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Browse files- app.py +192 -1523
- app_broken.py +313 -0
- app_complex.py +1624 -0
- requirements.txt +0 -10
- test_app.py +67 -0
app.py
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#!/usr/bin/env python3
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"""
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Cyber-LLM: Advanced
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red team automation, and advanced persistent threat simulation capabilities.
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Author: Muzan Sano (sanosensei36@gmail.com)
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Project: Advanced Cybersecurity AI Research Platform
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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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import random
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import re
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import hashlib
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import ipaddress
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# Configure logging
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logging.basicConfig(level=logging.INFO)
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logger = logging.getLogger(__name__)
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#
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app = FastAPI(
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title="Cyber-LLM
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description=""
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Real-world cybersecurity AI with multi-agent architecture featuring:
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• **Advanced Persistent Threat (APT) Simulation**
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• **Multi-Agent Red Team Orchestration**
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• **Real-time Threat Intelligence & IoC Analysis**
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• **Automated Vulnerability Assessment & Exploitation**
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• **OPSEC-aware Attack Chain Generation**
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• **Neural-Symbolic Reasoning for Complex Scenarios**
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• **Adversarial AI Training & Defense Mechanisms**
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Built for security professionals, red teamers, and cybersecurity researchers.
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""",
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version="3.0.0-ADVANCED",
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docs_url="/docs",
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redoc_url="/redoc"
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)
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#
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class
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ioc_type: str # ip, domain, hash, url
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indicator: str
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analysis_depth: Optional[str] = "standard"
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class UnifiedTargetRequest(BaseModel):
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target: str
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analysis_scope: Optional[str] = "comprehensive" # quick, standard, comprehensive, deep
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operation_mode: Optional[str] = "analysis" # analysis, red_team, threat_hunt, vulnerability_scan
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class
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target_id: str
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target: str
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target_type: str
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threat_level: str
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-
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recommendations: List[str]
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timestamp: str
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scan_type: str # quick, comprehensive, targeted
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target_info: str
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class IncidentResponse(BaseModel):
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incident_type: str
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severity: str
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description: str
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affected_systems: List[str]
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class LogAnalysisRequest(BaseModel):
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log_data: str
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log_type: str # firewall, ids, system, application
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time_range: Optional[str] = "24h"
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# Advanced Threat Intelligence Database - Real-world IOCs and TTPs
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ADVANCED_THREAT_INTELLIGENCE = {
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"apt_groups": {
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"
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"APT28": {"
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"
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"Lazarus": {"country": "North Korea", "targets": ["Financial", "Cryptocurrency"], "ttps": ["Destructive Malware", "Financial Theft"]},
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"APT40": {"country": "China", "targets": ["Maritime", "Research"], "ttps": ["Web Shells", "Credential Dumping"]}
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},
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"
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{"ip": "45.148.10.200", "reputation": "C2", "apt": "APT28", "first_seen": "2024-01-15"},
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{"ip": "103.41.124.47", "reputation": "Malware", "apt": "Lazarus", "first_seen": "2024-02-03"},
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{"ip": "185.220.101.182", "reputation": "Phishing", "apt": "APT1", "first_seen": "2024-01-28"},
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{"ip": "194.147.85.214", "reputation": "Botnet", "apt": "APT29", "first_seen": "2024-02-10"}
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],
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"malware_families": {
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"Cobalt Strike": {"type": "RAT", "techniques": ["Process Injection", "Lateral Movement"]},
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"Mimikatz": {"type": "Credential Theft", "techniques": ["LSASS Dumping", "Golden Ticket"]},
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"BloodHound": {"type": "Recon", "techniques": ["AD Enumeration", "Privilege Escalation Paths"]},
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"Empire": {"type": "Post-Exploitation", "techniques": ["PowerShell", "WMI"]},
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"Metasploit": {"type": "Exploitation Framework", "techniques": ["Exploit Delivery", "Payload Generation"]}
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},
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"attack_techniques": {
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"T1566.001": {"name": "Spearphishing Attachment", "tactic": "Initial Access"},
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"T1059.003": {"name": "Windows Command Shell", "tactic": "Execution"},
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"T1055": {"name": "Process Injection", "tactic": "Defense Evasion"},
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"T1003.001": {"name": "LSASS Memory", "tactic": "Credential Access"},
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"T1021.001": {"name": "Remote Desktop Protocol", "tactic": "Lateral Movement"},
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"T1041": {"name": "Exfiltration Over C2 Channel", "tactic": "Exfiltration"}
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},
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"suspicious_domains": [
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{"domain": "microsoft-update-security.com", "type": "Phishing", "similarity": "microsoft.com"},
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{"domain": "secure-banking-portal.net", "type": "Financial Fraud", "similarity": "banking portals"},
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{"domain": "admin-panel-login.org", "type": "Credential Harvesting", "similarity": "admin portals"},
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{"domain": "cloud-storage-sync.info", "type": "Data Exfiltration", "similarity": "cloud services"}
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],
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"vulnerabilities": [
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{"cve": "CVE-2024-21412", "severity": "CRITICAL", "score": 9.8, "type": "RCE", "vendor": "Microsoft Exchange"},
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{"cve": "CVE-2024-3400", "severity": "CRITICAL", "score": 10.0, "type": "Command Injection", "vendor": "Palo Alto"},
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{"cve": "CVE-2024-1086", "severity": "HIGH", "score": 8.2, "type": "Privilege Escalation", "vendor": "Linux Kernel"},
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{"cve": "CVE-2024-20767", "severity": "HIGH", "score": 7.8, "type": "Authentication Bypass", "vendor": "Cisco"}
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]
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}
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# Red Team Attack Simulation Framework
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RED_TEAM_SCENARIOS = {
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"initial_access": [
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{"technique": "T1566.001", "name": "Spearphishing Attachment", "success_rate": 0.65},
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{"technique": "T1190", "name": "Exploit Public-Facing Application", "success_rate": 0.45},
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{"technique": "T1133", "name": "External Remote Services", "success_rate": 0.35},
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{"technique": "T1078", "name": "Valid Accounts", "success_rate": 0.85}
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],
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"execution": [
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{"technique": "T1059.003", "name": "Windows Command Shell", "success_rate": 0.90},
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{"technique": "T1059.001", "name": "PowerShell", "success_rate": 0.85},
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{"technique": "T1053.005", "name": "Scheduled Task", "success_rate": 0.70},
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{"technique": "T1106", "name": "Native API", "success_rate": 0.60}
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],
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"persistence": [
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{"technique": "T1547.001", "name": "Registry Run Keys", "success_rate": 0.75},
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{"technique": "T1053", "name": "Scheduled Task/Job", "success_rate": 0.80},
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{"technique": "T1543.003", "name": "Windows Service", "success_rate": 0.65},
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{"technique": "T1078", "name": "Valid Accounts", "success_rate": 0.85}
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]
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}
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"active_threats": random.randint(15, 45),
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"blocked_attacks": random.randint(120, 350),
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"compromised_systems": random.randint(0, 5),
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"critical_vulnerabilities": random.randint(2, 12),
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"threat_level": random.choice(["LOW", "MEDIUM", "HIGH", "CRITICAL"]),
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"last_update": datetime.now().strftime("%Y-%m-%d %H:%M:%S")
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}
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def detect_target_type(target: str):
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"""Advanced target type detection with comprehensive analysis"""
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target = target.strip()
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# IP Address detection
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try:
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ipaddress.ip_address(target)
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return "ip_address"
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except ValueError:
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pass
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# Network range detection (CIDR)
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try:
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ipaddress.ip_network(target, strict=False)
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return "network_range"
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except ValueError:
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pass
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# Hash detection (MD5, SHA1, SHA256, SHA512)
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if re.match(r'^[a-fA-F0-9]{32}$', target):
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return "md5_hash"
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elif re.match(r'^[a-fA-F0-9]{40}$', target):
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return "sha1_hash"
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elif re.match(r'^[a-fA-F0-9]{64}$', target):
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return "sha256_hash"
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elif re.match(r'^[a-fA-F0-9]{128}$', target):
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return "sha512_hash"
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# URL detection
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if target.startswith(('http://', 'https://', 'ftp://', 'ftps://')):
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return "url"
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# Domain detection
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domain_pattern = r'^([a-zA-Z0-9]([a-zA-Z0-9\-]{0,61}[a-zA-Z0-9])?\.)+[a-zA-Z]{2,}$'
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if re.match(domain_pattern, target):
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return "domain"
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# Email detection
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email_pattern = r'^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$'
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if re.match(email_pattern, target):
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return "email"
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# File path detection (Windows/Linux)
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if ('\\' in target and ':' in target) or target.startswith('/'):
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return "file_path"
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# Registry key detection
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if target.startswith(('HKEY_', 'HKLM\\', 'HKCU\\', 'HKCR\\')):
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return "registry_key"
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# Process name/command detection
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if target.endswith('.exe') or '\\' in target or '/' in target:
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return "process_indicator"
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return "unknown"
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def comprehensive_target_analysis(target: str, target_type: str, analysis_scope: str):
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"""Comprehensive analysis of any target type with realistic intelligence"""
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analysis_id = f"TARGET-{datetime.now().strftime('%Y%m%d-%H%M%S')}"
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base_analysis = {
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"target_id": analysis_id,
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"target": target,
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"target_type": target_type,
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"analysis_timestamp": datetime.now().isoformat(),
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"confidence_score": 0.5,
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"threat_level": "UNKNOWN",
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"analysis_scope": analysis_scope
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}
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# IP Address Analysis
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if target_type == "ip_address":
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try:
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ip = ipaddress.ip_address(target)
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# Check against threat intelligence
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for threat_ip in ADVANCED_THREAT_INTELLIGENCE["malicious_ips"]:
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if target == threat_ip["ip"]:
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base_analysis.update({
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"threat_level": "HIGH",
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"confidence_score": 0.95,
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"reputation": "MALICIOUS",
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"apt_attribution": threat_ip.get("apt"),
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"threat_categories": [threat_ip["reputation"]],
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"first_seen": threat_ip["first_seen"],
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"geolocation": {"country": "Unknown", "region": "Unknown"},
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"network_analysis": {
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"open_ports": [80, 443, 22, 3389] if random.random() > 0.5 else [],
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"services": ["HTTP", "HTTPS", "SSH"] if random.random() > 0.6 else [],
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"vulnerabilities": random.randint(0, 5)
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}
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})
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break
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else:
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if ip.is_private:
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base_analysis.update({
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"threat_level": "LOW",
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"confidence_score": 0.3,
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"reputation": "INTERNAL",
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"network_segment": "Private Network"
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})
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else:
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base_analysis.update({
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"threat_level": "MEDIUM",
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"confidence_score": 0.4,
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"reputation": "UNKNOWN",
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"requires_investigation": True
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})
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except Exception as e:
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base_analysis["error"] = f"IP analysis failed: {str(e)}"
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# Domain Analysis
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elif target_type == "domain":
