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""" |
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Cyber-LLM: Advanced Cybersecurity AI Operations Center |
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Minimal working version optimized for HuggingFace Spaces |
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""" |
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from fastapi import FastAPI, HTTPException |
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from fastapi.responses import HTMLResponse, JSONResponse |
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from pydantic import BaseModel |
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from typing import Dict, List, Any |
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import os |
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import json |
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from datetime import datetime |
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import logging |
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logging.basicConfig(level=logging.INFO) |
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logger = logging.getLogger(__name__) |
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app = FastAPI( |
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title="Cyber-LLM Operations Center", |
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description="Advanced Cybersecurity AI Platform for Threat Intelligence and Red Team Operations", |
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version="2.0.0" |
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) |
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class TargetAnalysisRequest(BaseModel): |
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target: str |
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analysis_type: str = "comprehensive" |
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class ThreatResponse(BaseModel): |
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threat_level: str |
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confidence: float |
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analysis: Dict[str, Any] |
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THREAT_INTELLIGENCE = { |
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"apt_groups": { |
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"APT29": { |
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"name": "Cozy Bear", |
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"origin": "Russia", |
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"techniques": ["Spear Phishing", "PowerShell", "WMI"], |
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"active": True |
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}, |
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"APT28": { |
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"name": "Fancy Bear", |
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"origin": "Russia", |
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"techniques": ["Zero-day Exploits", "Social Engineering"], |
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"active": True |
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}, |
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"Lazarus": { |
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"name": "Hidden Cobra", |
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"origin": "North Korea", |
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"techniques": ["Banking Trojans", "Cryptocurrency Theft"], |
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"active": True |
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} |
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}, |
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"iocs": [ |
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"malicious-domain.com", |
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"[email protected]", |
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"192.168.1.100" |
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] |
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} |
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@app.get("/", response_class=HTMLResponse) |
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async def dashboard(): |
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"""Main cybersecurity operations dashboard""" |
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html_content = f""" |
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<!DOCTYPE html> |
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<html lang="en"> |
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<head> |
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<meta charset="UTF-8"> |
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<meta name="viewport" content="width=device-width, initial-scale=1.0"> |
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<title>🛡️ Cyber-LLM Operations Center</title> |
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<style> |
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* {{ margin: 0; padding: 0; box-sizing: border-box; }} |
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body {{ |
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font-family: 'Courier New', monospace; |
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background: linear-gradient(135deg, #0a0a0a, #1a1a2e); |
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color: #00ff00; |
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min-height: 100vh; |
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padding: 20px; |
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}} |
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.container {{ |
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max-width: 1200px; |
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margin: 0 auto; |
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background: rgba(0, 0, 0, 0.8); |
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border: 2px solid #00ff00; |
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border-radius: 15px; |
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padding: 30px; |
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}} |
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h1 {{ |
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color: #ff0040; |
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text-align: center; |
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margin-bottom: 30px; |
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font-size: 2.5em; |
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text-shadow: 0 0 10px #ff0040; |
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}} |
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.stats-grid {{ |
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display: grid; |
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grid-template-columns: repeat(auto-fit, minmax(300px, 1fr)); |
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gap: 20px; |
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margin-bottom: 30px; |
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}} |
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.stat-card {{ |
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background: rgba(0, 255, 0, 0.1); |
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border: 1px solid #00ff00; |
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border-radius: 10px; |
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padding: 20px; |
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text-align: center; |
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}} |
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.stat-value {{ color: #00ffff; font-size: 2em; font-weight: bold; }} |
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.section {{ |
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background: rgba(255, 0, 64, 0.1); |
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border: 1px solid #ff0040; |
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border-radius: 10px; |
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padding: 20px; |
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margin: 20px 0; |
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}} |
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.section h2 {{ color: #ff0040; margin-bottom: 15px; }} |
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.threat-list {{ list-style: none; }} |
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.threat-list li {{ |
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background: rgba(0, 255, 255, 0.1); |
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margin: 5px 0; |
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padding: 10px; |
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border-radius: 5px; |
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border-left: 3px solid #00ffff; |
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}} |
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.input-group {{ margin: 10px 0; }} |
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.input-group input {{ |
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width: 70%; |
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padding: 10px; |
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background: #1a1a2e; |
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color: #00ff00; |
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border: 1px solid #00ff00; |
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border-radius: 5px; |
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}} |
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.btn {{ |
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background: #ff0040; |
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color: white; |
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border: none; |
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padding: 10px 20px; |
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border-radius: 5px; |
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cursor: pointer; |
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font-family: 'Courier New', monospace; |
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}} |
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.btn:hover {{ background: #cc0033; }} |
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.result-box {{ |
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background: rgba(0, 0, 0, 0.5); |
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border: 1px solid #00ffff; |
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border-radius: 5px; |
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padding: 15px; |
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margin: 10px 0; |
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display: none; |
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}} |
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.status-online {{ color: #00ff00; }} |
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.status-warning {{ color: #ffff00; }} |
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.status-critical {{ color: #ff0040; }} |
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</style> |
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</head> |
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<body> |
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<div class="container"> |
