scenario is played by on-demand media providers, which collect customer information and, with this, increase the efficiency of recommendations on platforms.
What is Zero Trust? Learn about the benefits of Zero Trust and how to implement a Zero Trust security architecture. In This Article Digital transformation, cloud adoption and remote working have created the perfect storm that breaks the legacy architecture of a perimeter-based security model. Cloud computing has pushed data, users and devices outside of the trusted corporate network. Organizations must respond with the appropriate security measures to eliminate vulnerabilities in this new environment. Zero Trust security is the answer to this challenge. Zero Trust allows access to an organization's network from anywhere without compromising the ability to stay compliant with fast-changing privacy regulations. It's essential in today's work-from-anywhere world. What is Zero Trust? Zero Trust is an IT security framework that provides secure access to applications and services based on defined access control policies, whether a user is inside or outside an organization's network. Besides being authenticated, authorized users must be continuously validated for their security configurations and postures before being granted access to data and applications. Zero Trust is a series of concepts and involves the orchestration of many products across various pillars (e.g., user, data, devices, network, application, automation) to deliver a unified architecture. Because it works for infrastructure with no traditional network edge, you can apply the framework to local networks, the cloud and anything in between. Why is Zero Trust important? Zero Trust focuses on securing a company’s digital assets and preventing a breach. Here are the key benefits of a Zero Trust architecture compared with a legacy security architecture: Reduce attack surface Zero Trust mitigates the risks associated with the increase in attack surface caused by the adoption of cloud computing and remote working. It uses micro-segmentation to define micro-perimeters close to the data source, thereby eliminating the broad lateral movement found in many legacy architectures. Limit access to sensitive data Zero Trust components positively authenticate and authorize users and their devices to reach approved applications and information. This means the least privileged access model grants users access to data on a need-to-know basis. You can make company assets invisible to unauthorized users with the right technical solution. Since threat actors can’t attack what they can’t see, you can minimize the damage of a breach by limiting what can be accessed. Assess risks continuously Unlike legacy architectures, a Zero Trust solution can dynamically assess the security risk of users, devices and services to mitigate risks that may occur post-authentication. It can shut down access if a resource falls below what the organization deems as an acceptable risk level. Implementing Zero Trust security To address today's threat environment, you need to start with a Zero Trust mindset: - Assume all network traffic and requests for critical resources may be malicious. - Assume all infrastructure and devices may be compromised. - Accept that all access approvals to critical resources can incur risks. - Be prepared to perform damage assessment, control and recovery operations. - Implement aggressive system monitoring, system management and defensive operations. Zero Trust comprises various technical attributes that allow organizations to address the highest risk areas efficiently. An effective Zero Trust security framework should offer: - A security-first design: Reduces risks through isolated network virtualization, granular separation of duties and least privileged access. - Automated threat mitigation and remediation: Decreases the complexity of implementing security measures while preventing human errors. - Continuous and always-on security measures: Includes default-enabled and ubiquitous encryption, continuous monitoring of user behaviors, and context-aware adaptive authentication. However, not every organization can instantly replace a legacy security architecture with a fully mature and optimized Zero Trust one. As such, we have laid out a logical path to provide our customers with a blueprint to mature their Zero Trust architecture over time. For example, many companies start with enterprise segmentation in the data center to address lateral movement. Then, they'd evolve the architecture to address the contextual components of Zero Trust. Standards organizations, such as NIST, regularly publish architectural blueprints on how to build out Zero Trust architectures. We are positioned to align closely with these standards and support the practical execution of Zero Trust with short, agile workstreams. Ready to take the next step in Zero Trust security? In our complimentary Zero Trust briefing, we'll explore the capabilities and benefits of a Zero Trust architecture, along with vendor-specific capabilities and innovations. We'll work with your key stakeholders to understand your long-term vision and discuss strategies to secure your environment.
This is a potential security issue, you are being redirected to https://csrc.nist.gov Microservices architecture is increasingly being used to design, develop, and deploy large-scale application systems in both cloud-based and enterprise infrastructures. The resulting application system consists of relatively small, loosely coupled entities called microservices that communicate with each other using lightweight communication protocols. This smaller codebase facilitates faster code development and platform optimization for which network security, reliability, and latency are critical factors. NIST announces the publication of NIST Special Publication (SP) 800-204, Security Strategies for Microservices-based Application Systems, which outlines strategies for the secure deployment of a microservices-based application. The objective is to enhance the security profile of microservices-based applications by analyzing the implementation options for core state-of-practice features as well as the configuration options for architectural frameworks such as API gateway and service mesh. Core features include authentication and access management, service discovery, secure communication protocols, security monitoring, availability/resiliency improvement techniques (e.g., circuit breakers), load balancing and throttling, integrity assurance techniques during induction of new services, and handling of session persistence.
Posted on May 15, 2022 at 12:04 PM Researchers at GoDaddy’s security firm Sucuri have revealed that thousands of websites were hacked over the past few months due to known vulnerabilities. According to the researchers, the threat actors behind the campaign injected malicious scripts into WordPress themes and plugins, taking advantage of known security flaws at the time. The hacking activities are linked to plugins and themes built by thousands of third-party developers that use the open-source WordPress software instead of WordPress.com. WordPress.com’s parent company Automatic is the distributor of the software, but it doesn’t own it. Thousands of Sites Could Be Affected Sucuri noted that there are 322 WordPress sites with themes and plugins that were affected by the hack. However, the real number of other websites impacted by the exploit could be much higher. Last month, threat actors used the method to infiltrate 6,000 sites, according to Krasimir Kon, a malware analyst with Sucuri. This means that there may be more sites impacted since the campaign started months ago. “This page tricks unsuspecting users into subscribing to push notifications from the malicious site,” Konov added. When the users follow the directive by clicking on the CAPTCHA, they’ll automatically be entered into an opt-in list for several unwanted ads. The ads will look like they are coming from the operating system and not from the browser so that they will look authentic from a genuine company. The Hackers Can Run Tech-Support Scams Konov also noted that the opt-in maneuvers for push notifications are one of the ways threat actors can run tech support scams. In most cases, the affected users keep receiving annoying pop-up windows to inform them that their computer is compromised. A number is usually provided for the user to call and receive instructions to fix the problem. This is where they get gullible victims. Once they make the contact, the users may be exploited further. The Federal Trade Commission provided some useful points to help users stay off these types of scams. The commission noted that users should consider such messages as coming from scammers and hackers. It noted that a genuine security firm will not use such an approach to contact a user with an infected system. Real security messages do not ask users to call a certain number to get their issues fixed, the commission stated. WordPress.com stated that themes and plugins are not maintained or written within the core WordPress software. Based on Sucuri’s report, any theme or plugin hosted on the WordPress.org website is usually scanned for flaws. The Vulnerability Is From Third-Party Tools The report also noted that once security issues are discovered, authors of themes and plugins are notified immediately to prevent any more impact. If no response was received from the author or if a theme is not patched on time, it is pulled out of WordPress or completely closed from the portal. WordPress.org also helps by offering tools and resources on security for both plugin developers and theme developers. According to a spokesperson for the company, WordPress users are informed and encouraged to update important software, themes, and plugins, especially for self-hosted sites. WordPress also offers different security services to sites hosted on the WordPress.com platform. These security advisory services enable the company to address vulnerabilities like those referenced in the report. But despite the efforts by the company to keep the platform safe, it still suffers from some security lapses in some cases. The reason is that most of the plugins and themes hosted on the platform are managed independently by third parties. As a result, exploits on WordPress are usually from vulnerable themes or plugins from these third parties.
This is the best place for you if you want to learn from the best people in the penetration testing industry, including web app penetration testing and reverse engineering. In simple terms, reverse engineering means processes aimed at reconstructing a given object to understand how it was made and works. Equipped with that knowledge, one can analyze malware. Thus, training in reverse engineering provides the organization's IT teams with a crucial tool for their daily work, allowing them to secure the solutions they design more effectively and select the proper mechanisms to protect their organization's assets. Our training offer is addressed not only to IT specialists but also to the management and any other employee of the organization who, in the course of carrying out their professional duties, come in contact with IT infrastructure or its components. Each participant in the training receives a certificate to confirm they have gained new competencies in the relevant scope.
