File size: 13,490 Bytes
a5fb800
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
import gradio as gr
import torch
from transformers import AutoTokenizer, AutoModelForSequenceClassification
import numpy as np
import json
import re
import time
from datetime import datetime
import plotly.graph_objects as go
import plotly.express as px
from plotly.subplots import make_subplots

# Initialize SecBERT model
MODEL_NAME = "jackaduma/SecBERT"
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
model = AutoModelForSequenceClassification.from_pretrained(MODEL_NAME)

# Threat patterns and keywords
THREAT_PATTERNS = {
    "malware": ["trojan", "virus", "worm", "ransomware", "backdoor", "rootkit", "botnet", "keylogger"],
    "phishing": ["click here", "urgent action", "verify account", "suspended", "limited time", "act now"],
    "social_engineering": ["confidential", "insider", "exclusive", "secret", "don't tell", "between us"],
    "data_breach": ["leaked", "exposed", "unauthorized access", "data dump", "credentials", "database"],
    "network_attack": ["ddos", "injection", "exploit", "payload", "shell", "reverse", "buffer overflow"],
    "apt": ["advanced persistent", "nation state", "targeted", "spear phishing", "zero day", "lateral movement"]
}

DEMO_EXAMPLES = [
    "Urgent: Your account has been suspended! Click this link immediately to verify your identity and restore access.",
    "Our new trojan variant uses advanced persistence mechanisms and lateral movement techniques to maintain access.",
    "The APT group deployed custom malware with zero-day exploits targeting financial institutions.",
    "Database containing 2.3 million user credentials was found exposed on an unprotected server.",
    "Hi there! Hope you're having a great day. Looking forward to our meeting tomorrow at 2 PM.",
    "The SQL injection vulnerability allows attackers to dump the entire user database via union select queries."
]

def analyze_threat_patterns(text):
    """Analyze text for cybersecurity threat patterns"""
    threat_scores = {}
    detected_threats = []
    
    text_lower = text.lower()
    
    for threat_type, keywords in THREAT_PATTERNS.items():
        score = 0
        found_keywords = []
        
        for keyword in keywords:
            if keyword in text_lower:
                score += 1
                found_keywords.append(keyword)
        
        if score > 0:
            threat_scores[threat_type] = {
                "score": min(score / len(keywords), 1.0),
                "keywords": found_keywords
            }
            detected_threats.append(threat_type)
    
    return threat_scores, detected_threats

def get_threat_level(threat_scores):
    """Calculate overall threat level"""
    if not threat_scores:
        return "safe", 0.0
    
    max_score = max(threat_info["score"] for threat_info in threat_scores.values())
    
    if max_score >= 0.4:
        return "critical", max_score
    elif max_score >= 0.25:
        return "high", max_score
    elif max_score >= 0.15:
        return "medium", max_score
    else:
        return "low", max_score

def create_threat_visualization(threat_scores, overall_level, overall_score):
    """Create interactive threat visualization"""
    if not threat_scores:
        # Safe visualization
        fig = go.Figure(go.Indicator(
            mode = "gauge+number",
            value = 0,
            domain = {'x': [0, 1], 'y': [0, 1]},
            title = {'text': "🟒 SAFE"},
            gauge = {
                'axis': {'range': [None, 1]},
                'bar': {'color': "green"},
                'steps': [{'range': [0, 1], 'color': "lightgray"}],
                'threshold': {'line': {'color': "red", 'width': 4},
                           'thickness': 0.75, 'value': 0.8}
            }
        ))
    else:
        # Threat level colors
        colors = {
            "safe": "green",
            "low": "yellow", 
            "medium": "orange",
            "high": "red",
            "critical": "darkred"
        }
        
        # Main gauge
        fig = go.Figure(go.Indicator(
            mode = "gauge+number+delta",
            value = overall_score,
            domain = {'x': [0, 1], 'y': [0, 1]},
            title = {'text': f"🚨 {overall_level.upper()} THREAT"},
            delta = {'reference': 0.5},
            gauge = {
                'axis': {'range': [None, 1]},
                'bar': {'color': colors[overall_level]},
                'steps': [
                    {'range': [0, 0.15], 'color': "lightgreen"},
                    {'range': [0.15, 0.25], 'color': "yellow"},
                    {'range': [0.25, 0.4], 'color': "orange"},
                    {'range': [0.4, 1], 'color': "red"}
                ],
                'threshold': {'line': {'color': "black", 'width': 4},
                           'thickness': 0.75, 'value': 0.8}
            }
        ))
    