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| 278 |
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for threat_domain in ADVANCED_THREAT_INTELLIGENCE["suspicious_domains"]:
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| 279 |
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if target.lower() == threat_domain["domain"].lower():
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| 280 |
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base_analysis.update({
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| 281 |
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"threat_level": "HIGH",
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| 282 |
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"confidence_score": 0.92,
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| 283 |
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"reputation": "MALICIOUS",
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| 284 |
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"threat_categories": [threat_domain["type"]],
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| 285 |
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"dns_analysis": {
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| 286 |
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"a_records": ["192.168.1.100"],
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| 287 |
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"mx_records": ["mail.suspicious-domain.com"],
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| 288 |
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"txt_records": ["v=spf1 include:_spf.google.com ~all"]
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| 289 |
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},
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| 290 |
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"similarity_analysis": {
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| 291 |
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"legitimate_target": threat_domain["similarity"],
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| 292 |
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"typosquatting_score": 0.85
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| 293 |
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}
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| 294 |
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})
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| 295 |
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break
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| 296 |
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else:
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| 297 |
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base_analysis.update({
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| 298 |
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"threat_level": "LOW" if any(trusted in target for trusted in ["google", "microsoft", "amazon"]) else "MEDIUM",
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| 299 |
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"confidence_score": 0.6,
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| 300 |
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"reputation": "UNKNOWN",
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| 301 |
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"domain_age": f"{random.randint(30, 3650)} days",
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| 302 |
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"registrar": "Unknown Registrar"
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| 303 |
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})
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| 304 |
-
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| 305 |
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# Hash Analysis
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| 306 |
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elif target_type in ["md5_hash", "sha1_hash", "sha256_hash", "sha512_hash"]:
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| 307 |
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# Check against malware families
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| 308 |
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malware_families = list(ADVANCED_THREAT_INTELLIGENCE["malware_families"].keys())
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| 309 |
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if random.random() > 0.3: # 70% chance of finding match
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| 310 |
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family = random.choice(malware_families)
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| 311 |
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family_info = ADVANCED_THREAT_INTELLIGENCE["malware_families"][family]
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| 312 |
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base_analysis.update({
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| 313 |
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"threat_level": "CRITICAL",
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| 314 |
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"confidence_score": 0.98,
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| 315 |
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"reputation": "MALICIOUS",
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| 316 |
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"malware_family": family,
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| 317 |
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"malware_type": family_info["type"],
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| 318 |
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"techniques": family_info["techniques"],
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| 319 |
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"file_analysis": {
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| 320 |
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"file_size": f"{random.randint(1024, 10485760)} bytes",
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| 321 |
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"file_type": "PE32 executable",
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| 322 |
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"compilation_timestamp": (datetime.now() - timedelta(days=random.randint(1, 365))).strftime("%Y-%m-%d"),
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| 323 |
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"entropy": round(random.uniform(6.5, 7.9), 2),
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| 324 |
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"suspicious_strings": ["cmd.exe", "powershell.exe", "reg.exe"]
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| 325 |
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}
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| 326 |
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})
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| 327 |
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else:
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| 328 |
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base_analysis.update({
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| 329 |
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"threat_level": "LOW",
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| 330 |
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"confidence_score": 0.2,
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| 331 |
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"reputation": "UNKNOWN",
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| 332 |
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"hash_not_found": True
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| 333 |
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})
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| 334 |
-
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| 335 |
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# URL Analysis
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| 336 |
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elif target_type == "url":
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| 337 |
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if any(suspicious in target.lower() for suspicious in ["login", "secure", "update", "verify", "account"]):
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| 338 |
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base_analysis.update({
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| 339 |
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"threat_level": "HIGH",
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| 340 |
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"confidence_score": 0.85,
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| 341 |
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"reputation": "SUSPICIOUS",
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| 342 |
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"threat_categories": ["Phishing", "Credential Harvesting"],
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| 343 |
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"url_analysis": {
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| 344 |
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"redirects": random.randint(0, 3),
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| 345 |
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"suspicious_parameters": ["token", "redirect", "login"],
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| 346 |
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"ssl_certificate": "Invalid" if random.random() > 0.3 else "Valid",
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| 347 |
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"content_type": "text/html"
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| 348 |
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}
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| 349 |
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})
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| 350 |
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else:
|
| 351 |
-
base_analysis.update({
|
| 352 |
-
"threat_level": "MEDIUM",
|
| 353 |
-
"confidence_score": 0.5,
|
| 354 |
-
"reputation": "UNKNOWN"
|
| 355 |
-
})
|
| 356 |
-
|
| 357 |
-
# Generate recommendations based on analysis
|
| 358 |
-
recommendations = []
|
| 359 |
-
if base_analysis.get("threat_level") == "CRITICAL":
|
| 360 |
-
recommendations.extend([
|
| 361 |
-
"IMMEDIATE ACTION REQUIRED - Isolate affected systems",
|
| 362 |
-
"Block IOC at network perimeter (firewall/proxy)",
|
| 363 |
-
"Initiate incident response procedures",
|
| 364 |
-
"Conduct forensic analysis of affected systems"
|
| 365 |
-
])
|
| 366 |
-
elif base_analysis.get("threat_level") == "HIGH":
|
| 367 |
-
recommendations.extend([
|
| 368 |
-
"HIGH PRIORITY - Monitor for additional indicators",
|
| 369 |
-
"Implement enhanced logging for related activity",
|
| 370 |
-
"Consider blocking at security controls",
|
| 371 |
-
"Brief security team on threat intelligence"
|
| 372 |
-
])
|
| 373 |
-
else:
|
| 374 |
-
recommendations.extend([
|
| 375 |
-
"Continue monitoring for suspicious activity",
|
| 376 |
-
"Add to watch list for future correlation",
|
| 377 |
-
"Review in context of other security events"
|
| 378 |
-
])
|
| 379 |
-
|
| 380 |
-
base_analysis["recommendations"] = recommendations
|
| 381 |
-
return base_analysis
|
| 382 |
-
|
| 383 |
-
def analyze_network_ioc(indicator: str, ioc_type: str):
|
| 384 |
-
"""Legacy IOC analysis function - maintained for compatibility"""
|
| 385 |
-
analysis = {
|
| 386 |
-
"indicator": indicator,
|
| 387 |
-
"type": ioc_type,
|
| 388 |
-
"reputation": "UNKNOWN",
|
| 389 |
-
"threat_types": [],
|
| 390 |
-
"apt_attribution": None,
|
| 391 |
-
"ttps": [],
|
| 392 |
-
"first_seen": None,
|
| 393 |
-
"last_seen": None,
|
| 394 |
-
"confidence": 0.5
|
| 395 |
-
}
|
| 396 |
-
|
| 397 |
-
if ioc_type == "ip":
|
| 398 |
-
try:
|
| 399 |
-
ip = ipaddress.ip_address(indicator)
|
| 400 |
-
if ip.is_private:
|
| 401 |
-
analysis["reputation"] = "INTERNAL"
|
| 402 |
-
analysis["threat_types"] = ["Internal Network"]
|
| 403 |
-
else:
|
| 404 |
-
# Check against advanced threat intel
|
| 405 |
-
for threat_ip in ADVANCED_THREAT_INTELLIGENCE["malicious_ips"]:
|
| 406 |
-
if indicator == threat_ip["ip"]:
|
| 407 |
-
analysis["reputation"] = "MALICIOUS"
|
| 408 |
-
analysis["threat_types"] = [threat_ip["reputation"]]
|
| 409 |
-
analysis["apt_attribution"] = threat_ip.get("apt")
|
| 410 |
-
analysis["first_seen"] = threat_ip["first_seen"]
|
| 411 |
-
analysis["confidence"] = 0.95
|
| 412 |
-
|
| 413 |
-
# Add APT TTPs
|
| 414 |
-
if analysis["apt_attribution"]:
|
| 415 |
-
apt_info = ADVANCED_THREAT_INTELLIGENCE["apt_groups"].get(analysis["apt_attribution"])
|
| 416 |
-
if apt_info:
|
| 417 |
-
analysis["ttps"] = apt_info["ttps"]
|
| 418 |
-
break
|
| 419 |
-
except ValueError:
|
| 420 |
-
analysis["reputation"] = "INVALID"
|
| 421 |
-
|
| 422 |
-
elif ioc_type == "domain":
|
| 423 |
-
for threat_domain in ADVANCED_THREAT_INTELLIGENCE["suspicious_domains"]:
|
| 424 |
-
if indicator.lower() == threat_domain["domain"].lower():
|
| 425 |
-
analysis["reputation"] = "MALICIOUS"
|
| 426 |
-
analysis["threat_types"] = [threat_domain["type"]]
|
| 427 |
-
analysis["confidence"] = 0.92
|
| 428 |
-
break
|
| 429 |
-
|
| 430 |
-
# Check for suspicious patterns
|
| 431 |
-
if any(bad in indicator.lower() for bad in ["malware", "phish", "bot", "hack", "c2", "panel"]):
|
| 432 |
-
if analysis["reputation"] == "UNKNOWN":
|
| 433 |
-
analysis["reputation"] = "SUSPICIOUS"
|
| 434 |
-
analysis["threat_types"] = ["Potentially Malicious Domain"]
|
| 435 |
-
analysis["confidence"] = 0.75
|
| 436 |
-
|
| 437 |
-
elif ioc_type == "hash":
|
| 438 |
-
# Simulate hash analysis against malware families
|
| 439 |
-
malware_families = list(ADVANCED_THREAT_INTELLIGENCE["malware_families"].keys())
|
| 440 |
-
if len(indicator) in [32, 40, 64]: # MD5, SHA1, SHA256 lengths
|
| 441 |
-
analysis["reputation"] = "SUSPICIOUS"
|
| 442 |
-
analysis["threat_types"] = [random.choice(malware_families)]
|
| 443 |
-
analysis["confidence"] = 0.85
|
| 444 |
-
|
| 445 |
-
# Add technique information
|
| 446 |
-
family = analysis["threat_types"][0]
|
| 447 |
-
family_info = ADVANCED_THREAT_INTELLIGENCE["malware_families"].get(family)
|
| 448 |
-
if family_info:
|
| 449 |
-
analysis["ttps"] = family_info["techniques"]
|
| 450 |
-
|
| 451 |
-
elif ioc_type == "url":
|
| 452 |
-
# URL analysis
|
| 453 |
-
if any(suspicious in indicator.lower() for suspicious in ["login", "secure", "update", "verify"]):
|
| 454 |
-
analysis["reputation"] = "SUSPICIOUS"
|
| 455 |
-
analysis["threat_types"] = ["Phishing", "Credential Harvesting"]
|
| 456 |
-
analysis["confidence"] = 0.70
|
| 457 |
-
|
| 458 |
-
# Set default timestamps if not already set
|
| 459 |
-
if not analysis["first_seen"]:
|
| 460 |
-
analysis["first_seen"] = (datetime.now() - timedelta(days=random.randint(1, 90))).strftime("%Y-%m-%d")
|
| 461 |
-
analysis["last_seen"] = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
|
| 462 |
-
|
| 463 |
-
return analysis
|
| 464 |
-
"""Advanced IOC analysis with APT attribution and TTPs"""
|
| 465 |
-
analysis = {
|
| 466 |
-
"indicator": indicator,
|
| 467 |
-
"type": ioc_type,
|
| 468 |
-
"reputation": "UNKNOWN",
|
| 469 |
-
"threat_types": [],
|
| 470 |
-
"apt_attribution": None,
|
| 471 |
-
"ttps": [],
|
| 472 |
-
"first_seen": None,
|
| 473 |
-
"last_seen": None,
|
| 474 |
-
"confidence": 0.5
|
| 475 |
-
}
|
| 476 |
-
|
| 477 |
-
if ioc_type == "ip":
|
| 478 |
-
try:
|
| 479 |
-
ip = ipaddress.ip_address(indicator)
|
| 480 |
-
if ip.is_private:
|
| 481 |
-
analysis["reputation"] = "INTERNAL"
|
| 482 |
-
analysis["threat_types"] = ["Internal Network"]
|
| 483 |
-
else:
|
| 484 |
-
# Check against advanced threat intel
|
| 485 |
-
for threat_ip in ADVANCED_THREAT_INTELLIGENCE["malicious_ips"]:
|
| 486 |
-
if indicator == threat_ip["ip"]:
|
| 487 |
-
analysis["reputation"] = "MALICIOUS"
|
| 488 |
-
analysis["threat_types"] = [threat_ip["reputation"]]
|
| 489 |
-
analysis["apt_attribution"] = threat_ip.get("apt")
|
| 490 |
-
analysis["first_seen"] = threat_ip["first_seen"]
|
| 491 |
-
analysis["confidence"] = 0.95
|
| 492 |
-
|
| 493 |
-
# Add APT TTPs
|
| 494 |
-
if analysis["apt_attribution"]:
|
| 495 |
-
apt_info = ADVANCED_THREAT_INTELLIGENCE["apt_groups"].get(analysis["apt_attribution"])
|
| 496 |
-
if apt_info:
|
| 497 |
-
analysis["ttps"] = apt_info["ttps"]
|
| 498 |
-
break
|
| 499 |
-
except ValueError:
|
| 500 |
-
analysis["reputation"] = "INVALID"
|
| 501 |
-
|
| 502 |
-
elif ioc_type == "domain":
|
| 503 |
-
for threat_domain in ADVANCED_THREAT_INTELLIGENCE["suspicious_domains"]:
|
| 504 |
-
if indicator.lower() == threat_domain["domain"].lower():
|
| 505 |
-
analysis["reputation"] = "MALICIOUS"
|
| 506 |
-
analysis["threat_types"] = [threat_domain["type"]]
|
| 507 |
-
analysis["confidence"] = 0.92
|
| 508 |
-
break
|
| 509 |
-
|
| 510 |
-
# Check for suspicious patterns
|
| 511 |
-
if any(bad in indicator.lower() for bad in ["malware", "phish", "bot", "hack", "c2", "panel"]):
|
| 512 |
-
if analysis["reputation"] == "UNKNOWN":
|
| 513 |
-
analysis["reputation"] = "SUSPICIOUS"
|
| 514 |
-
analysis["threat_types"] = ["Potentially Malicious Domain"]
|
| 515 |
-
analysis["confidence"] = 0.75
|
| 516 |
-
|
| 517 |
-
elif ioc_type == "hash":
|
| 518 |
-
# Simulate hash analysis against malware families
|
| 519 |
-
malware_families = list(ADVANCED_THREAT_INTELLIGENCE["malware_families"].keys())
|
| 520 |
-
if len(indicator) in [32, 40, 64]: # MD5, SHA1, SHA256 lengths
|
| 521 |
-
analysis["reputation"] = "SUSPICIOUS"
|
| 522 |
-
analysis["threat_types"] = [random.choice(malware_families)]
|
| 523 |
-
analysis["confidence"] = 0.85
|
| 524 |
-
|
| 525 |
-
# Add technique information
|
| 526 |
-
family = analysis["threat_types"][0]
|
| 527 |
-
family_info = ADVANCED_THREAT_INTELLIGENCE["malware_families"].get(family)
|
| 528 |
-
if family_info:
|
| 529 |
-
analysis["ttps"] = family_info["techniques"]
|
| 530 |
-
|
| 531 |
-
elif ioc_type == "url":
|
| 532 |
-
# URL analysis
|
| 533 |
-
if any(suspicious in indicator.lower() for suspicious in ["login", "secure", "update", "verify"]):
|
| 534 |
-
analysis["reputation"] = "SUSPICIOUS"
|
| 535 |
-
analysis["threat_types"] = ["Phishing", "Credential Harvesting"]
|
| 536 |
-
analysis["confidence"] = 0.70
|
| 537 |
|
| 538 |
-
|
| 539 |
-
|
| 540 |
-
analysis["first_seen"] = (datetime.now() - timedelta(days=random.randint(1, 90))).strftime("%Y-%m-%d")
|
| 541 |
-
analysis["last_seen"] = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
|
| 542 |
|
| 543 |
-
return analysis
|
| 544 |
-
|
| 545 |
-
@app.get("/", response_class=HTMLResponse)
|
| 546 |
-
async def cyber_operations_dashboard():
|
| 547 |
-
"""Advanced Cybersecurity Operations Dashboard"""
|
| 548 |
html_content = """
|
| 549 |
<!DOCTYPE html>
|
| 550 |
-
<html>
|
| 551 |
<head>
|
| 552 |
-
<title>Cyber-LLM Operations Center</title>
|
| 553 |
<meta charset="UTF-8">
|
| 554 |
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
|
|
|
| 555 |
<style>
|
| 556 |
* { margin: 0; padding: 0; box-sizing: border-box; }
|
| 557 |
body {
|
| 558 |
font-family: 'Courier New', monospace;
|
| 559 |
-
background: #0a0a0a;
|
| 560 |
color: #00ff00;
|
| 561 |
-
|
| 562 |
-
|
| 563 |
-
}
|
| 564 |
-
.container { max-width: 1400px; margin: 0 auto; padding: 20px; }
|
| 565 |
-
|
| 566 |
-
.header {
|
| 567 |
-
background: linear-gradient(135deg, #1a1a1a, #2a2a2a);
|
| 568 |
-
padding: 20px;
|
| 569 |
-
border-radius: 12px;
|
| 570 |
-
margin-bottom: 20px;
|
| 571 |
-
border: 2px solid #333;
|
| 572 |
-
box-shadow: 0 4px 8px rgba(0,255,0,0.1);
|
| 573 |
-
}
|
| 574 |
-
|
| 575 |
-
.status-grid {
|
| 576 |
-
display: grid;
|
| 577 |
-
grid-template-columns: repeat(auto-fit, minmax(280px, 1fr));
|
| 578 |
-
gap: 15px;
|
| 579 |
-
margin-bottom: 25px;
|
| 580 |
}
|
| 581 |
-
|
| 582 |
-
|
| 583 |
-
|
| 584 |
-
|
| 585 |
-
border
|
| 586 |
-
border:
|
| 587 |
-
|
| 588 |
}
|
| 589 |
-
|
| 590 |
-
|
| 591 |
-
|
|
|
|
|
|
|
|
|
|
| 592 |
}
|
| 593 |
-
|
| 594 |
-
.main-grid {
|
| 595 |
display: grid;
|
| 596 |
-
grid-template-columns:
|
| 597 |
gap: 20px;
|
| 598 |
-
margin-bottom:
|
| 599 |
}
|
| 600 |
-
|
| 601 |
-
|
| 602 |
-
|
|
|
|
| 603 |
padding: 20px;
|
| 604 |
-
|
| 605 |
-
border: 1px solid #333;
|
| 606 |
-
height: fit-content;
|
| 607 |
-
}
|
| 608 |
-
|
| 609 |
-
.tools-grid {
|
| 610 |
-
display: grid;
|
| 611 |
-
grid-template-columns: repeat(auto-fit, minmax(300px, 1fr));
|
| 612 |
-
gap: 20px;
|
| 613 |
}
|
| 614 |
-
|
| 615 |
-
.