What is advanced BGP? Cisco Advanced BGP BGP (Border Gateway Protocol) is the routing protocol of the Internet, used to route traffic from one autonomous system (AS) to another. Unlike IGPs like OSPF or EIGRP, BGP uses a set of attributes to determine the best path for each destination. What is Microsoft BGP? BGP is the standard routing protocol commonly used in the Internet to exchange routing and reachability information between two or more networks. BGP can also enable transit routing among multiple networks by propagating routes a BGP gateway learns from one BGP peer to all other BGP peers. Is BGP A more advanced version of OSPF? BGP is a more advanced version of OSPF. OSPF maintains a database of other routers’ links. What is the purpose of BGP? Border Gateway Protocol (BGP) refers to a gateway protocol that enables the internet to exchange routing information between autonomous systems (AS). As networks interact with each other, they need a way to communicate. What is the full form of BGP? Border Gateway Protocol (BGP) is an Internet Engineering Task Force (IETF) standard, and the most scalable of all routing protocols. BGP is the routing protocol of the global Internet, as well as for Service Provider private networks. What is BGP route hijacking? BGP hijacking is a form of application-layer DDoS attack that allows an attacker to impersonate a network, using a legitimate network prefix as their own. When this “impersonated” information is accepted by other networks, traffic is inadvertently forwarded to the attacker instead of its proper destination. Is BGP a VPN? BGP-based VPNs allow a network operator to offer a VPN service to a VPN customer, delivering isolating connectivity between multiple sites of this customer. If a VRF imports from a Route Target, BGP IP VPN routes will be imported in this VRF. How do you peer to BGP? To configure the BGP peer sessions: - Configure the interfaces to Peers A, B, C, and D. - Set the autonomous system (AS) number. - Create the BGP group, and add the external neighbor addresses. - Specify the autonomous system (AS) number of the external AS. - Add Peer D, and set the AS number at the individual neighbor level. Which is faster OSPF or BGP? Network topology or design: OSPF is a type of hierarchical network topology or design while BGP is a type of mesh topology or design….OSPF vs BGP: What Are the Differences? \|Function\|\|The fastest route is preferred over shortest\|\|Best path is determined for the datagram\| Is OSPF still used? OSPF is the most widely used but it is not the only choice. With that said, it is the most standardized IGP and that allows for optimal vendor interoperability. OSPF is primarily used for internal routing because it’s a link-state routing protocol. What are the features of BGP? The characteristics of BGP follow: - BGP is an exterior gateway protocol (EGP) used in routing in the Internet. - BGP is a path vector routing protocol suited for strategic routing policies. - It uses TCP port 179 to establish connections with neighbors. - BGPv4 implements CIDR. - eBGP is used for external neighbors. Why we use BGP in MPLS? BGP is a protocol used to carry external routing information such as customers’ routing information or the internet routing information. The MPLS tunneling mechanism allows core routers to forward packets using labels only without the need to look up their destinations in IP routing tables. What do I need to know about BGP router? The BGP Router supports displaying the message and route statistics, if required, by using the Get-BgpStatistics Windows PowerShell command. Equal Cost Multi Path Routing (ECMP) support. The BGP Router supports ECMP and can have more than one equal cost routes plumbed into the BGP routing table and stack. Which is the latest version of the BGP protocol? The BGP Router is based on the latest BGP version 4 specification, and has been tested for interoperability with most of the major third party BGP routing devices. For more information, see Request for Comments (RFC) 4271, A Border Gateway Protocol 4 (BGP-4). How does edge use Border Gateway Protocol ( BGP )? The edge device runs BGP with an internal router and learns internal routes (in this case, 10.1.1.0/24) The edge device implements an Interior Gateway Protocol (IGP) and participates directly in internal routing. Each Enterprise site learns the routes from the other site over the direct eBGP connectivity. What kind of BGP is used in autonomous systems? Autonomous systems can also use an internal version of BGP to route through their internal networks, which is known as internal BGP, or iBGP for short. It should be noted that using internal BGP is NOT a requirement for using external BGP.
In unrestricted areas, it’s preferable to use a “blacklist” approach that excludes only those users, code, or machines that are predetermined to be dangerous. Logging only detected security events is generally considered tolerable and useful in this context. In restricted areas, you can add a “whitelist” via which you allow only things based on a list of “known good” users, code, or machines. Regulations may mandate the use of logging for audit purposes in these areas. In a college or university network, the areas that must be strictly controlled should be separate from areas that are expected to operate with little restriction. This separation minimizes the ability of threats or “bad actors” to cause problems by moving from one area to another, raising the level of their access privileges as they go. Beyond this, we can provide users with tools to protect their own personal areas, as well as education about how and when they might wish to apply them. These tools could include things like: How to maintain the balance between security and privacy - Backups: Regular, tested backups should be taken in sensitive areas to limit outages caused by data-damaging malware (like ransomware), hardware failure, and other catastrophes. As basic backup functionality is freely available in all major operating systems, educating students, teachers, and staff about the benefit of taking backups could be a useful tool for decreasing your IT support costs. - Encryption: Encryption helps protect data that’s not in use from being viewed by people who shouldn’t be able to access it. This should be applied both to data on disk and data being sent to or from sensitive areas of your network. Encryption is also freely available in major operating systems, as well as many popular communication apps. You may want to let your users know about these resources so they can help protect themselves. - Authorization lists: Authorization lists assign users permissions for what resources they can access. You should maintain these lists in sensitive areas, and users can also use these to limit access to certain people or groups over time (such as research that should not be publicly available before a certain date). • Multi-factor authentication tools: Many data breaches are caused by or result in lost login credentials. One of the best ways to mitigate the damage is to implement a second factor of authentication (verifying that users are who they say they are). Many online services already make this functionality available, and it’s a cost-effective tool, thanks to the amount of risk-mitigation it offers, to add to other login processes. In general, people aren’t opposed to security, but rather to the loss of personal control it often implies. By understanding the context of the controls, and enabling users to protect their own resources, we can make security measures more palatable.
Microsoft Office Tutorials and References In Depth Information Working with Document Properties in the Info Tab Finding and Linking to Additional Files Another valuable option on the Info tab of Backstage view is found in the Related Documents area. Because few of the documents we create today actually stand alone, knowing where and how to access similar content is important (and can save you a lot of time searching through folders and drives on the server). Both selections in the Related Files area—Open File Location and Edit Links To Files—are live selections, meaning that you can click them to move directly to the task you want to perform. When you click Open File Location, Word 2010 will ask you to confirm that the location you are accessing is a safe one; click Yes to continue, and Word 2010 opens the folder where the current file is stored. Now you can look for additional files, open collateral documents, or do the research you need to do. Perhaps, for example, you want to see what tags have been assigned to other files in your document folder. When you’re finished in the folder, click the Close box to return to the Word 2010 Backstage view. The Edit Links To Files selection enables you to check, modify, and update links to any objects you’ve embedded in your document. If you do not have other objects in your document, this option will not appear. Clicking this selection displays the Links dialog box, as shown in Figure 2-8. Figure 2-8 Use the Edit Links To Files selection on the Info tab to review, change, and update links to objects embedded in your document. To learn more about embedding objects and working with links in Word 2010, see Chapter 18, “Adding the Extras: Equations, Text Boxes, and Objects.” Customizing Document Properties Display The document properties shown by default on the Info tab of Backstage view are the ones most commonly used by the majority of Word users, but your needs or interests might dictate storing more specialized information about the file. You can change the document properties collected and displayed on the Info tab by clicking the Properties arrow (see
In Git, every line of the file .gitignore is a regular expression that describes files that should be ignored. However, one can also add lines that state which files not to ignore. The following example shows a configuration that ignores everything in a particular directory (./tmp) but explicitly states that PDF files in ./tmp should not be ignored: # Ignore everything in ./tmp ... # ... but do not ignore PDF files in ./tmp
Top-Level Domain Names A top-level domain (TLD), also referred to as a "top-level domain name", is the last part of an Internet domain name. Specifically, it is the group of letters that follow the final dot of any domain name. For example, the top-level domain of com (as these are the letters that follow the final dot). Using the example my-domain.co.nz, the top-level domain is nz (again, because these letters follow the final dot). Actually, the dot is usually included when expressing a top-level domain. Therefore, the above example would normally be expressed as Top-level domain names, as recognized by ICANN, fall under the following categories. Generic Top-Level Domains (gTLD) These are the most common domains that most people have heard of, such as .COM, .ORG, .NET, and .INFO. For more information on gTLDs see Generic Top-Level Domains Generic-Restricted Top-Level Domains Generic-restricted top-level domain names are similar to the generic top-level domains, only eligibility is intended to be restricted and ascertained more stringently. Examples are: .BIZ, .NAME, .PRO For more information, see Generic Restricted Top-Level Domains Sponsored Top-Level Domains (sTLD) These domains are proposed and sponsored by private agencies or organizations that establish and enforce rules restricting the eligibility to use the TLD. IANA also groups sTLDs with the generic top-level domains. Examples include: .AERO, .ASIA, .CAT, .COOP, .EDU, .GOV, .INT, .JOBS, .MIL, .MOBI, .MUSEUM, .TEL, .TRAVEL For more information on sTLDs see Sponsored Top-Level Domains Country Code Top-Level Domains (ccTLD) Country code top-level domain names are those that are generally used for a specific country or dependent territory. All ccTLD identifiers are two letters long, and all two-letter top-level domains are ccTLDs. Examples of ccTLDs include: .NZ (for New Zealand), .AU (for Australia), .CN (for China), .IN (for India), .UK (for the United Kingdom), .US (for the United States) For a full list of ccTLDs, see Country Code Top-Level Domains Reserved Top-Level Domains IANA has reserved some top-level domains for a range of purposes including infrastructure, testing, and support of international organizations. For example, internationalized top-level domains have been reserved by IANA for testing internationalized domain names. Examples include: .परीक्षा, .испытание, .آزمایشی, .ARPA, .INT For a list of reserved top-level domains, see Reserved Top-Level Domains Who is Responsible for Top-Level Domains? The assignment of domain names and IP addresses is done by the Internet Corporation for Assigned Names and Numbers (ICANN). ICANN is the international organization for introducing new top-level domains. The technical aspect of ICANN's work is carried out by Internet Assigned Numbers Authority (IANA). IANA is in charge of maintaining the DNS root zone. Complete List of Domain Extensions To view a complete list of top-level domains and other domain extensions, as well an explanation behind each one, see the domain name extension definitions. Registering Your Domain Name You register your domain name through an ICANN-accredited domain name registrar (or partner site) like ZappyHost. To register your domain name, enter your preferred domain into the search form. If it's available, simply proceed to the checkout. ZappyHost will walk you through the registration step by step.
