README.md

metadata

title: WhiteRabbitNeo
emoji: 💬
colorFrom: green
colorTo: purple
sdk: gradio
sdk_version: 5.9.1
app_file: app.py
pinned: true
license: mit
thumbnail: >-
  https://cdn-uploads.huggingface.co/production/uploads/64fbe312dcc5ce730e763dc6/VWduEhDSRJXeSqhUzYwCt.png

RabbitRedux: A Specialized Cybersecurity Code Classifier

RabbitRedux is an AI-powered model designed to classify and analyze code snippets, with a focus on cybersecurity applications like penetration testing, ransomware analysis, and security automation. Built upon the WhiteRabbitNeo/Llama-3.1-WhiteRabbitNeo-2-70B model, RabbitRedux is specialized for cybersecurity and offers high accuracy in analyzing and categorizing both general and cybersecurity-related code functions.

Key Features

• Penetration Testing Support: Assists in reconnaissance, enumeration, and task automation during penetration testing.
• Ransomware Analysis: Tracks and analyzes ransomware trends, providing actionable insights into emerging threats.
• Code Classification: Efficiently classifies code in general programming and cybersecurity-specific contexts.
• Adaptive Learning: Utilizes adapter transformers for modular training, making it flexible for quick adaptations to different tasks.

Datasets Used RabbitRedux leverages a range of datasets focused on both general and cybersecurity-specific tasks:

• Canstralian/Wordlists: A collection of cybersecurity-related wordlists for improved analysis.
• Canstralian/CyberExploitDB: A database of known cybersecurity exploits for model training.
• Canstralian/pentesting_dataset: A dataset containing pentesting-specific code snippets and functions.
• Canstralian/ShellCommands: A dataset dedicated to shell commands commonly used in security operations.

Model Details

Developer: Canstralian Base Model: WhiteRabbitNeo/Llama-3.1-WhiteRabbitNeo-2-70B, replit/replit-code-v1_5-3b Library: Adapter Transformers License: MIT License Metrics: Precision, Recall, F1 Score Evaluation: Evaluated for code classification tasks with an emphasis on cybersecurity Tags: code, text-generation-inference, security, cybersecurity

Usage

To use RabbitRedux for code classification, simply load the model and apply it for your cybersecurity tasks:

Copy code
from adapters import AutoAdapterModel

# Load the base model and RabbitRedux adapter
model = AutoAdapterModel.from_pretrained("replit/replit-code-v1_5-3b")
model.load_adapter("Canstralian/RabbitRedux", set_active=True)

# Use the model for classification tasks
predictions = model.predict(["Your code snippet here"])
Example Use Case
This model is perfect for tasks such as:

Classifying code snippets related to penetration testing.
Analyzing code related to security vulnerabilities or exploits.
Automatically categorizing code used in ransomware analysis.
Example:
python
Copy code
code_snippet = """import os
# Command to start a reverse shell
os.system('nc -lvp 4444')"""

predictions = model.predict([code_snippet])
print(predictions)  # Output: ['Reverse Shell', 'Penetration Testing']

Installation

Install dependencies:

pip install transformers
pip install git+https://github.com/canstralian/RabbitRedux.git

Load the model:

from adapters import AutoAdapterModel

model = AutoAdapterModel.from_pretrained("replit/replit-code-v1_5-3b")
model.load_adapter("Canstralian/RabbitRedux", set_active=True)

Evaluation Metrics

RabbitRedux has been evaluated on code classification tasks using the following metrics:

• Precision: 0.95
• Recall: 0.92
• F1 Score: 0.93

These metrics indicate high accuracy in classifying code in the cybersecurity domain.

Contributions

RabbitRedux is an open-source project, and contributions are welcome! You can contribute by forking the repository, submitting pull requests, or sharing ideas for improvement.

GitHub Repository: RabbitRedux on GitHub

Issues & Feedback: Feel free to open issues or submit feedback directly through the repository.

Citation

If you use RabbitRedux in your work or research, please cite it as follows:

BibTeX:

@misc{canstralian2024rabbitredux,
  author = {Canstralian},
  title = {RabbitRedux: A Model for Code Classification in Cybersecurity},
  year = {2024},
  url = {https://github.com/canstralian/RabbitRedux},
}
APA: Canstralian. (2024). RabbitRedux: A Model for Code Classification in Cybersecurity. Retrieved from https://github.com/canstralian/RabbitRedux

License

RabbitRedux is licensed under the MIT License. See LICENSE for more details.

Contact

For more information or to get in touch with the developers, please visit Canstralian's GitHub or reach out through the repository issues page.