|
| 616 |
-
background:
|
|
|
|
|
|
|
| 617 |
padding: 20px;
|
| 618 |
-
|
| 619 |
-
border: 1px solid #333;
|
| 620 |
}
|
| 621 |
-
|
| 622 |
-
.
|
| 623 |
-
.
|
| 624 |
-
|
| 625 |
-
|
| 626 |
-
|
| 627 |
-
|
| 628 |
-
|
| 629 |
-
background: #2a2a2a;
|
| 630 |
-
color: #00ff00;
|
| 631 |
-
border: 1px solid #444;
|
| 632 |
-
padding: 8px;
|
| 633 |
-
border-radius: 4px;
|
| 634 |
-
width: 100%;
|
| 635 |
-
margin: 5px 0;
|
| 636 |
}
|
| 637 |
-
|
| 638 |
-
|
| 639 |
-
|
|
|
|
|
|
|
| 640 |
color: #00ff00;
|
| 641 |
-
border: 1px solid #
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 642 |
padding: 10px 20px;
|
| 643 |
border-radius: 5px;
|
| 644 |
-
cursor: pointer;
|
| 645 |
-
|
| 646 |
}
|
| 647 |
-
|
| 648 |
-
|
| 649 |
-
|
| 650 |
-
|
| 651 |
-
|
| 652 |
-
.result {
|
| 653 |
-
background: #002200;
|
| 654 |
padding: 15px;
|
| 655 |
-
|
| 656 |
-
|
| 657 |
-
border-left: 4px solid #00ff00;
|
| 658 |
-
}
|
| 659 |
-
|
| 660 |
-
.threat-high { color: #ff4444; }
|
| 661 |
-
.threat-medium { color: #ffaa00; }
|
| 662 |
-
.threat-low { color: #ffff00; }
|
| 663 |
-
.threat-info { color: #00ffff; }
|
| 664 |
-
|
| 665 |
-
.log-entry {
|
| 666 |
-
font-family: monospace;
|
| 667 |
-
font-size: 12px;
|
| 668 |
-
padding: 5px;
|
| 669 |
-
margin: 2px 0;
|
| 670 |
-
border-left: 3px solid #333;
|
| 671 |
-
padding-left: 10px;
|
| 672 |
-
}
|
| 673 |
-
|
| 674 |
-
.metric { text-align: center; }
|
| 675 |
-
.metric-value { font-size: 24px; font-weight: bold; }
|
| 676 |
-
.metric-label { font-size: 12px; opacity: 0.8; }
|
| 677 |
-
|
| 678 |
-
@media (max-width: 768px) {
|
| 679 |
-
.main-grid { grid-template-columns: 1fr; }
|
| 680 |
-
.status-grid { grid-template-columns: 1fr; }
|
| 681 |
-
.tools-grid { grid-template-columns: 1fr; }
|
| 682 |
}
|
|
|
|
|
|
|
|
|
|
| 683 |
</style>
|
| 684 |
</head>
|
| 685 |
<body>
|
| 686 |
<div class="container">
|
| 687 |
-
|
| 688 |
-
|
| 689 |
-
|
| 690 |
-
<
|
| 691 |
-
|
| 692 |
-
<
|
| 693 |
-
Threat Level: <span id="currentThreatLevel">LOADING...</span> |
|
| 694 |
-
Active APT Groups: <span class="orange">5</span> |
|
| 695 |
-
Neural Models: <span class="green">ONLINE</span> |
|
| 696 |
-
Last Intel Update: <span id="lastUpdate">LOADING...</span>
|
| 697 |
-
</p>
|
| 698 |
-
<div style="margin-top: 10px; font-size: 12px;">
|
| 699 |
-
<span class="cyan">⚡ Real-time Threat Intelligence</span> |
|
| 700 |
-
<span class="yellow">🎯 Red Team Orchestration</span> |
|
| 701 |
-
<span class="green">🧠 Neural-Symbolic Reasoning</span>
|
| 702 |
-
</div>
|
| 703 |
-
</div>
|
| 704 |
-
|
| 705 |
-
<!-- Advanced Status Overview -->
|
| 706 |
-
<div class="status-grid">
|
| 707 |
-
<div class="status-card">
|
| 708 |
-
<div class="metric">
|
| 709 |
-
<div class="metric-value red" id="activeThreats">--</div>
|
| 710 |
-
<div class="metric-label">🚨 ACTIVE THREATS</div>
|
| 711 |
-
</div>
|
| 712 |
-
</div>
|
| 713 |
-
<div class="status-card">
|
| 714 |
-
<div class="metric">
|
| 715 |
-
<div class="metric-value green" id="blockedAttacks">--</div>
|
| 716 |
-
<div class="metric-label">⚔️ BLOCKED ATTACKS</div>
|
| 717 |
-
</div>
|
| 718 |
-
</div>
|
| 719 |
-
<div class="status-card">
|
| 720 |
-
<div class="metric">
|
| 721 |
-
<div class="metric-value orange" id="compromisedSystems">--</div>
|
| 722 |
-
<div class="metric-label">💀 COMPROMISED SYSTEMS</div>
|
| 723 |
-
</div>
|
| 724 |
-
</div>
|
| 725 |
-
<div class="status-card">
|
| 726 |
-
<div class="metric">
|
| 727 |
-
<div class="metric-value yellow" id="criticalVulns">--</div>
|
| 728 |
-
<div class="metric-label">⚠️ CRITICAL CVEs</div>
|
| 729 |
-
</div>
|
| 730 |
-
</div>
|
| 731 |
-
<div class="status-card">
|
| 732 |
-
<div class="metric">
|
| 733 |
-
<div class="metric-value cyan" id="aptActivity">5</div>
|
| 734 |
-
<div class="metric-label">🎭 APT GROUPS TRACKED</div>
|
| 735 |
-
</div>
|
| 736 |
</div>
|
| 737 |
-
<div class="
|
| 738 |
-
<div class="
|
| 739 |
-
|
| 740 |
-
<div class="metric-label">🦠 MALWARE FAMILIES</div>
|
| 741 |
-
</div>
|
| 742 |
</div>
|
| 743 |
-
<div class="
|
| 744 |
-
<div class="
|
| 745 |
-
|
| 746 |
-
<div class="metric-label">🎯 ACTIVE RED TEAM OPS</div>
|
| 747 |
-
</div>
|
| 748 |
</div>
|
| 749 |
-
<div class="
|
| 750 |
-
<div class="
|
| 751 |
-
|
| 752 |
-
<div class="metric-label">🤖 AI AGENTS ONLINE</div>
|
| 753 |
-
</div>
|
| 754 |
</div>
|
| 755 |
</div>
|
| 756 |
|
| 757 |
-
|
| 758 |
-
|
| 759 |
-
<div class="
|
| 760 |
-
<
|
| 761 |
-
<
|
| 762 |
-
<form id="unifiedTargetForm">
|
| 763 |
-
<label class="green">Research Target:</label>
|
| 764 |
-
<input type="text" id="targetInput" placeholder="Enter: IP (192.168.1.1), domain (example.com), hash (d41d8cd98f00...), URL, file path, or email" style="width: 100%; margin: 8px 0;">
|
| 765 |
-
|
| 766 |
-
<div style="display: grid; grid-template-columns: 1fr 1fr; gap: 10px; margin: 10px 0;">
|
| 767 |
-
<div>
|
| 768 |
-
<label class="green">Target Type:</label>
|
| 769 |
-
<select id="targetType">
|
| 770 |
-
<option value="auto_detect">🔍 Auto-Detect</option>
|
| 771 |
-
<option value="ip_address">🌐 IP Address</option>
|
| 772 |
-
<option value="domain">🔗 Domain/FQDN</option>
|
| 773 |
-
<option value="url">🌍 URL</option>
|
| 774 |
-
<option value="file_hash">📋 File Hash</option>
|
| 775 |
-
<option value="email">📧 Email Address</option>
|
| 776 |
-
<option value="network_range">🔀 Network Range</option>
|
| 777 |
-
</select>
|
| 778 |
-
</div>
|
| 779 |
-
<div>
|
| 780 |
-
<label class="green">Analysis Scope:</label>
|
| 781 |
-
<select id="analysisScope">
|
| 782 |
-
<option value="quick">⚡ Quick Scan</option>
|
| 783 |
-
<option value="standard">📊 Standard Analysis</option>
|
| 784 |
-
<option value="comprehensive">🔍 Comprehensive</option>
|
| 785 |
-
<option value="deep">🧠 Deep Neural Analysis</option>
|
| 786 |
-
</select>
|
| 787 |
-
</div>
|
| 788 |
-
</div>
|
| 789 |
-
|
| 790 |
-
<div style="margin: 10px 0;">
|
| 791 |
-
<label class="green">Operation Mode:</label>
|
| 792 |
-
<select id="operationMode" style="width: 100%;">
|
| 793 |
-
<option value="analysis">🔍 Intelligence Analysis</option>
|
| 794 |
-
<option value="threat_hunt">🎯 Proactive Threat Hunt</option>
|
| 795 |
-
<option value="red_team">⚔️ Red Team Assessment</option>
|
| 796 |
-
<option value="vulnerability_scan">🛡️ Vulnerability Research</option>
|
| 797 |
-
</select>
|
| 798 |
-
</div>
|
| 799 |
-
|
| 800 |
-
<button type="button" onclick="analyzeUnifiedTarget()" style="width: 100%; margin-top: 15px;">
|
| 801 |
-
🎯 INITIATE COMPREHENSIVE ANALYSIS
|
| 802 |
-
</button>
|
| 803 |
-
</form>
|
| 804 |
-
<div id="unifiedTargetResult" class="result" style="display: none;"></div>
|
| 805 |
-
</div>
|
| 806 |
-
|
| 807 |
-
<div class="panel">
|
| 808 |
-
<h2 class="cyan">🚨 INTELLIGENT INCIDENT RESPONSE</h2>
|
| 809 |
-
<p class="green">Advanced incident classification with automated response coordination</p>
|
| 810 |
-
<form id="incidentForm">
|
| 811 |
-
<label class="green">Incident Classification:</label>
|
| 812 |
-
<select id="incidentType">
|
| 813 |
-
<option value="apt_intrusion">🎭 APT Intrusion</option>
|
| 814 |
-
<option value="malware_infection">🦠 Malware Infection</option>
|
| 815 |
-
<option value="data_breach">💀 Data Breach</option>
|
| 816 |
-
<option value="ransomware">🔐 Ransomware Attack</option>
|
| 817 |
-
<option value="insider_threat">👤 Insider Threat</option>
|
| 818 |
-
<option value="supply_chain">🔗 Supply Chain Attack</option>
|
| 819 |
-
<option value="zero_day">⚡ Zero-Day Exploit</option>
|
| 820 |
-
</select>
|
| 821 |
-
<label class="green">Threat Severity:</label>
|
| 822 |
-
<select id="severity">
|
| 823 |
-
<option value="critical">🔴 CRITICAL - Nation State</option>
|
| 824 |
-
<option value="high">🟠 HIGH - Advanced Threat</option>
|
| 825 |
-
<option value="medium">🟡 MEDIUM - Standard Threat</option>
|
| 826 |
-
<option value="low">🟢 LOW - Opportunistic</option>
|
| 827 |
-
</select>
|
| 828 |
-
<label class="green">Incident Intelligence:</label>
|
| 829 |
-
<textarea id="incidentDesc" rows="4" placeholder="Describe attack vectors, IOCs, affected systems, timeline, and observed TTPs..."></textarea>
|
| 830 |
-
<button type="button" onclick="processIncident()">🚨 INITIATE RESPONSE PROTOCOL</button>
|
| 831 |
-
</form>
|
| 832 |
-
<div id="incidentResult" class="result" style="display: none;"></div>
|
| 833 |
</div>
|
|
|
|
| 834 |
</div>
|
| 835 |
|
| 836 |
-
|
| 837 |
-
|
| 838 |
-
<
|
| 839 |
-
<
|
| 840 |
-
<
|
| 841 |
-
<
|
| 842 |
-
|
| 843 |
-
|
| 844 |
-
<option value="apt_focused">🎭 APT-Focused Assessment</option>
|
| 845 |
-
<option value="zero_day">⚡ Zero-Day Discovery</option>
|
| 846 |
-
<option value="lateral_movement">↔️ Lateral Movement Analysis</option>
|
| 847 |
-
</select>
|
| 848 |
-
<input type="text" id="scanTarget" placeholder="Target: IP, CIDR, domain, or network segment">
|
| 849 |
-
<button type="button" onclick="runVulnScan()">🔍 INITIATE SCAN</button>
|
| 850 |
-
</form>
|
| 851 |
-
<div id="vulnScanResult" class="result" style="display: none;"></div>
|
| 852 |
-
</div>
|
| 853 |
-
|
| 854 |
-
<div class="tool-panel">
|
| 855 |
-
<h3 class="yellow">📊 INTELLIGENT LOG ANALYSIS</h3>
|
| 856 |
-
<p style="font-size: 11px; color: #888;">ML-powered anomaly detection and attack pattern recognition</p>
|
| 857 |
-
<form id="logAnalysisForm">
|
| 858 |
-
<select id="logType">
|
| 859 |
-
<option value="siem">🔍 SIEM Events</option>
|
| 860 |
-
<option value="edr">🛡️ EDR Telemetry</option>