This appendix lists and defines the common acronyms used in this book. ACL access control list. A form of IOS filter designed for packet and route classification and control. AF address family. Types of IP addresses that share the same characteristics, such as IPv4 and IPv6. AFI address family identifier. A value that represents an address family. ARF automatic route filtering. Automatic filtering of routes by matching RTs received versus those configured locally in an MPLS VPN network. ARP Address Resolution Protocol. An IETF protocol to map an IP address to a MAC address. AS autonomous system. A BGP routing domain that shares the AS number. ASBR autonomous system border router. A router that interfaces with other ...
Recently Protus3 was asked to assist someone who had fallen prey to ransomware. The person had clicked on an attachment in an email. It wasn’t too long before the message, shown here, popped up on their screen that the ransomware had encrypted all of the files in their My Documents folder. Remembering a recent news article about the identification of ransomware encryption algorithms, we decided to do some research. The victim sent us one of the encrypted files. We uploaded the encrypted file to: id-ransomware.malwarehunterteam.com We identified the ransomware as the Nemucod variant. With some research we found a site that would assist with decrypting the files. We went to the below site and followed the instructions: www.bleepingcomputer.com/news/security/decryptor-released-for-the-nemucod-trojans-crypted-ransomware We started the computer and downloaded the EMSISOFT Decrypter software from the Bleeping Computer website. Once downloaded, we had to drag and drop both an original file and encrypted file into the EMSISOFT application. We could not find an original file on the computer since the ransomware had encrypted all files on the computer. Instead, we searched the Outlook sent box and found a file sent before the ransomware activated. We copied and pasted the original file from Outlook to the computer’s desktop. Once on the desktop, we selected the two files and dragged them over to the EMSISOFT Decrypter Icon. The EMSISOFT application generated a message box which contained the encryption key. We confirmed the encryption key which then opened the EMSISOFT Decrypter application. Once opened, the application showed the drives attached to the computer, and we selected the decrypt icon. The files started to decrypt which lasted a little over an hour. When finished, we saved a log of the decrypted file that. After that, we downloaded the RKill software and ran a scan on the computer. When the scan finished, the RKill said that no infections were left on the computer. We then downloaded the free version of AVG and ran a virus scan. This came back as clean also. When this finished, we downloaded MalwareBytes and ran a scan. This came back with 15 infections which we successfully quarantined and removed. Once we completed these steps, we deleted all of the encrypted files. There are many variations of ransomware, and they are constantly changing. To prevent ransomware attacks on your computer or network, be cautious about clicking on any attachment on any email. Cyber criminals are getting better at crafting what appear to be legitimate emails. If you are not expecting to receive an email with an attachment from someone, don’t click on the attachment. If you know who the email is from, pick up the phone and call them. We have to assume in this age that any attachment could be a virus. The second step to protecting yourself from ransomware is to back up your computer or at a minimum your My Documents folder. Should you ever get attacked by ransomware, you would not have to worry about paying the ransom or decrypting the files. You would only have to clean the virus off your computer and restore the backup. Plan. Protect. Prosper. Protus3 specializes in security system design, security consulting, corporate investigations and other investigative services. Partner with Protus3 and we will examine each situation to identify threats and develop solutions for your best outcome.
What is Trojan.Kovter infection? In this short article you will certainly find about the definition of Trojan.Kovter as well as its adverse effect on your computer system. Such ransomware are a type of malware that is clarified by on-line fraudulences to require paying the ransom money by a target. In the majority of the instances, Trojan.Kovter ransomware will certainly advise its victims to initiate funds transfer for the objective of counteracting the changes that the Trojan infection has actually presented to the target’s gadget. These modifications can be as complies with: - Executable code extraction. Cybercriminals often use binary packers to hinder the malicious code from reverse-engineered by malware analysts. A packer is a tool that compresses, encrypts, and modifies a malicious file’s format. Sometimes packers can be used for legitimate ends, for example, to protect a program against cracking or copying. - Injection (inter-process); - Injection (Process Hollowing); - Creates RWX memory. There is a security trick with memory regions that allows an attacker to fill a buffer with a shellcode and then execute it. Filling a buffer with shellcode isn’t a big deal, it’s just data. The problem arises when the attacker is able to control the instruction pointer (EIP), usually by corrupting a function’s stack frame using a stack-based buffer overflow, and then changing the flow of execution by assigning this pointer to the address of the shellcode. - Mimics the system’s user agent string for its own requests; - HTTP traffic contains suspicious features which may be indicative of malware related traffic; - Performs some HTTP requests; - Executed a process and injected code into it, probably while unpacking; - Detects VirtualBox through the presence of a library; - Detects Sandboxie through the presence of a library; - Detects SunBelt Sandbox through the presence of a library; - Detects the presence of Wine emulator via function name; - A process attempted to delay the analysis task by a long amount of time.; - Behavior consistent with a dropper attempting to download the next stage.; - Installs itself for autorun at Windows startup. There is simple tactic using the Windows startup folder located at: C:\Users\[user-name]\AppData\Roaming\Microsoft\Windows\StartMenu\Programs\Startup Shortcut links (.lnk extension) placed in this folder will cause Windows to launch the application each time [user-name] logs into Windows. The registry run keys perform the same action, and can be located in different locations: - Attempts to identify installed AV products by installation directory; - Checks the version of Bios, possibly for anti-virtualization; - Checks the presence of disk drives in the registry, possibly for anti-virtualization; - Detects VirtualBox through the presence of a file; - Detects VirtualBox through the presence of a registry key; - Detects VMware through the presence of a file; - Detects VMware through the presence of a registry key; - Detects Virtual PC through the presence of a file; - Detects Virtual PC through the presence of a registry key; - Attempts to modify browser security settings; - Creates a copy of itself; - Attempts to disable System Restore. System Restore function – allows you to revert the computer’s state (system files, applications, and system settings) to that of a previous point in time, which can be used to recover after a virus attack. - Collects information to fingerprint the system. There are behavioral human characteristics that can be used to digitally identify a person to grant access to systems, devices, or data. Unlike passwords and verification codes, fingerprints are fundamental parts of user’s identities. Among the threats blocked on biometric data processing and storage systems is spyware, the malware used in phishing attacks (mostly spyware downloaders and droppers), ransomware, and Banking Trojans as posing the greatest danger. - Anomalous binary characteristics. This is a way of hiding virus’ code from antiviruses and virus’ analysts. - Ciphering the documents situated on the victim’s disk drive — so the target can no longer use the information; - Preventing routine accessibility to the target’s workstation. This is the typical behavior of a virus called locker. It blocks access to the computer until the victim pays the ransom. One of the most common networks where Trojan.Kovter are infused are: - By means of phishing emails; - As a repercussion of customer winding up on a source that holds a destructive software application; As soon as the Trojan is successfully infused, it will certainly either cipher the data on the target’s PC or protect against the gadget from working in a proper fashion – while additionally placing a ransom money note that discusses the requirement for the victims to effect the payment for the function of decrypting the documents or bring back the file system back to the preliminary problem. In the majority of