    fig.update_layout(
        height=300,
        font={'color': "white", 'family': "Arial"},
        paper_bgcolor="rgba(0,0,0,0.1)",
        plot_bgcolor="rgba(0,0,0,0)"
    )
    
    return fig

def create_threat_breakdown(threat_scores):
    """Create threat category breakdown chart"""
    if not threat_scores:
        return None
    
    categories = list(threat_scores.keys())
    scores = [threat_scores[cat]["score"] for cat in categories]
    
    colors = px.colors.qualitative.Set3
    
    fig = go.Figure(data=[
        go.Bar(
            x=categories,
            y=scores,
            marker_color=colors[:len(categories)],
            text=[f"{s:.1%}" for s in scores],
            textposition='auto',
        )
    ])
    
    fig.update_layout(
        title="Threat Categories Detected",
        xaxis_title="Threat Type",
        yaxis_title="Threat Score",
        height=400,
        font={'color': "white"},
        paper_bgcolor="rgba(0,0,0,0.1)",
        plot_bgcolor="rgba(0,0,0,0)"
    )
    
    return fig

def highlight_threats_in_text(text, threat_scores):
    """Highlight detected threats in the original text"""
    if not threat_scores:
        return text
    
    highlighted_text = text
    colors = ["#ff6b6b", "#4ecdc4", "#45b7d1", "#96ceb4", "#ffeaa7", "#dda0dd"]
    
    color_idx = 0
    for threat_type, threat_info in threat_scores.items():
        color = colors[color_idx % len(colors)]
        for keyword in threat_info["keywords"]:
            pattern = re.compile(re.escape(keyword), re.IGNORECASE)
            highlighted_text = pattern.sub(
                f'<mark style="background-color: {color}; padding: 2px 4px; border-radius: 3px; font-weight: bold;">{keyword}</mark>',
                highlighted_text
            )
        color_idx += 1
    
    return highlighted_text

def analyze_cybersecurity_threat(text, progress=gr.Progress()):
    """Main threat analysis function"""
    progress(0, desc="Initializing analysis...")
    time.sleep(0.5)
    
    progress(0.2, desc="Scanning for threat patterns...")
    threat_scores, detected_threats = analyze_threat_patterns(text)
    time.sleep(0.3)
    
    progress(0.5, desc="Calculating threat levels...")
    overall_level, overall_score = get_threat_level(threat_scores)
    time.sleep(0.3)
    
    progress(0.7, desc="Generating visualizations...")
    gauge_chart = create_threat_visualization(threat_scores, overall_level, overall_score)
    breakdown_chart = create_threat_breakdown(threat_scores)
    time.sleep(0.3)
    
    progress(0.9, desc="Highlighting threats in text...")
    highlighted_text = highlight_threats_in_text(text, threat_scores)
    
    # Generate detailed analysis
    analysis_report = generate_analysis_report(threat_scores, overall_level, overall_score, detected_threats)
    
    progress(1.0, desc="Analysis complete!")
    
    return (
        gauge_chart,
        breakdown_chart if breakdown_chart else gr.update(visible=False),
        f"<div style='padding: 15px; background: rgba(0,0,0,0.1); border-radius: 10px; color: white;'>{highlighted_text}</div>",
        analysis_report,
        gr.update(visible=True)
    )

def generate_analysis_report(threat_scores, overall_level, overall_score, detected_threats):
    """Generate detailed threat analysis report"""
    timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
    
    report = f"""
    ## πŸ” Cybersecurity Threat Analysis Report
    **Timestamp:** {timestamp}
    **Overall Threat Level:** {overall_level.upper()} ({overall_score:.1%})
    
    ### πŸ“Š Summary
    """
    
    if not threat_scores:
        report += """
        βœ… **No cybersecurity threats detected!**
        
        The analyzed text appears to be safe and doesn't contain indicators of:
        - Malware or malicious software
        - Phishing attempts
        - Social engineering tactics
        - Data breach indicators
        - Network attack patterns
        - Advanced Persistent Threat (APT) activities
        """
    else:
        report += f"""
        ⚠️ **{len(detected_threats)} threat categories detected:**
        