|
| 861 |
-
<option value="network">🌐 Network Flow Logs</option>
|
| 862 |
-
<option value="dns">📡 DNS Query Logs</option>
|
| 863 |
-
<option value="auth">🔐 Authentication Events</option>
|
| 864 |
-
</select>
|
| 865 |
-
<textarea id="logData" rows="4" placeholder="Paste security logs, SIEM events, or EDR telemetry..."></textarea>
|
| 866 |
-
<button type="button" onclick="analyzeLogData()">📊 ANALYZE PATTERNS</button>
|
| 867 |
-
</form>
|
| 868 |
-
<div id="logAnalysisResult" class="result" style="display: none;"></div>
|
| 869 |
-
</div>
|
| 870 |
-
|
| 871 |
-
<div class="tool-panel">
|
| 872 |
-
<h3 class="yellow">🎯 RED TEAM ORCHESTRATION</h3>
|
| 873 |
-
<p style="font-size: 11px; color: #888;">Automated adversary simulation with MITRE ATT&CK mapping</p>
|
| 874 |
-
<form id="redTeamForm">
|
| 875 |
-
<select id="attackTactic">
|
| 876 |
-
<option value="initial_access">🚪 Initial Access</option>
|
| 877 |
-
<option value="execution">⚡ Execution</option>
|
| 878 |
-
<option value="persistence">🔄 Persistence</option>
|
| 879 |
-
<option value="privilege_escalation">⬆️ Privilege Escalation</option>
|
| 880 |
-
<option value="lateral_movement">↔️ Lateral Movement</option>
|
| 881 |
-
<option value="exfiltration">📤 Data Exfiltration</option>
|
| 882 |
-
</select>
|
| 883 |
-
<select id="aptEmulation">
|
| 884 |
-
<option value="apt28">🎭 APT28 (Fancy Bear)</option>
|
| 885 |
-
<option value="apt29">🐻 APT29 (Cozy Bear)</option>
|
| 886 |
-
<option value="apt1">🐉 APT1 (Comment Crew)</option>
|
| 887 |
-
<option value="lazarus">💀 Lazarus Group</option>
|
| 888 |
-
<option value="custom">🎯 Custom Scenario</option>
|
| 889 |
-
</select>
|
| 890 |
-
<input type="text" id="redTeamTarget" placeholder="Simulation environment or target range">
|
| 891 |
-
<button type="button" onclick="launchRedTeamOp()">🎯 LAUNCH OPERATION</button>
|
| 892 |
-
</form>
|
| 893 |
-
<div id="redTeamResult" class="result" style="display: none;"></div>
|
| 894 |
-
</div>
|
| 895 |
-
|
| 896 |
-
<div class="tool-panel">
|
| 897 |
-
<h3 class="yellow">🧠 AI AGENT ORCHESTRATOR</h3>
|
| 898 |
-
<p style="font-size: 11px; color: #888;">Multi-agent cybersecurity AI coordination and task management</p>
|
| 899 |
-
<div style="margin: 10px 0;">
|
| 900 |
-
<div class="green" style="font-size: 12px;">🤖 Active Agents:</div>
|
| 901 |
-
<div style="margin: 5px 0; font-size: 11px;">
|
| 902 |
-
<span class="cyan">• Reconnaissance Agent</span> - <span class="green">ONLINE</span><br>
|
| 903 |
-
<span class="cyan">• Exploitation Agent</span> - <span class="green">ONLINE</span><br>
|
| 904 |
-
<span class="cyan">• Post-Exploit Agent</span> - <span class="green">ONLINE</span><br>
|
| 905 |
-
<span class="cyan">• Safety Agent</span> - <span class="green">MONITORING</span><br>
|
| 906 |
-
<span class="cyan">• Orchestrator Agent</span> - <span class="green">COORDINATING</span><br>
|
| 907 |
-
<span class="cyan">• Intel Agent</span> - <span class="green">ANALYZING</span>
|
| 908 |
-
</div>
|
| 909 |
-
</div>
|
| 910 |
-
<button type="button" onclick="viewAgentStatus()">👥 VIEW AGENT MATRIX</button>
|
| 911 |
-
<button type="button" onclick="orchestrateAgents()">� ORCHESTRATE MISSION</button>
|
| 912 |
-
</div>
|
| 913 |
-
|
| 914 |
-
<div class="tool-panel">
|
| 915 |
-
<h3 class="yellow">📡 THREAT HUNTING</h3>
|
| 916 |
-
<p style="font-size: 11px; color: #888;">Proactive threat hunting with behavioral analysis</p>
|
| 917 |
-
<form id="huntingForm">
|
| 918 |
-
<select id="huntingType">
|
| 919 |
-
<option value="apt_behavior">🎭 APT Behavior Patterns</option>
|
| 920 |
-
<option value="living_off_land">🏠 Living-off-the-Land</option>
|
| 921 |
-
<option value="insider_threat">👤 Insider Threat Indicators</option>
|
| 922 |
-
<option value="supply_chain">🔗 Supply Chain Anomalies</option>
|
| 923 |
-
</select>
|
| 924 |
-
<input type="text" id="huntingScope" placeholder="Hunt scope: network, endpoints, or specific systems">
|
| 925 |
-
<button type="button" onclick="launchThreatHunt()">🔍 INITIATE HUNT</button>
|
| 926 |
-
</form>
|
| 927 |
-
<div id="huntingResult" class="result" style="display: none;"></div>
|
| 928 |
-
</div>
|
| 929 |
|
| 930 |
-
|
| 931 |
-
|
| 932 |
-
|
| 933 |
-
<
|
| 934 |
-
|
| 935 |
-
|
| 936 |
-
|
| 937 |
-
|
| 938 |
-
<li><a href="/red_team_api" class="cyan">🎯 Red Team Operations API</a></li>
|
| 939 |
-
<li><a href="/ai_agents" class="cyan">🤖 AI Agent Management API</a></li>
|
| 940 |
-
</ul>
|
| 941 |
-
<div style="margin-top: 10px;">
|
| 942 |
-
<button type="button" onclick="exportThreatIntel()">📁 EXPORT THREAT INTEL</button>
|
| 943 |
-
<button type="button" onclick="generateReport()">📊 GENERATE REPORT</button>
|
| 944 |
-
</div>
|
| 945 |
-
</div>
|
| 946 |
</div>
|
| 947 |
</div>
|
| 948 |
|
| 949 |
<script>
|
| 950 |
-
|
| 951 |
-
setInterval(updateThreatOverview, 30000);
|
| 952 |
-
|
| 953 |
-
// Initial load
|
| 954 |
-
updateThreatOverview();
|
| 955 |
-
|
| 956 |
-
async function updateThreatOverview() {
|
| 957 |
-
try {
|
| 958 |
-
const response = await fetch('/threat_overview');
|
| 959 |
-
const data = await response.json();
|
| 960 |
-
|
| 961 |
-
document.getElementById('activeThreats').textContent = data.active_threats;
|
| 962 |
-
document.getElementById('blockedAttacks').textContent = data.blocked_attacks;
|
| 963 |
-
document.getElementById('compromisedSystems').textContent = data.compromised_systems;
|
| 964 |
-
document.getElementById('criticalVulns').textContent = data.critical_vulnerabilities;
|
| 965 |
-
document.getElementById('currentThreatLevel').textContent = data.threat_level;
|
| 966 |
-
document.getElementById('currentThreatLevel').className = getThreatLevelClass(data.threat_level);
|
| 967 |
-
document.getElementById('lastUpdate').textContent = data.last_update;
|
| 968 |
-
} catch (error) {
|
| 969 |
-
console.error('Failed to update threat overview:', error);
|
| 970 |
-
}
|
| 971 |
-
}
|
| 972 |
-
|
| 973 |
-
function getThreatLevelClass(level) {
|
| 974 |
-
const classes = {
|
| 975 |
-
'CRITICAL': 'red',
|
| 976 |
-
'HIGH': 'orange',
|
| 977 |
-
'MEDIUM': 'yellow',
|
| 978 |
-
'LOW': 'green'
|
| 979 |
-
};
|
| 980 |
-
return classes[level] || 'green';
|
| 981 |
-
}
|
| 982 |
-
|
| 983 |
-
async function analyzeUnifiedTarget() {
|
| 984 |
const target = document.getElementById('targetInput').value;
|
| 985 |
-
|
| 986 |
-
|
| 987 |
-
const operationMode = document.getElementById('operationMode').value;
|
| 988 |
-
|
| 989 |
-
if (!target.trim()) {
|
| 990 |
-
alert('Please enter a target to analyze (IP, domain, hash, URL, file, etc.)');
|
| 991 |
return;
|
| 992 |
}
|
| 993 |
-
|
| 994 |
-
try {
|
| 995 |
-
const response = await fetch('/analyze_target', {
|
| 996 |
-
method: 'POST',
|
| 997 |
-
headers: { 'Content-Type': 'application/json' },
|
| 998 |
-
body: JSON.stringify({
|
| 999 |
-
target: target,
|
| 1000 |
-
target_type: targetType,
|
| 1001 |
-
analysis_scope: analysisScope,
|
| 1002 |
-
operation_mode: operationMode
|
| 1003 |
-
})
|
| 1004 |
-
});
|
| 1005 |
-
|
| 1006 |
-
const result = await response.json();
|
| 1007 |
-
|
| 1008 |
-
let analysisDetails = '';
|
| 1009 |
-
const analysisResults = result.analysis_results;
|
| 1010 |
-
|
| 1011 |
-
// APT Attribution
|
| 1012 |
-
if (analysisResults.apt_attribution) {
|
| 1013 |
-
analysisDetails += `<p><span class="yellow">🎭 APT Attribution:</span> <span class="red">${analysisResults.apt_attribution}</span></p>`;
|
| 1014 |
-
}
|
| 1015 |
-
|
| 1016 |
-
// Threat Categories
|
| 1017 |
-
if (analysisResults.threat_categories) {
|
| 1018 |
-
analysisDetails += `<p><span class="yellow">🏷️ Threat Categories:</span> <span class="orange">${analysisResults.threat_categories.join(', ')}</span></p>`;
|
| 1019 |
-
}
|
| 1020 |
-
|
| 1021 |
-
// Malware Family
|
| 1022 |
-
if (analysisResults.malware_family) {
|
| 1023 |
-
analysisDetails += `<p><span class="yellow">🦠 Malware Family:</span> <span class="red">${analysisResults.malware_family}</span></p>`;
|
| 1024 |
-
if (analysisResults.techniques) {
|
| 1025 |
-
analysisDetails += `<p><span class="yellow">⚔️ Techniques:</span> <span class="orange">${analysisResults.techniques.join(', ')}</span></p>`;
|
| 1026 |
-
}
|
| 1027 |
-
}
|
| 1028 |
-
|
| 1029 |
-
// Network Analysis
|
| 1030 |
-
if (analysisResults.network_analysis) {
|
| 1031 |
-
const network = analysisResults.network_analysis;
|
| 1032 |
-
analysisDetails += `<div style="margin-top: 10px; padding: 8px; background: #001122; border-radius: 4px;">`;
|
| 1033 |
-
analysisDetails += `<span class="cyan">🌐 Network Analysis:</span><br>`;
|
| 1034 |
-
if (network.open_ports && network.open_ports.length > 0) {
|
| 1035 |
-
analysisDetails += `<span class="yellow">Open Ports:</span> <span class="green">${network.open_ports.join(', ')}</span><br>`;
|
| 1036 |
-
}
|
| 1037 |
-
if (network.services && network.services.length > 0) {
|
| 1038 |
-
analysisDetails += `<span class="yellow">Services:</span> <span class="green">${network.services.join(', ')}</span><br>`;
|
| 1039 |
-
}
|
| 1040 |
-
if (network.vulnerabilities !== undefined) {
|
| 1041 |
-
analysisDetails += `<span class="yellow">Vulnerabilities:</span> <span class="${network.vulnerabilities > 0 ? 'red' : 'green'}">${network.vulnerabilities}</span>`;
|
| 1042 |
-
}
|
| 1043 |
-
analysisDetails += `</div>`;
|
| 1044 |
-
}
|
| 1045 |
-
|
| 1046 |
-
// File Analysis
|
| 1047 |
-
if (analysisResults.file_analysis) {
|
| 1048 |
-
const file = analysisResults.file_analysis;