circumstances, the ransom note will come up when the customer restarts the PC after the system has actually already been harmed. Trojan.Kovter distribution networks. In various corners of the world, Trojan.Kovter grows by leaps and bounds. Nonetheless, the ransom money notes and also techniques of obtaining the ransom quantity may vary depending upon particular local (local) setups. The ransom notes and also methods of extorting the ransom amount might differ depending on particular neighborhood (local) settings. As an example: Faulty informs regarding unlicensed software program. In specific areas, the Trojans often wrongfully report having actually detected some unlicensed applications made it possible for on the target’s device. The sharp then demands the customer to pay the ransom money. Faulty declarations concerning unlawful content. In nations where software application piracy is less popular, this approach is not as effective for the cyber fraudulences. Conversely, the Trojan.Kovter popup alert might wrongly declare to be stemming from a law enforcement organization and also will certainly report having located kid porn or various other unlawful information on the gadget. Trojan.Kovter popup alert may incorrectly claim to be acquiring from a legislation enforcement organization and will certainly report having situated child porn or other illegal information on the gadget. The alert will likewise contain a demand for the customer to pay the ransom money. File Info:crc32: E06857C9md5: 71633b70db472fb1605cdff919144daaname: 71633B70DB472FB1605CDFF919144DAA.mlwsha1: 292779188769fea7d78be3f04d4ce819e6dee3e1sha256: dd827e10f5b51d2a4bd1063d7a3340e36be930c8b496e16a553ebc3ed7694a2dsha512: f52ba7f476c253bb9933a22d62d74a3218b141f96968908828939c903f0093cce310f8c106eb921ffb38b4f416d011d8b0dfa815573bdf6589a33d080f0e4674ssdeep: 6144:OZK/dldDmqKsZB6LUDS+ZIrwwABTtDEZ+EXxopLQK2WVHOhoLASIebN2:FlmVsWLOWXUQpM332eR2type: PE32 executable (GUI) Intel 80386, for MS Windows Version Info:0: [No Data] Trojan.Kovter also known as: \|Elastic\|\|malicious (high confidence)\| \|K7AntiVirus\|\|Trojan ( 00514a1a1 )\| \|K7GW\|\|Trojan ( 00514a1a1 )\| \|Cynet\|\|Malicious (score: 100)\| \|MAX\|\|malware (ai score=80)\| \|SentinelOne\|\|Static AI – Malicious PE – Downloader\| How to remove Trojan.Kovter ransomware? Unwanted application has ofter come with other viruses and spyware. This threats can steal account credentials, or crypt your documents for ransom. Reasons why I would recommend GridinSoft1 The is an excellent way to deal with recognizing and removing threats – using Gridinsoft Anti-Malware. This program will scan your PC, find and neutralize all suspicious processes.2. Download GridinSoft Anti-Malware. You can download GridinSoft Anti-Malware by clicking the button below: Run the setup file. When setup file has finished downloading, double-click on the setup-antimalware-fix.exe file to install GridinSoft Anti-Malware on your system. An User Account Control asking you about to allow GridinSoft Anti-Malware to make changes to your device. So, you should click “Yes” to continue with the installation. Press “Install” button. Once installed, Anti-Malware will automatically run. Wait for the Anti-Malware scan to complete. GridinSoft Anti-Malware will automatically start scanning your system for Trojan.Kovter files and other malicious programs. This process can take a 20-30 minutes, so I suggest you periodically check on the status of the scan process. Click on “Clean Now”. When the scan has finished, you will see the list of infections that GridinSoft Anti-Malware has detected. To remove them click on the “Clean Now” button in right corner. Are Your Protected? GridinSoft Anti-Malware will scan and clean your PC for free in the trial period. The free version offer real-time protection for first 2 days. If you want to be fully protected at all times – I can recommended you to purchase a full version: If the guide doesn’t help you to remove Trojan.Kovter you can always ask me in the comments for getting help. User Review( votes)
Some of the basic defensive strategies against DOS include but not limited to: Disabling Unnecessary services Make sure you run hardening on your systems bases on best practices for specific OS. Also make sure unused services are disabled or removed. This is effective technique when it comes to stopping bot’s from being delivered to your system by trojans. Enable Throttling on the routers The attack can be stooped by applying throttling on your router. Use Reverse Proxy Proxy acts as middle man during communication so the attack can be proactively stopped before reaching the server Enable Ingress and Egress Filtering One of the benefits of filtering ingress egress traffic is stooping spoofed addresses from getting on the internal network Service could be automatically shutdown or throttled during attack You can add additional resourced so you can actually handle attack without noticing performance issues.
Users have reported to us receiving alerts indicating unfamiliar devices attempting to access their network equipment. This includes their Nebula switches. Creating firewall policies have safeguarded their router, however, the Nebula switches still encounter attempted undesired access. This is because network switches are usually located under gateways/routers/firewalls. This makes switches more accessible than most devices. For users who are not familiar with setting a management VLAN, they can use the Nebula switch's ACL to protect their network devices by black-listing devices attempting to access their network equipment. SETUP/STEP BY STEP PROCEDURE: 1. Set static IP addresses for your network equipment. This includes the administrator's PC/laptop/notebooks. 2. Sign-in to Nebula CC and go to Switch > ACL and set up an ACL to accommodate to the traffic you want to block 1. Connect a device set with an IP address of the device attempting access. 2. The device should not be able to access the respective ports of network equipment(s).
Broadcasting is envisioned to be a vital technology that will govern the behavior and analysis of vehicular networks. Since the topology of VANETs is subject to rapid changes, an efficient utilization of the broadcasting technology can easily help in conveying the location information of the vehicles as well as for the purpose of avoiding accidents. This work, with an emphasis on the broadcasting of emergency messages in a multi-hop broadcasting scenario, studies the characteristics of broadcasting delay in a vehicular ad hoc network by means of simulations for various network scenarios. The broadcasting delay is evaluated and simulated for the following scenarios - sparse networks, freeway scenario and cluster-based networks, which compensate for the short-comings in a freeway scenario. The effect of variation in the ZOR was also observed. Finally, the cluster based model was incorporated in the freeway scenario and its resulting effect on the delay behavior was observed. G. Narayanan, “Comparison of the delay performance for various vehicular communication network scenarios”, in International Conference on Communications and Signal Processing (ICCSP), 2014 , Melmaruvathur, 2014.
Skip to Main Content This paper studies distributed, combined authentication and intrusion detection with data fusion in mobile ad-hoc networks (MANETs). Multimodal biometrics are deployed to work with intrusion detection systems (IDSs) to alleviate the shortcomings of unimodal biometric systems. Since each device in the network has measurement and estimation errors, more than one device needs to be chosen, and observations can be fused to increase observation accuracy using Dempster-Shafer theory for data fusion. The system decides whether or not user authentication (or IDS input) is required, and which biosensors (or IDSs) should be chosen depending on the security posture. The decisions are made in a fully distributed manner by each authentication device and each IDS. Simulation results are presented to show the effectiveness of the proposed scheme.
It seems that every week a new way of targeting Android users with malware is discovered, and most often than not, Russian users are primary targets. Sophos’ researcher Vanja Svajcer followed links lately disseminated through Twitter, and landed on a number of .ru domains pointed to the same IP address hosted in Ukraine. “Depending on the URL you click on and URL parameters, you might be prompted (in Russian) to install fake updates for a variety of products including the Opera browser and Skype,” Graham Cluley reports. “Or you might be presented with a page which prompts you to run a security scan on your phone.” The scans are, of course, bogus, and the apps offered after them are as well. They appear to be antivirus applications – and sometimes they even present icons stolen from legitimate security firms such as Kaspersky Lab – but most of the time are actually premium rate Trojans. Also, if one is very unlucky, the downloaded Trojans also have the ability to download further malware onto the device.