        """
        
        for threat_type, threat_info in threat_scores.items():
            score_percent = threat_info["score"] * 100
            keywords = ", ".join(f"`{kw}`" for kw in threat_info["keywords"])
            
            report += f"""
        **{threat_type.upper()}** - {score_percent:.1f}% confidence
        - Detected keywords: {keywords}
        
        """
        
        report += """
        ### πŸ›‘οΈ Recommendations
        
        """
        
        if overall_level == "critical":
            report += "🚨 **IMMEDIATE ACTION REQUIRED** - This content shows strong indicators of cybersecurity threats"
        elif overall_level == "high":
            report += "⚠️ **HIGH PRIORITY** - Review and investigate this content immediately"
        elif overall_level == "medium":
            report += "πŸ”Ά **MODERATE CONCERN** - Monitor and verify the source of this content"
        else:
            report += "πŸ’‘ **LOW PRIORITY** - Minor indicators detected, routine monitoring recommended"
    
    return report

# Custom CSS for the interface
custom_css = """
.gradio-container {
    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%) !important;
    color: white;
}

.gr-button {
    background: linear-gradient(45deg, #FF6B6B, #4ECDC4) !important;
    border: none !important;
    color: white !important;
    font-weight: bold !important;
    transition: all 0.3s ease !important;
}

.gr-button:hover {
    transform: translateY(-2px) !important;
    box-shadow: 0 5px 15px rgba(0,0,0,0.3) !important;
}

.gr-textbox textarea {
    background: rgba(255,255,255,0.1) !important;
    border: 2px solid rgba(255,255,255,0.3) !important;
    color: white !important;
}

.gr-markdown {
    color: white !important;
}

.threat-highlight {
    animation: pulse 2s infinite;
}

@keyframes pulse {
    0% { opacity: 1; }
    50% { opacity: 0.7; }
    100% { opacity: 1; }
}
"""

# Build the Gradio interface
with gr.Blocks(css=custom_css, title="🚨 Cyber Threat Radar") as demo:
    gr.Markdown("""
    # 🚨 Cyber Threat Radar Dashboard
    ### Powered by SecBERT - Real-time Cybersecurity Threat Detection
    
    **Upload any text and watch our AI detect hidden cybersecurity threats in real-time!**
    
    Try pasting emails, code snippets, news articles, or any suspicious content. Our advanced AI will analyze it for:
    🦠 Malware indicators β€’ 🎣 Phishing attempts β€’ πŸ‘₯ Social engineering β€’ πŸ’Ύ Data breaches β€’ 🌐 Network attacks β€’ 🎯 APT activities
    """)
    
    with gr.Row():
        with gr.Column(scale=2):
            input_text = gr.Textbox(
                label="πŸ“ Enter text to analyze",
                placeholder="Paste any text here - emails, articles, code, reports...",
                lines=8,
                max_lines=15
            )
            
            with gr.Row():
                analyze_btn = gr.Button("πŸ” Analyze Threats", variant="primary", size="lg")
                clear_btn = gr.Button("πŸ—‘οΈ Clear", variant="secondary")
            
            gr.Markdown("### 🎯 Try These Examples:")
            example_buttons = []
            for i, example in enumerate(DEMO_EXAMPLES):
                btn = gr.Button(f"Example {i+1}: {example[:50]}...", variant="secondary", size="sm")
                btn.click(lambda x=example: x, outputs=input_text)
                example_buttons.append(btn)
    
    with gr.Row():
        with gr.Column():
            threat_gauge = gr.Plot(label="🎯 Threat Level Gauge")
        with gr.Column():
            threat_breakdown = gr.Plot(label="πŸ“Š Threat Categories", visible=False)
    
    with gr.Row():
        highlighted_text = gr.HTML(label="πŸ” Text Analysis (Threats Highlighted)")
    
    with gr.Row():
        analysis_report = gr.Markdown(label="πŸ“‹ Detailed Analysis Report")
    
    results_section = gr.Group(visible=False)
    
    # Event handlers
    analyze_btn.click(
        analyze_cybersecurity_threat,
        inputs=[input_text],
        outputs=[threat_gauge, threat_breakdown, highlighted_text, analysis_report, results_section]
    )
    
    clear_btn.click(
        lambda: ("", None, None, "", gr.update(visible=False)),
        outputs=[input_text, threat_gauge, threat_breakdown, analysis_report, results_section]
    )

if __name__ == "__main__":
    demo.launch(
        share=True,
        show_error=True,
        debug=True,
        server_name="0.0.0.0",
        server_port=7860
    )