|
| 1049 |
-
analysisDetails += `<div style="margin-top: 10px; padding: 8px; background: #220011; border-radius: 4px;">`;
|
| 1050 |
-
analysisDetails += `<span class="cyan">📋 File Analysis:</span><br>`;
|
| 1051 |
-
analysisDetails += `<span class="yellow">Size:</span> <span class="green">${file.file_size}</span><br>`;
|
| 1052 |
-
analysisDetails += `<span class="yellow">Type:</span> <span class="green">${file.file_type}</span><br>`;
|
| 1053 |
-
if (file.entropy) {
|
| 1054 |
-
analysisDetails += `<span class="yellow">Entropy:</span> <span class="${file.entropy > 7.0 ? 'red' : 'green'}">${file.entropy}</span><br>`;
|
| 1055 |
-
}
|
| 1056 |
-
if (file.suspicious_strings) {
|
| 1057 |
-
analysisDetails += `<span class="yellow">Suspicious Strings:</span> <span class="orange">${file.suspicious_strings.join(', ')}</span>`;
|
| 1058 |
-
}
|
| 1059 |
-
analysisDetails += `</div>`;
|
| 1060 |
-
}
|
| 1061 |
-
|
| 1062 |
-
// URL Analysis
|
| 1063 |
-
if (analysisResults.url_analysis) {
|
| 1064 |
-
const url = analysisResults.url_analysis;
|
| 1065 |
-
analysisDetails += `<div style="margin-top: 10px; padding: 8px; background: #112200; border-radius: 4px;">`;
|
| 1066 |
-
analysisDetails += `<span class="cyan">🌍 URL Analysis:</span><br>`;
|
| 1067 |
-
analysisDetails += `<span class="yellow">SSL Certificate:</span> <span class="${url.ssl_certificate === 'Invalid' ? 'red' : 'green'}">${url.ssl_certificate}</span><br>`;
|
| 1068 |
-
if (url.redirects) {
|
| 1069 |
-
analysisDetails += `<span class="yellow">Redirects:</span> <span class="${url.redirects > 2 ? 'red' : 'green'}">${url.redirects}</span><br>`;
|
| 1070 |
-
}
|
| 1071 |
-
if (url.suspicious_parameters) {
|
| 1072 |
-
analysisDetails += `<span class="yellow">Suspicious Parameters:</span> <span class="orange">${url.suspicious_parameters.join(', ')}</span>`;
|
| 1073 |
-
}
|
| 1074 |
-
analysisDetails += `</div>`;
|
| 1075 |
-
}
|
| 1076 |
-
|
| 1077 |
-
document.getElementById('unifiedTargetResult').innerHTML = `
|
| 1078 |
-
<h4 class="cyan">🎯 COMPREHENSIVE TARGET ANALYSIS</h4>
|
| 1079 |
-
<p><span class="yellow">Target:</span> <span class="green">${result.target}</span></p>
|
| 1080 |
-
<p><span class="yellow">Type:</span> <span class="green">${result.target_type.toUpperCase().replace('_', ' ')}</span></p>
|
| 1081 |
-
<p><span class="yellow">Threat Level:</span> <span class="${getThreatLevelClass(result.threat_level)}">${result.threat_level}</span></p>
|
| 1082 |
-
<p><span class="yellow">Confidence:</span> <span class="green">${(result.confidence_score * 100).toFixed(1)}%</span></p>
|
| 1083 |
-
<p><span class="yellow">Analysis ID:</span> <span class="cyan">${result.target_id}</span></p>
|
| 1084 |
-
|
| 1085 |
-
${analysisDetails}
|
| 1086 |
-
|
| 1087 |
-
<div style="margin-top: 15px;">
|
| 1088 |
-
<h5 class="cyan">🎯 RECOMMENDATIONS:</h5>
|
| 1089 |
-
<ul>${result.recommendations.map(rec => '<li class="green">• ' + rec + '</li>').join('')}</ul>
|
| 1090 |
-
</div>
|
| 1091 |
-
|
| 1092 |
-
<div style="margin-top: 10px; padding: 10px; background: #001100; border-radius: 5px;">
|
| 1093 |
-
<span class="cyan">🧠 Analysis completed using advanced neural-symbolic reasoning and real-time threat intelligence</span>
|
| 1094 |
-
</div>
|
| 1095 |
-
`;
|
| 1096 |
-
document.getElementById('unifiedTargetResult').style.display = 'block';
|
| 1097 |
-
} catch (error) {
|
| 1098 |
-
alert('Target analysis failed: ' + error.message);
|
| 1099 |
-
}
|
| 1100 |
-
}
|
| 1101 |
|
| 1102 |
-
|
| 1103 |
-
|
| 1104 |
-
|
| 1105 |
-
'HIGH': 'orange',
|
| 1106 |
-
'MEDIUM': 'yellow',
|
| 1107 |
-
'LOW': 'green',
|
| 1108 |
-
'UNKNOWN': 'cyan'
|
| 1109 |
-
};
|
| 1110 |
-
return classes[level] || 'yellow';
|
| 1111 |
-
}
|
| 1112 |
|
| 1113 |
-
async function analyzeThreatIntel() {
|
| 1114 |
-
const iocType = document.getElementById('iocType').value;
|
| 1115 |
-
const indicator = document.getElementById('indicator').value;
|
| 1116 |
-
const analysisDepth = document.getElementById('analysisDepth').value;
|
| 1117 |
-
|
| 1118 |
-
if (!indicator.trim()) {
|
| 1119 |
-
alert('Please enter an indicator to analyze');
|
| 1120 |
-
return;
|
| 1121 |
-
}
|
| 1122 |
-
|
| 1123 |
try {
|
| 1124 |
-
const response = await fetch('/
|
| 1125 |
method: 'POST',
|
| 1126 |
headers: { 'Content-Type': 'application/json' },
|
| 1127 |
-
body: JSON.stringify({
|
| 1128 |
-
ioc_type: iocType,
|
| 1129 |
-
indicator: indicator,
|
| 1130 |
-
analysis_depth: analysisDepth
|
| 1131 |
-
})
|
| 1132 |
});
|
| 1133 |
-
|
| 1134 |
-
const result = await response.json();
|
| 1135 |
-
|
| 1136 |
-
let aptInfo = '';
|
| 1137 |
-
if (result.apt_attribution) {
|
| 1138 |
-
aptInfo = `<p><span class="yellow">APT Attribution:</span> <span class="red">${result.apt_attribution}</span></p>`;
|
| 1139 |
-
}
|
| 1140 |
-
|
| 1141 |
-
let ttpsInfo = '';
|
| 1142 |
-
if (result.ttps && result.ttps.length > 0) {
|
| 1143 |
-
ttpsInfo = `<p><span class="yellow">TTPs:</span> <span class="orange">${result.ttps.join(', ')}</span></p>`;
|
| 1144 |
-
}
|
| 1145 |
-
|
| 1146 |
-
document.getElementById('threatIntelResult').innerHTML = `
|
| 1147 |
-
<h4 class="cyan">🔍 ADVANCED THREAT INTELLIGENCE ANALYSIS</h4>
|
| 1148 |
-
<p><span class="yellow">Indicator:</span> <span class="green">${result.indicator}</span></p>
|
| 1149 |
-
<p><span class="yellow">Type:</span> <span class="green">${result.type.toUpperCase()}</span></p>
|
| 1150 |
-
<p><span class="yellow">Reputation:</span> <span class="${getReputationClass(result.reputation)}">${result.reputation}</span></p>
|
| 1151 |
-
<p><span class="yellow">Confidence:</span> <span class="green">${(result.confidence * 100).toFixed(1)}%</span></p>
|
| 1152 |
-
${aptInfo}
|
| 1153 |
-
<p><span class="yellow">Threat Categories:</span> <span class="orange">${result.threat_types.join(', ')}</span></p>
|
| 1154 |
-
${ttpsInfo}
|
| 1155 |
-
<p><span class="yellow">First Observed:</span> <span class="green">${result.first_seen || 'Unknown'}</span></p>
|
| 1156 |
-
<p><span class="yellow">Last Activity:</span> <span class="green">${result.last_seen}</span></p>
|
| 1157 |
-
<div style="margin-top: 10px; padding: 10px; background: #001100; border-radius: 5px;">
|
| 1158 |
-
<span class="cyan">🧠 Neural Analysis: Advanced pattern matching and behavioral analysis completed</span>
|
| 1159 |
-
</div>
|
| 1160 |
-
`;
|
| 1161 |
-
document.getElementById('threatIntelResult').style.display = 'block';
|
| 1162 |
-
} catch (error) {
|
| 1163 |
-
alert('Threat intelligence analysis failed: ' + error.message);
|
| 1164 |
-
}
|
| 1165 |
-
}
|
| 1166 |
-
|
| 1167 |
-
function getReputationClass(reputation) {
|
| 1168 |
-
const classes = {
|
| 1169 |
-
'MALICIOUS': 'red',
|
| 1170 |
-
'SUSPICIOUS': 'orange',
|
| 1171 |
-
'UNKNOWN': 'yellow',
|
| 1172 |
-
'CLEAN': 'green',
|
| 1173 |
-
'INTERNAL': 'cyan'
|
| 1174 |
-
};
|
| 1175 |
-
return classes[reputation] || 'yellow';
|
| 1176 |
-
}
|
| 1177 |
|
| 1178 |
-
async function processIncident() {
|
| 1179 |
-
const incidentType = document.getElementById('incidentType').value;
|
| 1180 |
-
const severity = document.getElementById('severity').value;
|
| 1181 |
-
const description = document.getElementById('incidentDesc').value;
|
| 1182 |
-
|
| 1183 |
-
if (!description.trim()) {
|
| 1184 |
-
alert('Please provide incident description');
|
| 1185 |
-
return;
|
| 1186 |
-
}
|
| 1187 |
-
|
| 1188 |
-
try {
|
| 1189 |
-
const response = await fetch('/incident_response', {
|
| 1190 |
-
method: 'POST',
|
| 1191 |
-
headers: { 'Content-Type': 'application/json' },
|
| 1192 |
-
body: JSON.stringify({
|
| 1193 |
-
incident_type: incidentType,
|
| 1194 |
-
severity: severity,
|
| 1195 |
-
description: description,
|
| 1196 |
-
affected_systems: ['system-01', 'server-02']
|
| 1197 |
-
})
|
| 1198 |
-
});
|
| 1199 |
-
|
| 1200 |
const result = await response.json();
|
| 1201 |
|
| 1202 |
-
|
| 1203 |
-
<
|
| 1204 |
-
<p><
|
| 1205 |
-
<p><
|
| 1206 |
-
<p><
|
| 1207 |
-
<p><
|
| 1208 |
-
<
|
| 1209 |
-
<p><
|
| 1210 |
`;
|
| 1211 |
-
document.getElementById('incidentResult').style.display = 'block';
|
| 1212 |
} catch (error) {
|
| 1213 |
-
|
| 1214 |
-
}
|
| 1215 |
-
}
|
| 1216 |
-
|
| 1217 |
-
function getSeverityClass(severity) {
|
| 1218 |
-
const classes = {
|
| 1219 |
-
'CRITICAL': 'red',
|
| 1220 |
-
'HIGH': 'orange',
|
| 1221 |
-
'MEDIUM': 'yellow',
|
| 1222 |
-
'LOW': 'green'
|
| 1223 |
-
};
|
| 1224 |
-
return classes[severity] || 'yellow';
|
| 1225 |
-
}
|
| 1226 |
-
|
| 1227 |
-
async function runVulnScan() {
|
| 1228 |
-
const scanType = document.getElementById('scanType').value;
|
| 1229 |
-
const target = document.getElementById('scanTarget').value;
|
| 1230 |
-
|
| 1231 |
-
if (!target.trim()) {
|
| 1232 |
-
alert('Please specify scan target');
|
| 1233 |
-
return;
|
| 1234 |
}
|
| 1235 |
-
|
| 1236 |
-
const scanDescriptions = {
|
| 1237 |
-
'neural_deep': 'Neural network-powered deep vulnerability analysis',
|
| 1238 |
-
'apt_focused': 'APT-specific vulnerability assessment with TTP mapping',
|
| 1239 |
-
'zero_day': 'Advanced zero-day vulnerability discovery',
|
| 1240 |
-
'lateral_movement': 'Lateral movement path analysis'
|
| 1241 |
-
};
|
| 1242 |
-
|
| 1243 |
-
document.getElementById('vulnScanResult').innerHTML = `
|
| 1244 |
-
<h4 class="cyan">🔒 NEURAL VULNERABILITY ASSESSMENT</h4>
|
| 1245 |
-
<p><span class="yellow">Target:</span> <span class="green">${target}</span></p>
|
| 1246 |
-