Information Security and Regulatory Compliance Glossary Access Control is a security technique that regulates who or what can view, use, or access resources in a computing environment. It is a fundamental concept in security that minimizes risk to the business or organization. There are two types of access control: physical and logical. Physical access control limits access to buildings, rooms, and physical IT assets. Logical access control limits connections to computer networks, system files, and data. Access Control List (ACL) An Access Control List (ACL) is a list of permissions attached to an object that specifies which users or system processes are granted access to objects, as well as what operations are allowed on given objects. Each entry in a typical ACL specifies a subject and an operation. Advanced Persistent Threat (APT) An advanced persistent threat (APT) is a prolonged, aimed attack on a specific target with the intention to compromise their system and gain information from or about that target. APT attacks are typically carried out by organized cybercriminal groups and can extend over a long period of time, often going unnoticed for months or even years. An air gap, in computer security, is a measure or design intended to prevent insecure connections between an unsecured network, for instance, the public internet, and a secured computer system. An air-gapped system is one that is physically isolated from unsecured networks. Application Security involves measures taken to improve the security of an application often by finding, fixing and preventing security vulnerabilities within the application. This can include security considerations in the design and development, but also system configuration, and the deployment processes. An audit in the context of information security is a systematic evaluation of the security of a company's information system by measuring how well it conforms to a set of established criteria. This typically includes assessments of various aspects like physical configuration, environment, software, information handling processes, and user practices. An Audit Trail is a record of the sequence of activities detailing the operational history within an organization or system. In IT, this often includes logs of who has accessed a computer system, when it was accessed, and what operations were performed. It's crucial for maintaining security, recovering lost transactions, and in the forensic investigation of a cyber incident. The ability to prove that a person or application is genuine, verifying the identity of that person or application. Authentication uses one or more of three primary methods, or factors: what you know, what you are, and what you have. “What you know” encompasses passwords, personal identification numbers (PINs), passphrases, and other secrets. This type of authentication is not strong on its own and is typically paired with another authentication factor. “What you are” involves biometric authentication methods, such as retinal scans, fingerprints, voice or signature recognition, and so on. These factors cannot be easily changed if compromised. “What you have” entails objects or applications running on objects that you physically possess. Traditionally this involved keys, but modern forms may also involve USB tokens, smart cards, and one-time password applications on devices. This factor requires possession of the object at the time of use and may be hindered by intentional or unintentional loss of, or damage to, the object. Authorization is the act of determining whether a user or application has the right to conduct particular activities in a system. This determination is typically based on the role that a user holds within the organization, and the rights associated with that role. This concept is known as Role-Based Access Control (RBAC). In this model, roles are created for various job functions, and permissions to perform certain operations are assigned to specific roles. Users are then assigned appropriate roles, and through those roles, users acquire the permissions to perform particular system functions. Because users are not assigned permissions directly, but only acquire them through their roles (role-based privileges), management of individual user rights becomes a matter of simply assigning appropriate roles to the user's account; this simplifies common operations, such as adding a user or changing a user's department. Availability is the assurance that data and services are accessible to authorized users whenever needed. This involves maintaining system and service uptime, ensuring system resources are not overwhelmed, and implementing robust backup and recovery procedures to prevent and recover from potential failures. Redundancy is often used as a measure to ensure availability. A subset of authentication methods that uses unique physical or behavioral characteristics to verify an individual's identity. This can include fingerprints, facial recognition, iris or retinal scans, voice recognition, and even typing rhythm. Biometric authentication provides a higher level of security as these characteristics are difficult to replicate, but it also raises privacy concerns and cannot be changed if compromised. Blue Teaming refers to the internal defense team that defends against both real attackers (external threats) and the Red Team (internal, simulated attacks). Brute Force Attack A brute force attack is a trial-and-error method used to obtain information such as a user password or personal identification number (PIN). In a brute force attack, automated software is used to generate a large number of consecutive guesses as to the value of the desired data. Business Continuity Planning (BCP) A proactive planning process that ensures critical services or products are delivered during a disruption. This includes identifying potential threats to an organization, assessing the impact of those threats, and developing strategies to minimize the impact. BCP aims to minimize financial loss and prevent damage to the organization's reputation, while ensuring the quick resumption of time-sensitive tasks and processes. The CIA Triad is an abbreviation for the core tenets of information security: confidentiality, integrity, and availability. These principles need to be in balance, as an overemphasis on one may lead to weaknesses in others. For instance, focusing too much on confidentiality could make data less available to authorized users. Cloud Computing is the delivery of different services through the Internet, including data storage, servers, databases, networking, and software. These cloud-based services are designed to provide easy, scalable access to applications, resources and services, and are fully managed by a cloud services provider. In the context of information security, compliance refers to the process of adhering to a set of specific standards, regulations, laws, or policies that are applicable to a particular business or sector. These regulations can be internal (company policies) or external (laws or industry standards). Compensating controls are alternative security measures implemented when a primary control is not feasible or cost-effective. The compensating control must effectively mitigate the risk to an acceptable level. These controls are typically used when an organization can't comply with a security standard's primary requirements for technical or business reasons. Confidentiality involves ensuring that sensitive information is accessed only by those with a legitimate need to know. This is often enforced through encryption, access controls, and other protective measures designed to keep unauthorized individuals from accessing the data. Controlled Unclassified Information (CUI) Controlled Unclassified Information (CUI) is a category of information that law, regulation, or government-wide policy requires to have safeguarding or dissemination controls, but is not classified under Executive Order 13526 or the Atomic Energy Act. This typically includes information that may pertain to privacy, proprietary business interests, and law enforcement investigations. Criminal Justice Information Services (CJIS) CJIS is a division of the United States Federal Bureau of Investigation (FBI) that provides criminal justice information needed to perform law enforcement duties. The CJIS Security Policy outlines the security precautions that must be taken to protect this data, including in areas such as authentication, access control, encryption, and auditing. Cybersecurity Maturity Model Certification (CMMC) The Cybersecurity Maturity Model Certification (CMMC) is a unified cybersecurity standard for future Department of Defense (DoD) acquisitions. Depending on the sensitivity of the information, different levels of CMMC might be required, ranging from basic cyber hygiene to advanced. A data breach is an incident where data is accessed, exposed, copied, transmitted, viewed, or stolen by an unauthorized party. This can involve any form of data: electronic or paper. The data could be sensitive, protected, or confidential, such as credit card numbers, customer data, personal identification information, intellectual property, trade secrets, and so on. This term does not indicate intent; other terms such as 'data leak' and 'information leakage' help convey whether a data breach was intentional or not. Data Encryption is the method of using an algorithm to transform data into a form that is unreadable without a decryption key. Its purpose is to secure sensitive and confidential data, both at rest and in transit, to prevent unauthorized access. Data Loss Prevention (DLP) A strategy, encompassing a set of technologies, processes, and procedures, designed to prevent sensitive or critical information from being sent outside the corporate network, lost, misused, or accessed by unauthorized users. DLP involves control over what data end users can transfer and typically includes the monitoring, detection, and blocking of data in motion, data at rest, and data in use. This term is also used to describe software products that assist a network administrator in implementing these controls. Data Masking is a method of creating a structurally similar but inauthentic version of an organization's data that can be used for purposes such as software testing and user training. This helps protect the actual data while having a functional substitute for occasions when the real data is not required. Data Protection Impact Assessment (DPIA) A Data Protection Impact Assessment (DPIA) is a process designed to help organizations systematically analyze, identify and minimize the data protection risks of a project or plan. DPIAs are often used in the context of GDPR compliance. Defense-in-depth is a strategy that employs a series of mechanisms to slow the advance of an attack aimed at acquiring unauthorized access to information. This layered approach to security can include physical security, network security, antivirus software, user authentication, and encryption, among others. Each layer provides protection so that if one layer is breached, a subsequent layer is already in place to thwart an attack. Defense Information Systems Agency (DISA) The Defense Information Systems Agency (DISA) is a combat support agency of the U.S. Department of Defense (DoD). DISA provides, operates, and assures command and control and information-sharing capabilities and a globally accessible enterprise information infrastructure in direct support to joint warfighters, national level leaders, and other mission and coalition partners across the full spectrum of military operations. DISA Security Technical Implementation Guides (STIGs) DISA Security Technical Implementation Guides (STIGs) are the configuration standards for DoD Information Assurance (IA) and IA-enabled devices and