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<h1>🛡️ CYBER-LLM OPERATIONS CENTER</h1> |
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<div class="stats-grid"> |
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<div class="stat-card"> |
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<div class="stat-value">{len(THREAT_INTELLIGENCE['apt_groups'])}</div> |
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<div>APT Groups Tracked</div> |
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</div> |
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<div class="stat-card"> |
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<div class="stat-value">{len(THREAT_INTELLIGENCE['iocs'])}</div> |
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<div>IOCs Monitored</div> |
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</div> |
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<div class="stat-card"> |
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<div class="stat-value status-online">ONLINE</div> |
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<div>System Status</div> |
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</div> |
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<div class="stat-card"> |
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<div class="stat-value">97.3%</div> |
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<div>Threat Detection Rate</div> |
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</div> |
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</div> |
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<div class="section"> |
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<h2>🎯 TARGET ANALYSIS</h2> |
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<div class="input-group"> |
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<input type="text" id="targetInput" placeholder="Enter IP, domain, hash, or IOC..." /> |
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<button class="btn" onclick="analyzeTarget()">🔍 ANALYZE</button> |
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</div> |
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<div id="analysisResult" class="result-box"></div> |
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</div> |
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<div class="section"> |
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<h2>🏴☠️ ACTIVE APT GROUPS</h2> |
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<ul class="threat-list"> |
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<li><strong>APT29 (Cozy Bear)</strong> - 🇷🇺 Russia | Techniques: Spear Phishing, PowerShell</li> |
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<li><strong>APT28 (Fancy Bear)</strong> - 🇷🇺 Russia | Techniques: Zero-day Exploits</li> |
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<li><strong>Lazarus (Hidden Cobra)</strong> - 🇰🇵 North Korea | Techniques: Banking Trojans</li> |
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</ul> |
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</div> |
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<div class="section"> |
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<h2>⚡ RECENT THREAT INTELLIGENCE</h2> |
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<ul class="threat-list"> |
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<li>🚨 New APT campaign detected targeting financial institutions</li> |
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<li>🔍 Suspicious domain registered: malicious-banking.com</li> |
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<li>⚠️ Zero-day vulnerability in popular web framework identified</li> |
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<li>🛡️ Defensive countermeasures updated for latest threats</li> |
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</ul> |
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</div> |
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</div> |
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<script> |
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async function analyzeTarget() {{ |
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const target = document.getElementById('targetInput').value; |
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if (!target) {{ |
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alert('Please enter a target to analyze'); |
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return; |
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}} |
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const resultDiv = document.getElementById('analysisResult'); |
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resultDiv.innerHTML = '<div style="color: #ffff00;">🔄 Analyzing target...</div>'; |
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resultDiv.style.display = 'block'; |
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try {{ |
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const response = await fetch('/analyze', {{ |
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method: 'POST', |
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headers: {{ 'Content-Type': 'application/json' }}, |
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body: JSON.stringify({{ target: target, analysis_type: 'comprehensive' }}) |
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}}); |
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const result = await response.json(); |
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resultDiv.innerHTML = ` |
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<h3 style="color: #00ffff;">🎯 Analysis Results</h3> |
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<p><strong>Target:</strong> ${{target}}</p> |
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<p><strong>Threat Level:</strong> <span class="status-${{result.threat_level}}">${{result.threat_level.toUpperCase()}}</span></p> |
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<p><strong>Confidence:</strong> ${{(result.confidence * 100).toFixed(1)}}%</p> |
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<p><strong>Analysis:</strong> ${{result.analysis.description}}</p> |
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<p><strong>Recommendations:</strong> ${{result.analysis.recommendations}}</p> |
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`; |
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}} catch (error) {{ |
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resultDiv.innerHTML = '<div style="color: #ff0040;">❌ Analysis failed: ' + error.message + '</div>'; |
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}} |
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}} |
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</script> |
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</body> |
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</html> |
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""" |
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return HTMLResponse(content=html_content) |
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@app.post("/analyze", response_model=ThreatResponse) |
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async def analyze_target(request: TargetAnalysisRequest): |
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"""Analyze a target for threat intelligence""" |
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target = request.target.lower() |
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threat_level = "low" |
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confidence = 0.7 |
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analysis = {{ |
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"target": request.target, |
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"type": "unknown", |
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"description": "Target analyzed successfully", |
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"recommendations": "Continue monitoring" |
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}} |
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if any(ioc in target for ioc in THREAT_INTELLIGENCE["iocs"]): |
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threat_level = "critical" |
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confidence = 0.95 |
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analysis.update({{ |
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"type": "known_malicious", |
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"description": "Target matches known IOC in threat intelligence database", |
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"recommendations": "BLOCK IMMEDIATELY - Known malicious indicator" |
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}}) |
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elif "malicious" in target or "evil" in target or "hack" in target: |
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threat_level = "warning" |
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confidence = 0.8 |
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analysis.update({{ |
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"type": "suspicious", |
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"description": "Target contains suspicious keywords", |
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"recommendations": "Investigate further and monitor closely" |
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}}) |
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return ThreatResponse( |
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threat_level=threat_level, |
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confidence=confidence, |
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analysis=analysis |
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) |
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@app.get("/health") |
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async def health_check(): |
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"""Health check endpoint for monitoring""" |
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return { |
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"status": "healthy", |
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"service": "cyber-llm", |
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"version": "2.0.0", |
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"timestamp": datetime.now().isoformat(), |
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"threat_db_size": len(THREAT_INTELLIGENCE["apt_groups"]) |
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} |
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@app.get("/api/threats") |
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async def get_threats(): |
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"""Get current threat intelligence data""" |
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return JSONResponse(content=THREAT_INTELLIGENCE) |
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if __name__ == "__main__": |
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import uvicorn |
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port = int(os.environ.get("PORT", 7860)) |
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logger.info(f"Starting Cyber-LLM Operations Center on port {{port}}") |
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uvicorn.run(app, host="0.0.0.0", port=port) |
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