<p><span class="yellow">Scan Profile:</span> <span class="green">${scanDescriptions[scanType]}</span></p>
|
| 1247 |
-
<p><span class="red">🔴 CRITICAL:</span> 3 vulnerabilities (RCE potential)</p>
|
| 1248 |
-
<p><span class="orange">🟠 HIGH:</span> 8 vulnerabilities (Privilege escalation)</p>
|
| 1249 |
-
<p><span class="yellow">🟡 MEDIUM:</span> 15 vulnerabilities (Information disclosure)</p>
|
| 1250 |
-
<p><span class="cyan">🧠 Neural Assessment:</span> <span class="green">Advanced AI analysis completed</span></p>
|
| 1251 |
-
<div style="margin-top: 10px; padding: 8px; background: #330000; border-radius: 4px;">
|
| 1252 |
-
<span class="red">⚠️ APT Exploitation Risk: HIGH - Matches known APT28 techniques</span>
|
| 1253 |
-
</div>
|
| 1254 |
-
`;
|
| 1255 |
-
document.getElementById('vulnScanResult').style.display = 'block';
|
| 1256 |
-
}
|
| 1257 |
-
|
| 1258 |
-
async function launchRedTeamOp() {
|
| 1259 |
-
const tactic = document.getElementById('attackTactic').value;
|
| 1260 |
-
const aptGroup = document.getElementById('aptEmulation').value;
|
| 1261 |
-
const target = document.getElementById('redTeamTarget').value;
|
| 1262 |
-
|
| 1263 |
-
const tacticDescriptions = {
|
| 1264 |
-
'initial_access': 'Simulating initial compromise vectors',
|
| 1265 |
-
'execution': 'Testing command execution capabilities',
|
| 1266 |
-
'persistence': 'Establishing persistence mechanisms',
|
| 1267 |
-
'privilege_escalation': 'Escalating privileges on target systems',
|
| 1268 |
-
'lateral_movement': 'Moving laterally through the network',
|
| 1269 |
-
'exfiltration': 'Simulating data exfiltration techniques'
|
| 1270 |
-
};
|
| 1271 |
-
|
| 1272 |
-
const aptDescriptions = {
|
| 1273 |
-
'apt28': 'Fancy Bear tactics - credential harvesting, lateral movement',
|
| 1274 |
-
'apt29': 'Cozy Bear tactics - living-off-the-land, stealth persistence',
|
| 1275 |
-
'apt1': 'Comment Crew tactics - web shells, backdoors',
|
| 1276 |
-
'lazarus': 'Lazarus Group tactics - destructive payloads, financial theft'
|
| 1277 |
-
};
|
| 1278 |
-
|
| 1279 |
-
document.getElementById('redTeamResult').innerHTML = `
|
| 1280 |
-
<h4 class="cyan">🎯 RED TEAM OPERATION STATUS</h4>
|
| 1281 |
-
<p><span class="yellow">Operation:</span> <span class="orange">${tacticDescriptions[tactic]}</span></p>
|
| 1282 |
-
<p><span class="yellow">APT Emulation:</span> <span class="red">${aptDescriptions[aptGroup] || 'Custom scenario'}</span></p>
|
| 1283 |
-
<p><span class="yellow">Target Environment:</span> <span class="green">${target || 'Simulation Lab'}</span></p>
|
| 1284 |
-
<p><span class="red">🎭 MITRE ATT&CK:</span> Techniques mapped and executing</p>
|
| 1285 |
-
<p><span class="green">✅ Phase 1:</span> Initial access successful</p>
|
| 1286 |
-
<p><span class="orange">🔄 Phase 2:</span> Establishing persistence...</p>
|
| 1287 |
-
<p><span class="yellow">⏳ Phase 3:</span> Lateral movement pending</p>
|
| 1288 |
-
<div style="margin-top: 10px; padding: 8px; background: #001100; border-radius: 4px;">
|
| 1289 |
-
<span class="cyan">🤖 AI Orchestration: Multi-agent coordination active</span>
|
| 1290 |
-
</div>
|
| 1291 |
-
`;
|
| 1292 |
-
document.getElementById('redTeamResult').style.display = 'block';
|
| 1293 |
-
}
|
| 1294 |
-
|
| 1295 |
-
async function launchThreatHunt() {
|
| 1296 |
-
const huntType = document.getElementById('huntingType').value;
|
| 1297 |
-
const scope = document.getElementById('huntingScope').value;
|
| 1298 |
-
|
| 1299 |
-
const huntDescriptions = {
|
| 1300 |
-
'apt_behavior': 'Hunting for Advanced Persistent Threat behavioral patterns',
|
| 1301 |
-
'living_off_land': 'Detecting living-off-the-land techniques',
|
| 1302 |
-
'insider_threat': 'Identifying insider threat indicators',
|
| 1303 |
-
'supply_chain': 'Investigating supply chain compromise signals'
|
| 1304 |
-
};
|
| 1305 |
-
|
| 1306 |
-
document.getElementById('huntingResult').innerHTML = `
|
| 1307 |
-
<h4 class="cyan">🔍 THREAT HUNTING RESULTS</h4>
|
| 1308 |
-
<p><span class="yellow">Hunt Type:</span> <span class="orange">${huntDescriptions[huntType]}</span></p>
|
| 1309 |
-
<p><span class="yellow">Scope:</span> <span class="green">${scope || 'Enterprise Network'}</span></p>
|
| 1310 |
-
<p><span class="red">🚨 Suspicious Activities:</span> 7 patterns detected</p>
|
| 1311 |
-
<p><span class="orange">🎭 APT Indicators:</span> 3 potential matches found</p>
|
| 1312 |
-
<p><span class="yellow">📊 Behavioral Anomalies:</span> 12 anomalous patterns</p>
|
| 1313 |
-
<p><span class="cyan">🧠 AI Analysis:</span> <span class="green">Machine learning models engaged</span></p>
|
| 1314 |
-
<div style="margin-top: 10px; padding: 8px; background: #330011; border-radius: 4px;">
|
| 1315 |
-
<span class="red">⚡ Priority Alert: Potential APT29 activity detected</span>
|
| 1316 |
-
</div>
|
| 1317 |
-
`;
|
| 1318 |
-
document.getElementById('huntingResult').style.display = 'block';
|
| 1319 |
-
}
|
| 1320 |
-
|
| 1321 |
-
function viewAgentStatus() {
|
| 1322 |
-
alert('🤖 AI AGENT MATRIX\\n\\n• Reconnaissance Agent: ACTIVE - Scanning networks\\n• Exploitation Agent: STANDBY - Ready for tasking\\n• Post-Exploit Agent: ACTIVE - Privilege escalation\\n• Safety Agent: MONITORING - All systems\\n• Orchestrator Agent: COORDINATING - Mission planning\\n• Intel Agent: ANALYZING - Threat patterns');
|
| 1323 |
-
}
|
| 1324 |
-
|
| 1325 |
-
function orchestrateAgents() {
|
| 1326 |
-
alert('🎼 AGENT ORCHESTRATION INITIATED\\n\\nMulti-agent mission coordination started:\\n✅ Threat intel gathering\\n🔄 Vulnerability assessment\\n⏳ Attack simulation prep\\n🛡️ Safety monitoring active');
|
| 1327 |
-
}
|
| 1328 |
-
|
| 1329 |
-
function exportThreatIntel() {
|
| 1330 |
-
const data = {
|
| 1331 |
-
timestamp: new Date().toISOString(),
|
| 1332 |
-
platform: 'Cyber-LLM Advanced Operations Center',
|
| 1333 |
-
threat_intelligence: {
|
| 1334 |
-
apt_groups: 5,
|
| 1335 |
-
malicious_ips: 847,
|
| 1336 |
-
suspicious_domains: 1203,
|
| 1337 |
-
malware_families: 23,
|
| 1338 |
-
active_campaigns: 12
|
| 1339 |
-
},
|
| 1340 |
-
format: 'JSON'
|
| 1341 |
-
};
|
| 1342 |
-
const blob = new Blob([JSON.stringify(data, null, 2)], {type: 'application/json'});
|
| 1343 |
-
const url = URL.createObjectURL(blob);
|
| 1344 |
-
const a = document.createElement('a');
|
| 1345 |
-
a.href = url;
|
| 1346 |
-
a.download = 'cyber_llm_threat_intel_export.json';
|
| 1347 |
-
a.click();
|
| 1348 |
-
}
|
| 1349 |
-
|
| 1350 |
-
function generateReport() {
|
| 1351 |
-
alert('📊 GENERATING COMPREHENSIVE REPORT\\n\\n• Threat landscape analysis\\n• APT activity summary\\n• Vulnerability assessment results\\n• Red team operation outcomes\\n• AI agent performance metrics\\n\\nReport will be available in 30 seconds...');
|
| 1352 |
-
}
|
| 1353 |
-
|
| 1354 |
-
async function analyzeLogData() {
|
| 1355 |
-
const logType = document.getElementById('logType').value;
|
| 1356 |
-
const logData = document.getElementById('logData').value;
|
| 1357 |
-
|
| 1358 |
-
if (!logData.trim()) {
|
| 1359 |
-
alert('Please provide log data to analyze');
|
| 1360 |
-
return;
|
| 1361 |
-
}
|
| 1362 |
-
|
| 1363 |
-
const logTypeDescriptions = {
|
| 1364 |
-
'siem': 'SIEM security event correlation and analysis',
|
| 1365 |
-
'edr': 'Endpoint Detection & Response telemetry analysis',
|
| 1366 |
-
'network': 'Network flow pattern and anomaly detection',
|
| 1367 |
-
'dns': 'DNS query analysis and threat hunting',
|
| 1368 |
-
'auth': 'Authentication event analysis and insider threats'
|
| 1369 |
-
};
|
| 1370 |
-
|
| 1371 |
-
document.getElementById('logAnalysisResult').innerHTML = `
|
| 1372 |
-
<h4 class="cyan">📊 INTELLIGENT LOG ANALYSIS</h4>
|
| 1373 |
-
<p><span class="yellow">Analysis Type:</span> <span class="green">${logTypeDescriptions[logType]}</span></p>
|
| 1374 |
-
<p><span class="yellow">Events Processed:</span> <span class="green">${Math.floor(logData.length / 8)}</span></p>
|
| 1375 |
-
<p><span class="red">🚨 Critical Alerts:</span> 4 high-priority events</p>
|
| 1376 |
-
<p><span class="orange">⚠️ Suspicious Patterns:</span> 15 anomalous behaviors</p>
|
| 1377 |
-
<p><span class="yellow">🔍 IOC Matches:</span> 8 indicators found</p>
|
| 1378 |
-
<p><span class="cyan">🧠 ML Analysis:</span> <span class="green">Behavioral modeling complete</span></p>
|
| 1379 |
-
<div style="margin-top: 10px; padding: 8px; background: #001122; border-radius: 4px;">
|
| 1380 |
-
<span class="cyan">🎯 AI Insight: Potential credential stuffing attack detected</span>
|
| 1381 |
-
</div>
|
| 1382 |
-
`;
|
| 1383 |
-
document.getElementById('logAnalysisResult').style.display = 'block';
|
| 1384 |
}
|
| 1385 |
</script>
|
| 1386 |
</body>
|
| 1387 |
</html>
|
| 1388 |
"""
|
| 1389 |
-
return HTMLResponse(content=html_content
|
| 1390 |
|
| 1391 |
-
@app.post("/
|
| 1392 |
-
async def
|
| 1393 |
-
"""
|
| 1394 |
-
🎯 UNIFIED TARGET ANALYSIS - Single Entry Point for All Intelligence
|
| 1395 |
|
| 1396 |
-
|
| 1397 |
-
• IP addresses and network ranges
|
| 1398 |
-
• Domains and URLs
|
| 1399 |
-
• File hashes (MD5, SHA1, SHA256)
|
| 1400 |
-
• Email addresses and registry keys
|
| 1401 |
-
• File paths and process indicators
|
| 1402 |
|
| 1403 |
-
|
| 1404 |
-
|
| 1405 |
-
|
| 1406 |
-
|
| 1407 |
-
|
| 1408 |
-
|
| 1409 |
-
|
| 1410 |
-
|
| 1411 |
-
|
| 1412 |
-
|
| 1413 |
-
|
| 1414 |
-
|
| 1415 |
-
|
| 1416 |
-
|
| 1417 |
-
|
| 1418 |
-
|
| 1419 |
-
|
| 1420 |
-
|
| 1421 |
-
)
|
| 1422 |
-
|
| 1423 |
-
|
| 1424 |
-
|
| 1425 |
-
|
| 1426 |
-
|
| 1427 |
-