systems. A STIG describes how to minimize network-based attacks and prevent system access when the attacker is trying to gain access through a system’s network interface. They are a valuable resource to help secure large and complex network infrastructures. Denial-of-Service (DoS) Attack A type of cyber attack in which an attacker seeks to make a machine or network resource unavailable to its intended users by temporarily or indefinitely disrupting services of a host connected to the Internet. This is typically accomplished by flooding the targeted system with requests, in an attempt to overload systems and prevent some or all legitimate requests from being fulfilled. Distributed Denial of Service (DDoS) Attack A variant of the Denial-of-Service (DoS) attack, but the attack source is more than one, often thousands of, unique IP addresses. It is distinct from DoS attacks, as the attack traffic is generated from a distributed network of compromised devices, often referred to as a 'botnet'. These attacks can be significantly more difficult to mitigate due to the distributed nature of the attack source. Disaster Recovery (DR) Disaster Recovery is the coordinated process of restoring systems, data, and infrastructure required for maintaining or resuming critical business operations after a disaster or disruption. This process involves various steps such as planning, testing, and implementing strategies like data backup and recovery, system redundancy, and contingency planning. E-Discovery refers to discovery in legal proceedings such as litigation, government investigations, or Freedom of Information Act requests, where the information sought is in electronic format. It can be an involved process that entails identifying, securing, and searching electronic records for relevant evidence. In the context of network security, an endpoint is any device that communicates back and forth with a network, including but not limited to desktops, laptops, smartphones, and servers. This refers to the approach of safeguarding the various endpoints on a network, which are entry points for security threats. Endpoint security involves both security software located on a centrally managed and accessible server or gateway within the network and client software installed on each endpoint device. This system monitors and blocks potentially harmful activities and/or objects that could jeopardize the network, providing protection for the network when accessed via remote devices such as laptops, smartphones, or other wireless and mobile devices. Encryption is the process of converting plaintext into encoded data (ciphertext) to prevent unauthorized access. Only authorized parties can decipher a ciphertext back to plaintext and access the original information. Encryption does not prevent interference, but denies the intelligible content to a would-be interceptor. In an encryption scheme, the intended information or message, referred to as plaintext, is encrypted using an encryption algorithm - a cipher - generating ciphertext that can be read only if decrypted. Federal Information Security Management Act (FISMA) FISMA is United States legislation that defines a comprehensive framework to protect government information, operations and assets against natural or man-made threats. FISMA was enacted as part of the Electronic Government Act of 2002. FedRAMP is a government-wide program that provides a standardized approach to security assessment, authorization, and continuous monitoring for cloud products and services used by federal agencies. Its goal is to ensure effective, repeatable cloud security for the government. A firewall is a network security system that monitors and controls incoming and outgoing network traffic based on predetermined security rules. A firewall typically establishes a barrier between a trusted internal network and untrusted external network, such as the Internet. A finding refers to an issue that has been identified during an audit or assessment. In information security, a finding could be a weakness or deficiency in the system that could potentially be exploited by a threat actor, or it could be an area where the organization is not meeting its own policies or a regulatory requirement. General Data Protection Regulation (GDPR) The General Data Protection Regulation (GDPR) is a regulation in EU law on data protection and privacy in the European Union and the European Economic Area. It also addresses the transfer of personal data outside these areas. GDPR aims to give control to individuals over their personal data and to simplify the regulatory environment for international business. Health Insurance Portability and Accountability Act (HIPAA) The Health Insurance Portability and Accountability Act (HIPAA) is a federal law that requires the creation of national standards to protect sensitive patient health information from being disclosed without the patient's consent or knowledge. A honeypot is a computer system that is set up to act as a decoy to lure cyber attackers, and to detect, deflect, or study attempts to gain unauthorized access to information systems. Honeypots can be designed to purposely engage and deceive hackers and identify malicious activities performed over the Internet. Identification is the process of a user asserting a claimed identity, such as by providing a username or email address. It's the first step in access control and is followed by authentication, which is the process of verifying the claimed identity. Identification establishes the 'who' for access control and accountability, while authentication verifies that 'who.' Identity and Access Management (IAM) Identity and access management (IAM) is a framework for business processes that facilitates the management of electronic or digital identities. The framework includes the technology needed to support identity management. An incident is the attempted or successful unauthorized access, use, disclosure, modification, or destruction of information, or interference with system operations. Incidents can be caused by people, natural phenomena, disasters, and even animals. When an incident occurs, it's crucial for organizations to have an Incident Response plan in place. This is a structured approach to addressing and managing the aftermath of a security incident with the aim to limit damage and reduce recovery time and costs. The organized approach to addressing and managing the aftermath of a security breach or cyberattack. The goal is to manage the situation in a way that limits damage, reduces recovery time and costs, and enhances the organization's resilience. An effective incident response plan involves identification, containment, eradication, recovery, and lessons learned to prevent future incidents. Information Assurance (IA) Information Assurance (IA) is the practice of assuring information and managing risks related to the use, processing, storage, and transmission of information or data and the systems and processes used for those purposes. IA includes protection of the integrity, availability, authenticity, non-repudiation, and confidentiality of user data. Information Governance is the management of information at an organization. It includes policies, processes, and controls designed to manage information throughout its lifecycle, from creation, use, maintenance, to disposal, with regard to regulatory compliance, data protection, and data privacy. Information Security Management System (ISMS) An Information Security Management System (ISMS) is a set of policies, procedures, and systems for managing risks to organizational data, with the objective of ensuring acceptable levels of information security risk. Integrity in information security refers to maintaining the accuracy, consistency, and trustworthiness of data over its entire life cycle. Measures taken to ensure integrity include controlling the physical environment of networked terminals and servers, restricting access to data, and maintaining rigorous authentication practices. Data integrity can be threatened by many things including human error, physical damage to hardware, malicious activity, and more. Intrusion Detection System (IDS) An Intrusion Detection System (IDS) is a system that monitors network traffic for suspicious activity and alerts the system or network administrator. In some cases, the IDS may also respond to anomalous or malicious traffic by taking action such as blocking the user or source IP address from accessing the network. Intrusion Prevention System (IPS) An Intrusion Prevention System (IPS) is a system that examines network traffic flows to detect and prevent vulnerability exploits, which are the main method by which malware is delivered onto a network. An IPS not only detects malicious activities but also takes proactive actions to prevent the data from entering the network. ISO 27001 is a specification for an information security management system (ISMS). An ISMS is a framework of policies and procedures that includes all legal, physical and technical controls involved in an organization's information risk management processes. Lateral movement refers to the techniques that a cyber attacker uses to move through a network in search of targeted key data and assets after gaining initial access. This can involve exploitation of vulnerabilities in software, abuse of system features, or use of stolen credentials. These techniques are typically used to avoid detection and gain access to sensitive data or privileged system access. The principle of least privilege recommends that only the minimum access rights necessary for staff or systems to perform their authorized tasks should be assigned, and for the minimum duration necessary. This approach minimizes the risk of unauthorized access or actions. A modern implementation of this principle is just-in-time (JIT) access, where users are granted the necessary permissions only at the moment they're needed, and these permissions are revoked immediately after. Malicious software designed to infiltrate, damage, or disable computers, computer systems, networks, or electronic devices, often while giving a threat actor remote control over the affected systems. Malware encompasses a range of software types, including viruses, worms, ransomware, and spyware. It spreads through various methods such as email attachments, software downloads, or malicious websites. Malware analysis is the process of understanding the behavior and purpose of a suspicious file or URL to help mitigate potential risks. It involves using a variety of tools and techniques to assess the nature, functionality, and potential impact of the suspected malware. Multi-Factor Authentication (MFA) is a method that uses authentication techniques from two or more of the distinct categories of factors. For example, combining a password (something you know) with a one-time password generated by an app on a smartphone (something you have), or a facial scan (something you are) with a PIN. This approach significantly enhances security because even if one factor is compromised, an attacker still has at least one more barrier to breach. It's important to note that true MFA requires elements from different categories. Two elements from the same category (e.g., two types of something you know, like a password and a security question) does not constitute MFA but is instead referred to as two-step verification. Network Address Translation (NAT) Network Address Translation (NAT) is a method of remapping one IP address space into another by modifying network address information in the IP header of packets while they are in transit across a traffic routing device. Network segmentation is the practice of dividing a computer network into subnetworks, each being a network segment or network layer. Advantages of such division are primarily for boosting