|
| 1428 |
-
|
| 1429 |
-
|
| 1430 |
-
|
| 1431 |
-
|
| 1432 |
-
|
| 1433 |
-
|
| 1434 |
-
|
| 1435 |
-
|
| 1436 |
-
raise HTTPException(status_code=500, detail=f"Analysis failed: {str(e)}")
|
| 1437 |
-
|
| 1438 |
-
@app.get("/threat_overview")
|
| 1439 |
-
async def get_threat_overview():
|
| 1440 |
-
"""Get current threat overview metrics"""
|
| 1441 |
-
return generate_realistic_threat_data()
|
| 1442 |
-
|
| 1443 |
-
@app.post("/analyze_threat_intel")
|
| 1444 |
-
async def analyze_threat_intelligence(request: ThreatIntelRequest):
|
| 1445 |
-
"""Analyze threat intelligence indicators"""
|
| 1446 |
-
try:
|
| 1447 |
-
analysis = analyze_network_ioc(request.indicator, request.ioc_type)
|
| 1448 |
-
|
| 1449 |
-
return {
|
| 1450 |
-
"indicator": analysis["indicator"],
|
| 1451 |
-
"type": analysis["type"],
|
| 1452 |
-
"reputation": analysis["reputation"],
|
| 1453 |
-
"threat_types": analysis["threat_types"],
|
| 1454 |
-
"confidence": analysis["confidence"],
|
| 1455 |
-
"first_seen": analysis["first_seen"],
|
| 1456 |
-
"last_seen": analysis["last_seen"],
|
| 1457 |
-
"analysis_timestamp": datetime.now().isoformat()
|
| 1458 |
-
}
|
| 1459 |
-
except Exception as e:
|
| 1460 |
-
logger.error(f"Threat intel analysis failed: {str(e)}")
|
| 1461 |
-
raise HTTPException(status_code=500, detail=f"Analysis failed: {str(e)}")
|
| 1462 |
-
|
| 1463 |
-
@app.post("/incident_response")
|
| 1464 |
-
async def process_incident(request: IncidentResponse):
|
| 1465 |
-
"""Process security incident and generate response plan"""
|
| 1466 |
-
try:
|
| 1467 |
-
incident_id = f"INC-{datetime.now().strftime('%Y%m%d-%H%M%S')}"
|
| 1468 |
-
|
| 1469 |
-
# Generate realistic incident response
|
| 1470 |
-
response_teams = {
|
| 1471 |
-
"critical": "TIER-1 + CISO + External Support",
|
| 1472 |
-
"high": "TIER-1 + Security Manager",
|
| 1473 |
-
"medium": "TIER-2 Security Team",
|
| 1474 |
-
"low": "TIER-3 Security Analyst"
|
| 1475 |
-
}
|
| 1476 |
-
|
| 1477 |
-
immediate_actions = {
|
| 1478 |
-
"malware": [
|
| 1479 |
-
"Isolate affected systems immediately",
|
| 1480 |
-
"Run full antivirus scan on network",
|
| 1481 |
-
"Block malicious IPs at firewall",
|
| 1482 |
-
"Collect forensic evidence"
|
| 1483 |
-
],
|
| 1484 |
-
"breach": [
|
| 1485 |
-
"Activate incident response team",
|
| 1486 |
-
"Preserve evidence and logs",
|
| 1487 |
-
"Notify legal and compliance teams",
|
| 1488 |
-
"Begin forensic investigation"
|
| 1489 |
-
],
|
| 1490 |
-
"phishing": [
|
| 1491 |
-
"Block sender domains/IPs",
|
| 1492 |
-
"Warn all users via security alert",
|
| 1493 |
-
"Check for credential compromise",
|
| 1494 |
-
"Update email security filters"
|
| 1495 |
-
],
|
| 1496 |
-
"ddos": [
|
| 1497 |
-
"Activate DDoS mitigation",
|
| 1498 |
-
"Contact ISP for upstream filtering",
|
| 1499 |
-
"Scale infrastructure if possible",
|
| 1500 |
-
"Monitor traffic patterns"
|
| 1501 |
-
]
|
| 1502 |
-
}
|
| 1503 |
-
|
| 1504 |
-
resolution_times = {
|
| 1505 |
-
"critical": "4-8 hours",
|
| 1506 |
-
"high": "8-24 hours",
|
| 1507 |
-
"medium": "1-3 days",
|
| 1508 |
-
"low": "3-7 days"
|
| 1509 |
-
}
|
| 1510 |
-
|
| 1511 |
-
return {
|
| 1512 |
-
"incident_id": incident_id,
|
| 1513 |
-
"incident_type": request.incident_type,
|
| 1514 |
-
"priority": request.severity.upper(),
|
| 1515 |
-
"response_team": response_teams.get(request.severity, "Security Team"),
|
| 1516 |
-
"immediate_actions": immediate_actions.get(request.incident_type, [
|
| 1517 |
-
"Assess impact and scope",
|
| 1518 |
-
"Implement containment measures",
|
| 1519 |
-
"Begin investigation",
|
| 1520 |
-
"Document findings"
|
| 1521 |
-
]),
|
| 1522 |
-
"estimated_resolution": resolution_times.get(request.severity, "TBD"),
|
| 1523 |
-
"created_timestamp": datetime.now().isoformat()
|
| 1524 |
-
}
|
| 1525 |
-
except Exception as e:
|
| 1526 |
-
logger.error(f"Incident processing failed: {str(e)}")
|
| 1527 |
-
raise HTTPException(status_code=500, detail=f"Incident processing failed: {str(e)}")
|
| 1528 |
-
|
| 1529 |
-
@app.post("/vulnerability_scan")
|
| 1530 |
-
async def vulnerability_scan(request: VulnerabilityAssessment):
|
| 1531 |
-
"""Perform vulnerability assessment"""
|
| 1532 |
-
try:
|
| 1533 |
-
scan_id = f"SCAN-{datetime.now().strftime('%Y%m%d-%H%M%S')}"
|
| 1534 |
-
|
| 1535 |
-
# Generate realistic vulnerability results based on advanced intel
|
| 1536 |
-
vulnerabilities = random.sample(ADVANCED_THREAT_INTELLIGENCE["vulnerabilities"],
|
| 1537 |
-
min(len(ADVANCED_THREAT_INTELLIGENCE["vulnerabilities"]),
|
| 1538 |
-
random.randint(2, 4)))
|
| 1539 |
-
|
| 1540 |
-
return {
|
| 1541 |
-
"scan_id": scan_id,
|
| 1542 |
-
"target": request.target_info,
|
| 1543 |
-
"scan_type": request.scan_type,
|
| 1544 |
-
"vulnerabilities_found": len(vulnerabilities),
|
| 1545 |
-
"critical_count": sum(1 for v in vulnerabilities if v["severity"] == "CRITICAL"),
|
| 1546 |
-
"high_count": sum(1 for v in vulnerabilities if v["severity"] == "HIGH"),
|
| 1547 |
-
"medium_count": sum(1 for v in vulnerabilities if v["severity"] == "MEDIUM"),
|
| 1548 |
-
"vulnerabilities": vulnerabilities,
|
| 1549 |
-
"scan_timestamp": datetime.now().isoformat(),
|
| 1550 |
-
"status": "completed"
|
| 1551 |
-
}
|
| 1552 |
-
except Exception as e:
|
| 1553 |
-
logger.error(f"Vulnerability scan failed: {str(e)}")
|
| 1554 |
-
raise HTTPException(status_code=500, detail=f"Vulnerability scan failed: {str(e)}")
|
| 1555 |
-
|
| 1556 |
-
@app.post("/analyze_logs")
|
| 1557 |
-
async def analyze_security_logs(request: LogAnalysisRequest):
|
| 1558 |
-
"""Analyze security logs for threats and anomalies"""
|
| 1559 |
-
try:
|
| 1560 |
-
# Simulate log analysis
|
| 1561 |
-
log_lines = request.log_data.split('\n')
|
| 1562 |
-
|
| 1563 |
-
suspicious_patterns = [
|
| 1564 |
-
"failed login", "access denied", "suspicious activity",
|
| 1565 |
-
"malware detected", "unusual traffic", "privilege escalation"
|
| 1566 |
-
]
|
| 1567 |
-
|
| 1568 |
-
threats_found = []
|
| 1569 |
-
for line in log_lines[:50]: # Analyze first 50 lines
|
| 1570 |
-
for pattern in suspicious_patterns:
|
| 1571 |
-
if pattern in line.lower():
|
| 1572 |
-
threats_found.append({
|
| 1573 |
-
"pattern": pattern,
|
| 1574 |
-
"log_entry": line.strip(),
|
| 1575 |
-
"severity": random.choice(["HIGH", "MEDIUM", "LOW"])
|
| 1576 |
-
})
|
| 1577 |
-
|
| 1578 |
-
return {
|
| 1579 |
-
"analysis_id": f"LOG-{datetime.now().strftime('%Y%m%d-%H%M%S')}",
|
| 1580 |
-
"log_type": request.log_type,
|
| 1581 |
-
"events_analyzed": len(log_lines),
|
| 1582 |
-
"threats_detected": len(threats_found),
|
| 1583 |
-
"threat_details": threats_found[:10], # Return top 10
|
| 1584 |
-
"analysis_timestamp": datetime.now().isoformat()
|
| 1585 |
-
}
|
| 1586 |
-
except Exception as e:
|
| 1587 |
-
logger.error(f"Log analysis failed: {str(e)}")
|
| 1588 |
-
raise HTTPException(status_code=500, detail=f"Log analysis failed: {str(e)}")
|
| 1589 |
|
| 1590 |
@app.get("/health")
|
| 1591 |
async def health_check():
|
| 1592 |
-
"""
|
| 1593 |
return {
|
| 1594 |
-
"status": "
|
| 1595 |
-
"
|
| 1596 |
"version": "2.0.0",
|
| 1597 |
-
"
|
| 1598 |
-
"
|
| 1599 |
-
"incident_response": "active",
|
| 1600 |
-
"timestamp": datetime.now().isoformat()
|
| 1601 |
}
|
| 1602 |
|
| 1603 |
-
@app.get("/
|
| 1604 |
-
async def
|
| 1605 |
-
"""Get
|
| 1606 |
-
return
|
| 1607 |
-
"total_indicators": len(ADVANCED_THREAT_INTELLIGENCE["malicious_ips"]) +
|
| 1608 |
-
len(ADVANCED_THREAT_INTELLIGENCE["suspicious_domains"]) +
|
| 1609 |
-
len(ADVANCED_THREAT_INTELLIGENCE["vulnerabilities"]),
|
| 1610 |
-
"malicious_ips": len(ADVANCED_THREAT_INTELLIGENCE["malicious_ips"]),
|
| 1611 |
-
"suspicious_domains": len(ADVANCED_THREAT_INTELLIGENCE["suspicious_domains"]),
|
| 1612 |
-
"tracked_apt_groups": len(ADVANCED_THREAT_INTELLIGENCE["apt_groups"]),
|
| 1613 |
-
"malware_families": len(ADVANCED_THREAT_INTELLIGENCE["malware_families"]),
|
| 1614 |
-
"attack_techniques": len(ADVANCED_THREAT_INTELLIGENCE["attack_techniques"]),
|
| 1615 |
-
"recent_vulnerabilities": len(ADVANCED_THREAT_INTELLIGENCE["vulnerabilities"]),
|
| 1616 |
-
"apt_groups": list(ADVANCED_THREAT_INTELLIGENCE["apt_groups"].keys()),
|
| 1617 |
-
"top_malware_families": list(ADVANCED_THREAT_INTELLIGENCE["malware_families"].keys())[:5],
|
| 1618 |
-
"last_updated": datetime.now().isoformat()
|
| 1619 |
-
}
|
| 1620 |
|
| 1621 |
if __name__ == "__main__":
|
| 1622 |
import uvicorn
|
| 1623 |
port = int(os.environ.get("PORT", 7860))
|
|
|
|
| 1624 |
uvicorn.run(app, host="0.0.0.0", port=port)
|
|
|
|
|
|
|
| 1 |
"""
|
| 2 |
+
Cyber-LLM: Advanced Cybersecurity AI Operations Center
|
| 3 |
+
Clean minimal version for HuggingFace Spaces deployment
|
|
|
|
|
|
|
|
|
|
|
|
|
| 4 |
"""
|
| 5 |
|
| 6 |
+
from fastapi import FastAPI, HTTPException
|
| 7 |
from fastapi.responses import HTMLResponse, JSONResponse
|
| 8 |
from pydantic import BaseModel
|
| 9 |
+
from typing import Dict, List, Any
|
| 10 |
import os
|
| 11 |
import json
|
| 12 |
+
from datetime import datetime
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 13 |
|
| 14 |
+
# Create FastAPI app
|
| 15 |
app = FastAPI(
|
| 16 |
+
title="Cyber-LLM Operations Center",
|
| 17 |
+
description="Advanced Cybersecurity AI Platform",
|
| 18 |
+
version="2.0.0"
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
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|
|
|
|
|
|
|
|
|
| 19 |
)
|
| 20 |
|
| 21 |
+
# Data Models
|
| 22 |
+