performance and improving security through isolation. NIST 800-53 is a publication from the National Institute of Standards and Technology (NIST) that provides a catalog of security and privacy controls for all U.S. federal information systems except those related to national security. It is part of the NIST Risk Management Framework. NIST 800-171 is a set of standards that define how to protect sensitive, non-classified information in non-federal systems and organizations. It's often used by government contractors and subcontractors to adequately safeguard controlled unclassified information (CUI). North American Electric Reliability Corporation Critical Infrastructure Protection (NERC CIP) NERC CIP is a set of standards designed to secure the assets required for operating North America's bulk electric system. The NERC CIP plan consists of 9 standards and 45 requirements covering the security of electronic perimeters and the protection of critical cyber assets as well as personnel and training, security management and disaster recovery planning. Non-repudiation refers to the ability to ensure that a party to a contract or a communication cannot deny the authenticity of their signature on a document or the sending of a message. In digital security, it provides proof of the origin or delivery of data to protect the sender against false denial by the recipient that the data has been received, or to protect the recipient against false denial by the sender that the data has been sent. Patch Management is a process used in IT to ensure that all systems are up-to-date with the latest security patches and updates. This is crucial for protecting systems against known vulnerabilities that can be exploited by attackers. Patch management activities include: maintaining knowledge of available patches, deciding which patches are appropriate for particular systems, ensuring patches are installed properly, testing systems after installation, and documenting all associated procedures. Payment Card Industry Data Security Standard (PCI DSS) The Payment Card Industry Data Security Standard (PCI DSS) is an information security standard for organizations that handle branded credit cards from the major card schemes. PCI DSS helps to prevent credit card fraud through increased controls around data and its exposure to compromise. A method of evaluating the security of a computer system, network, or web application by simulating an attack from a malicious source. Privilege escalation happens when a user gets access to more resources or functionality than they are normally allowed, and such elevation or changes should have been prevented by the system. This concept is significant in the context of a malicious cyber-attack, where an intruder initiates a privilege escalation attack to exploit a bug, design flaw, or configuration oversight in an operating system or software application to gain elevated access to resources. Privileged Access Management (PAM) A cybersecurity discipline that encompasses the strategies and technologies for exerting control over the elevated (“privileged”) access and permissions for users, accounts, processes, and systems across an IT environment. Phishing is a type of social engineering attack often used to steal user data, including login credentials and credit card numbers. It occurs when an attacker, masquerading as a trusted entity, tricks a victim into opening an email, instant message, or text message. The recipient is then tricked into clicking a malicious link, which can lead to the installation of malware, the freezing of the system as part of a ransomware attack, or the revealing of sensitive information. Privacy Impact Assessment (PIA) A tool for identifying and assessing privacy risks throughout the development life cycle of a program or system. A PIA examines how personal information is collected, used, stored, and shared, and it helps organizations make informed decisions about privacy aspects related to products, services, or initiatives. A thorough PIA helps ensure compliance with privacy laws, regulations, and policies, while also building trust through transparency. Public Key Infrastructure (PKI) Public Key Infrastructure (PKI) is a technology for authenticating users and devices in the digital world. The basic idea is to have one or more trusted parties digitally sign documents certifying that a particular cryptographic key belongs to a particular user or device. Ransomware is a type of malicious software designed to block access to a computer system or data until a sum of money or ransom is paid. Red Teaming is a full-scope, multi-layered attack simulation designed to measure how well a company's people, networks, applications and physical security controls can withstand an attack from a real-life adversary. Recovery Point Objective (RPO) Recovery Point Objective (RPO) refers to the maximum tolerable period in which data might be lost due to a major incident. It is measured in time, such as 'one hour of customer data'. This means that, in the event of a disaster, the organization should be prepared to lose up to one hour's worth of data. RPO is a key consideration in backup and disaster recovery planning. Recovery Time Objective (RTO) Recovery Time Objective (RTO) is the targeted duration of time within which a business process must be restored after a disaster or disruption to avoid unacceptable consequences associated with a break in business continuity. In other words, it's the length of time your business can afford to be 'down' or offline. Risk Assessment is the process of identifying, estimating, and prioritizing risks to organizational operations and assets resulting from the operation and use of information systems. The risk assessment process is used to identify potential threats, vulnerabilities that could be exploited by the threats, and the potential impact on the organization should a threat exploit a vulnerability. Risk Management Framework (RMF) The Risk Management Framework (RMF) is a set of criteria that dictate how the United States government IT systems must be architected, secured, and monitored. Initially developed by the Department of Defense (DoD), the RMF was later adopted by the rest of the U.S federal information systems in 2010. Secure coding is the practice of developing computer software in a way that guards against the accidental introduction of security vulnerabilities. It involves regular testing and code review, and the use of coding practices specifically designed to promote security. Security Architecture refers to the design artifacts that describe how the security controls (security countermeasures) are positioned, and how they relate to the overall systems architecture. These controls serve the purpose to maintain the system's quality attributes, among them confidentiality, integrity, availability, accountability and assurance. Security Awareness Training Security Awareness Training is a formal process for educating employees about computer security. The goal is to enable employees to understand potential threats to the organization's information and how to apply best practices to prevent breaches or attacks. Security controls are safeguards or countermeasures employed to avoid, detect, counteract, or minimize security risks. They can be categorized into administrative (policies and procedures), physical (locks, fences), and technical (firewalls, access controls) controls. These controls aim to protect the confidentiality, integrity, and availability of data. Security Information and Event Management (SIEM) Security Information and Event Management (SIEM) software products and services combine security information management (SIM) and security event management (SEM). They provide real-time analysis of security alerts generated by applications and network hardware. Security Operations Center (SOC) A centralized unit that deals with security issues on an organizational and technical level. Sarbanes-Oxley Act (SOX) The Sarbanes-Oxley Act (SOX) is a United States federal law that mandates certain practices in financial record keeping and reporting for corporations. This law has implications for information security, particularly in areas such as access controls, data retention, and data protection. Security Operations, Automation, and Response (SOAR) Security Orchestration, Automation, and Response (SOAR) is a term for software products and services that help streamline and automate the incident response process in an organization's security operations center (SOC). SOAR tools allow an organization to collect data about security threats from multiple sources and automate responses to low-level threats. A Security Policy is a high-level plan that outlines the organization's security principles, approach, guidelines, and standards. It sets the strategic direction, scope, and tone for all security efforts within the organization. Security Posture is the security status of an enterprise's networks, information, and systems based on information security resources (e.g., people, hardware, software, policies) and capabilities in place to manage the defense of the enterprise and to react as the situation changes. Security Risk is the potential for losses or other adverse impacts to arise due to vulnerabilities that could be exploited by threats. These losses or impacts can be to the information or the systems that process, store, and transmit that information. Secure Sockets Layer (SSL) / Transport Layer Security (TLS) SSL and TLS are cryptographic protocols designed to provide communications security over a computer network. Websites use TLS to secure all communications between their servers and web browsers. SSL is the predecessor to TLS. Security Testing is the process of evaluating and testing an information system, network, or web application to find vulnerabilities, weaknesses, or compliance issues that could be exploited or lead to a potential breach or loss of data, affecting the system's information security. Separation of Duties Separation of Duties (SoD) is a key concept of internal controls and is the most common way to prevent or detect internal fraud. The principle of SoD is that no employee or group should be in a position to both perpetrate and conceal errors or fraud in the normal course of their duties. In general, the flow of responsibilities should be organized so that the successful completion of a process requires the participation of two or more individuals or departments. Social engineering is a tactic that adversaries use to trick you into revealing sensitive information. They can solicit a monetary payment or gain access to your confidential data. Social engineering can be combined with any of the threats listed above to make you more likely to click on links, download malware, or trust a malicious source. Spear phishing is an email or electronic communications scam targeted towards a specific individual, organization or business. Although often intended to steal data for malicious purposes, cybercriminals may also intend to install malware on a targeted user’s computer. StateRAMP is an independent non-profit organization that provides a security framework similar to FedRAMP, but intended for use by state, local, tribal, and territorial governments. Its purpose is to standardize, streamline, and improve cybersecurity risk management. Supply Chain Attack A Supply Chain Attack is a cyber attack that seeks to damage an organization by targeting less-secure elements in the supply network. System hardening is the process of securing a system by reducing its surface of vulnerability. This is typically accomplished by removing unnecessary software, unnecessary usernames or logins and the disabling or removal of unnecessary services. Threat Hunting refers to the proactive search for malware or attackers lurking in a network. Unlike other forms of threat detection, threat hunting is unique in that it is performed by human analysts and involves the proactive identification of adversaries rather than waiting for automated alerts. Threat Intelligence, in the context of cybersecurity, is knowledge that allows you to prevent or mitigate cyber attacks. It is the process of using tools, techniques and intelligence to understand and analyze potential threats that could harm the organization. Transport Layer Security (TLS) / Secure Sockets Layer (SSL) SSL and TLS are cryptographic protocols designed to provide communications security over a computer network. Websites use TLS to secure all communications between their servers and web browsers. SSL is the predecessor to TLS. Two-Factor Authentication (2FA) A security measure that requires two distinct methods, or factors, to verify a user's identity. This process provides a higher level of security than single-factor authentication (SFA), which typically involves only a password or passcode. The two factors in 2FA can include something the user knows, such as a username and password, and something the user has, like a smartphone app to approve authentication requests. The objective of 2FA is to enhance the protection of both the user's credentials and the resources the user can access. Virtual Local Area Network (VLAN) A virtual LAN (VLAN) is any broadcast domain that is partitioned and isolated in a computer network at the data link layer (OSI layer 2). VLANs work by applying tags to network frames and handling these tags in networking systems – creating the appearance and functionality of network traffic that is physically on a single network but acts as if it is split between separate networks. Virtual Private Network (VPN) A VPN extends a private network across a public network and enables users to send and receive data across shared or public networks as if their computing devices were directly connected to the private network. It provides a secure tunnel for your internet connection, protecting your data from attackers. A vulnerability is a weakness in an information system, system security procedures, internal controls, or implementations that could be exploited by a threat source. Vulnerability management, the practice of identifying, classifying, prioritizing, and resolving vulnerabilities, is a crucial part of maintaining robust security. This often involves the use of automated vulnerability scanners and regular patch management. An ongoing process of identifying, classifying, prioritizing, mitigating, and remediating vulnerabilities in software and hardware systems. This includes regular scanning for weaknesses, risk assessment to understand their impact, patch management to fix the vulnerabilities, and reporting to ensure transparency and continuous improvement. Effective vulnerability management helps protect systems against exploitation and reduces the potential attack surface. Whaling is a specific kind of malicious hacking within the more general category of phishing, which involves hunting for data that can be used by the hacker. In general, phishing efforts are focused on collecting personal data about users. In whaling, the targets are high-ranking bankers, executives or others in powerful positions or job titles. Zero Trust is a security concept centered on the belief that organizations should not automatically trust anything inside or outside its perimeters and instead must verify anything and everything trying to connect to its systems before granting access. The strategy around Zero Trust boils down to "never trust, always verify." Zero Trust Architecture A security concept centered on the belief that organizations should not automatically trust anything inside or outside its perimeters and instead must verify anything and everything trying to connect to its systems before granting access. A cyberattack that occurs on the same day a vulnerability becomes known to the public and before a patch or solution is implemented. In these situations, the software developers have zero days to fix the issue, hence the term. These exploits are highly valuable to attackers, as they take advantage of vulnerabilities that are currently unprotected, making the systems susceptible to unauthorized actions.
What is Honeypot ? A honeypot is a cybersecurity technique that involves setting up a decoy system or network with the purpose of attracting and detecting hackers and other cyber attackers. The honeypot appears to be a legitimate target, but in reality, it is a trap that is designed to gather information about the tactics, techniques, and procedures (TTPs) used by attackers. How it Works ? Honeypots work by luring attackers into a system that appears to be a legitimate target, but is actually a trap. When an attacker interacts with the honeypot, the system captures information about the attacker's methods, such as the IP address, tools and techniques used, and the specific actions taken. This information can then be used to improve security measures and better protect real systems and networks from future attacks. Types of Honeypots: Honeypots can be classified on the basis of their deployment and their level of involvement. On the basis of deployment, honeypots can be classified as: 1. Production honeypots These honeypots are deployed in a production environment and simulate real systems and services that an organization might use. They are often used to detect attacks against specific systems or services, such as web servers or email servers. 2. Research honeypots These honeypots are designed to be used by researchers and security professionals to gather data about attacks and attackers. They are often deployed in a controlled environment and can be customized to simulate different types of systems and services. Based on the level of involvement, honeypots can be classified as: 1. High-interaction honeypots These honeypots fully emulate real systems and services, giving attackers the impression that they are interacting with a legitimate system. High-interaction honeypots are more difficult to set up and maintain, but they can provide more detailed information about attackers and their methods. 2. Low-interaction honeypots These honeypots simulate only the most common protocols and services, such as HTTP or FTP. They are easier to set up and maintain, but provide less detailed information about attackers. 3. Pure honeypots A pure honeypot is a type of honeypot that is designed to be completely passive, meaning it does not interact with attackers in any way. It is a decoy system or network that is set up to attract and detect attacks, without taking any active measures to prevent or respond to them. Honeyd is a low-interaction honeypot that simulates a variety of different systems and services. It is easy to set up and is often used for research and education purposes. Kippo is a high-interaction honeypot that emulates an SSH server. It captures information about attackers, including their usernames, passwords, and commands used. Dionaea is a high-interaction honeypot that is designed to capture malware samples and gather information about attackers. It supports a wide range of protocols and services, including HTTP, FTP, and SMB. Cowrie is a high-interaction honeypot that emulates a Telnet or SSH server. It captures information about attackers, including their usernames, passwords, and commands used. Honeypots can be used in a variety of different contexts, including in research, as a tool for training security personnel, and as part of an organization's overall cybersecurity strategy.
GetCrypt Ransomware Description Malware experts have identified a new ransomware threat, which is targeting innocent users. They dubbed it the GetCrypt Ransomware. File-locking Trojans, like the GetCrypt Ransomware, have been very popular among cybercriminals in recent years. They claim their victims by tricking the users into allowing the threat onto their computers. Then the data-encrypting Trojan locks the user's data and demands cash in return for the decryption key. This is a very aggressive and threatening malware type. The GetCrypt Ransomware is likely being propagated using mass spam email campaigns, bogus application updates and corrupted pirated software. Once the GetCrypt Ransomware lands on your machine, it will perform an extensive scan of your data. When the scan is completed, the GetCrypt Ransomware would have identified and located all the files it was set to encrypt. Logically, the next step is the encryption process itself. The GetCrypt Ransomware would lock your files and add a new extension at the end of the file name. It is interesting that this file-locking Trojan does not have a consistent extension that it adds; instead, the GetCrypt Ransomware applies random 4-character extensions to the affected files. For example, the new extension could be '.OGHF' or '.TRSP,' etc. The next step is dropping the ransom note. The GetCrypt Ransomware's ransom note is named '# DECRYPT MY FILES #.txt.' Using only capital letters accompanied by exclamation marks or other symbols as a ransom note name is a common method used by cybercriminals because it makes the note more visible to the victim. In the note, the creators of the GetCrypt Ransomware inform the users that their data have been locked using a 'strong algorithm.' They also go on to say that it is impossible to recover the encrypted data without using the original key (which the attackers have). Then, the authors of the GetCrypt Ransomware provide an email '[email protected],' where the user is meant to contact them. In case they do not receive a reply within 48 hours, the attackers ask the victim to send an email to an alternative address – [email protected]. We recommend you not to follow these instructions. It is not a good idea to pay cybercriminals not only because your cash will go towards their shady future endeavors, but because it is likely that they will not provide you with the decryption key they are promising. A better option is to make sure you install a reputable anti-malware application and have it clean your computer of this nasty bug. File System Details \|#\|\|File Name\|\|Size\|\|MD5\|\|Detection Count\| This article is provided "as is" and to be used for educational information purposes only. By following any instructions on this article, you agree to be bound by the disclaimer. We make no guarantees that this article will help you completely remove the malware threats on your computer. Spyware changes regularly; therefore, it is difficult to fully clean an infected machine through manual means.
Exporting data to a Syslog server To increase the space in the database, you can configure the management server to send the log data to a Syslog server. When you export log data to a Syslog server, you must configure the Syslog server to receive the logs. See Exporting log data to a text file To export log data to a Syslog server In the console, click . Click the local site or remote site that you want to export log data from. On the General tab, in the list box, select how often to send the log data to the file. In the list box, select the management server to send the logs to. If you use SQL Server and connect multiple management servers to the database, specify only one server as the Master Logging Server. Provide the following information: Type the IP address or domain name of the Syslog server that you want to receive the log data. Select the protocol to use, and type the destination port that the Syslog server uses to listen for Syslog messages. Type the number of the log facility that you want to the Syslog configuration file to use, or use the default. Valid values range from 0 to 23. On the Log Filter tab, check which logs to export.

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