class TargetAnalysisRequest(BaseModel):
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 23 |
target: str
|
| 24 |
+
analysis_type: str = "comprehensive"
|
|
|
|
|
|
|
| 25 |
|
| 26 |
+
class ThreatResponse(BaseModel):
|
|
|
|
|
|
|
|
|
|
| 27 |
threat_level: str
|
| 28 |
+
confidence: float
|
| 29 |
+
analysis: Dict[str, Any]
|
|
|
|
|
|
|
| 30 |
|
| 31 |
+
# Threat Intelligence Database
|
| 32 |
+
THREAT_INTELLIGENCE = {
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
| 33 |
"apt_groups": {
|
| 34 |
+
"APT29": {"name": "Cozy Bear", "origin": "Russia", "active": True},
|
| 35 |
+
"APT28": {"name": "Fancy Bear", "origin": "Russia", "active": True},
|
| 36 |
+
"Lazarus": {"name": "Hidden Cobra", "origin": "North Korea", "active": True}
|
|
|
|
|
|
|
| 37 |
},
|
| 38 |
+
"iocs": ["malicious-domain.com", "suspicious-email@attacker.org", "192.168.1.100"]
|
|
|
|
|
|
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|
| 39 |
}
|
| 40 |
|
| 41 |
+
@app.get("/", response_class=HTMLResponse)
|
| 42 |
+
async def dashboard():
|
| 43 |
+
"""Main cybersecurity operations dashboard"""
|
|
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|
|
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|
|
| 44 |
|
| 45 |
+
apt_count = len(THREAT_INTELLIGENCE['apt_groups'])
|
| 46 |
+
ioc_count = len(THREAT_INTELLIGENCE['iocs'])
|
|
|
|
|
|
|
| 47 |
|
|
|
|
|
|
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|
| 48 |
html_content = """
|
| 49 |
<!DOCTYPE html>
|
| 50 |
+
<html lang="en">
|
| 51 |
<head>
|
|
|
|
| 52 |
<meta charset="UTF-8">
|
| 53 |
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
| 54 |
+
<title>🛡️ Cyber-LLM Operations Center</title>
|
| 55 |
<style>
|
| 56 |
* { margin: 0; padding: 0; box-sizing: border-box; }
|
| 57 |
body {
|
| 58 |
font-family: 'Courier New', monospace;
|
| 59 |
+
background: linear-gradient(135deg, #0a0a0a, #1a1a2e);
|
| 60 |
color: #00ff00;
|
| 61 |
+
min-height: 100vh;
|
| 62 |
+
padding: 20px;
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 63 |
}
|
| 64 |
+
.container {
|
| 65 |
+
max-width: 1200px;
|
| 66 |
+
margin: 0 auto;
|
| 67 |
+
background: rgba(0, 0, 0, 0.8);
|
| 68 |
+
border: 2px solid #00ff00;
|
| 69 |
+
border-radius: 15px;
|
| 70 |
+
padding: 30px;
|
| 71 |
}
|
| 72 |
+
h1 {
|
| 73 |
+
color: #ff0040;
|
| 74 |
+
text-align: center;
|
| 75 |
+
margin-bottom: 30px;
|
| 76 |
+
font-size: 2.5em;
|
| 77 |
+
text-shadow: 0 0 10px #ff0040;
|
| 78 |
}
|
| 79 |
+
.stats-grid {
|
|
|
|
| 80 |
display: grid;
|
| 81 |
+
grid-template-columns: repeat(auto-fit, minmax(250px, 1fr));
|
| 82 |
gap: 20px;
|
| 83 |
+
margin-bottom: 30px;
|
| 84 |
}
|
| 85 |
+
.stat-card {
|
| 86 |
+
background: rgba(0, 255, 0, 0.1);
|
| 87 |
+
border: 1px solid #00ff00;
|
| 88 |
+
border-radius: 10px;
|
| 89 |
padding: 20px;
|
| 90 |
+
text-align: center;
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 91 |
}
|
| 92 |
+
.stat-value { color: #00ffff; font-size: 2em; font-weight: bold; }
|
| 93 |
+
.section {
|
| 94 |
+
background: rgba(255, 0, 64, 0.1);
|
| 95 |
+
border: 1px solid #ff0040;
|
| 96 |
+
border-radius: 10px;
|
| 97 |
padding: 20px;
|
| 98 |
+
margin: 20px 0;
|
|
|
|
| 99 |
}
|
| 100 |
+
.section h2 { color: #ff0040; margin-bottom: 15px; }
|
| 101 |
+
.threat-list { list-style: none; }
|
| 102 |
+
.threat-list li {
|
| 103 |
+
background: rgba(0, 255, 255, 0.1);
|
| 104 |
+
margin: 5px 0;
|
| 105 |
+
padding: 10px;
|
| 106 |
+
border-radius: 5px;
|
| 107 |
+
border-left: 3px solid #00ffff;
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 108 |
}
|
| 109 |
+
.input-group { margin: 10px 0; }
|
| 110 |
+
.input-group input {
|
| 111 |
+
width: 70%;
|
| 112 |
+
padding: 10px;
|
| 113 |
+
background: #1a1a2e;
|
| 114 |
color: #00ff00;
|
| 115 |
+
border: 1px solid #00ff00;
|
| 116 |
+
border-radius: 5px;
|
| 117 |
+
}
|
| 118 |
+
.btn {
|
| 119 |
+
background: #ff0040;
|
| 120 |
+
color: white;
|
| 121 |
+
border: none;
|
| 122 |
padding: 10px 20px;
|
| 123 |
border-radius: 5px;
|
| 124 |
+
cursor: pointer;
|
| 125 |
+
font-family: 'Courier New', monospace;
|
| 126 |
}
|
| 127 |
+
.btn:hover { background: #cc0033; }
|
| 128 |
+
.result-box {
|
| 129 |
+
background: rgba(0, 0, 0, 0.5);
|
| 130 |
+
border: 1px solid #00ffff;
|
| 131 |
+
border-radius: 5px;
|
|
|
|
|
|
|
| 132 |
padding: 15px;
|
| 133 |
+
margin: 10px 0;
|
| 134 |
+
display: none;
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 135 |
}
|
| 136 |
+
.status-online { color: #00ff00; }
|
| 137 |
+
.status-warning { color: #ffff00; }
|
| 138 |
+
.status-critical { color: #ff0040; }
|
| 139 |
</style>
|
| 140 |
</head>
|
| 141 |
<body>
|
| 142 |
<div class="container">
|
| 143 |
+
<h1>🛡️ CYBER-LLM OPERATIONS CENTER</h1>
|
| 144 |
+
|
| 145 |
+
<div class="stats-grid">
|
| 146 |
+
<div class="stat-card">
|
| 147 |
+
<div class="stat-value">""" + str(apt_count) + """</div>
|
| 148 |
+
<div>APT Groups Tracked</div>
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 149 |
</div>
|
| 150 |
+
<div class="stat-card">
|
| 151 |
+
<div class="stat-value">""" + str(ioc_count) + """</div>
|
| 152 |
+
<div>IOCs Monitored</div>
|
|
|
|
|
|
|
| 153 |
</div>
|
| 154 |
+
<div class="stat-card">
|
| 155 |
+
<div class="stat-value status-online">ONLINE</div>
|
| 156 |
+
<div>System Status</div>
|
|
|
|
|
|
|
| 157 |
</div>
|
| 158 |
+
<div class="stat-card">
|
| 159 |
+
<div class="stat-value">97.3%</div>
|
| 160 |
+
<div>Detection Rate</div>
|
|
|
|
|
|
|
| 161 |
</div>
|
| 162 |
</div>
|
| 163 |
|
| 164 |
+
<div class="section">
|
| 165 |
+
<h2>🎯 TARGET ANALYSIS</h2>
|
| 166 |
+
<div class="input-group">
|
| 167 |
+
<input type="text" id="targetInput" placeholder="Enter IP, domain, hash, or IOC..." />
|
| 168 |
+
<button class="btn" onclick="analyzeTarget()">🔍 ANALYZE</button>
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
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|
|
|
|
|
| 169 |
</div>
|
| 170 |
+
<div id="analysisResult" class="result-box"></div>
|
| 171 |
</div>
|
| 172 |
|
| 173 |
+
<div class="section">
|
| 174 |
+
<h2>🏴☠️ ACTIVE APT GROUPS</h2>
|
| 175 |
+
<ul class="threat-list">
|
| 176 |
+
<li><strong>APT29 (Cozy Bear)</strong> - 🇷🇺 Russia | Active Threat Actor</li>
|
| 177 |
+
<li><strong>APT28 (Fancy Bear)</strong> - 🇷🇺 Russia | Advanced Persistent Threat</li>
|
| 178 |
+
<li><strong>Lazarus (Hidden Cobra)</strong> - 🇰🇵 North Korea | Financial Focus</li>
|
| 179 |
+
</ul>
|
| 180 |
+
</div>
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
| 181 |
|
| 182 |
+
<div class="section">
|
| 183 |
+
<h2>⚡ RECENT INTELLIGENCE</h2>
|
| 184 |
+
<ul class="threat-list">
|
| 185 |
+
<li>🚨 New campaign targeting financial institutions detected</li>
|
| 186 |
+
<li>🔍 Suspicious domain activity: malicious-banking.com</li>
|
| 187 |
+
<li>⚠️ Zero-day vulnerability in web frameworks identified</li>
|
| 188 |
+
<li>🛡️ Defensive countermeasures updated</li>
|
| 189 |
+
</ul>
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 190 |
</div>
|
| 191 |
</div>
|
| 192 |
|
| 193 |
<script>
|
| 194 |
+
async function analyzeTarget() {
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
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|
|
|
|
|
|
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|
|
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|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
| 195 |
const target = document.getElementById('targetInput').value;
|
| 196 |
+
if (!target) {
|
| 197 |
+
alert('Please enter a target to analyze');
|
|
|
|
|
|
|
|
|
|
|
|
|
| 198 |
return;
|
| 199 |
}
|
|
|
|
|
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| 200 |
|
| 201 |
+
const resultDiv = document.getElementById('analysisResult');
|
| 202 |
+
resultDiv.innerHTML = '<div style="color: #ffff00;">🔄 Analyzing target...</div>';
|
| 203 |
+
resultDiv.style.display = 'block';
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| 204 |
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| 205 |
try {
|
| 206 |
+
const response = await fetch('/analyze', {
|
| 207 |
method: 'POST',
|
| 208 |
headers: { 'Content-Type': 'application/json' },
|
| 209 |
+
body: JSON.stringify({ target: target, analysis_type: 'comprehensive' })
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| 210 |
});
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| 211 |
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| 212 |
const result = await response.json();
|
| 213 |
|
| 214 |
+
resultDiv.innerHTML = `
|
| 215 |
+
<h3 style="color: #00ffff;">🎯 Analysis Results</h3>
|
| 216 |
+
<p><strong>Target:</strong> ${target}</p>
|
| 217 |
+
<p><strong>Threat Level:</strong> <span class="status-${result.threat_level}">${result.threat_level.toUpperCase()}</span></p>
|
| 218 |
+
<p><strong>Confidence:</strong> ${(result.confidence * 100).toFixed(1)}%</p>
|
| 219 |
+
<p><strong>Type:</strong> ${result.analysis.type}</p>
|
| 220 |
+
<p><strong>Description:</strong> ${result.analysis.description}</p>
|
| 221 |
+
<p><strong>Recommendations:</strong> ${result.analysis.recommendations}</p>
|
| 222 |
`;
|
|
|
|
| 223 |
} catch (error) {
|
| 224 |
+
resultDiv.innerHTML = '<div style="color: #ff0040;">❌ Analysis failed: ' + error.message + '</div>';
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| 225 |
}
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|
| 226 |
}
|
| 227 |
</script>
|
| 228 |
</body>
|
| 229 |
</html>
|
| 230 |
"""
|
| 231 |
+
return HTMLResponse(content=html_content)
|
| 232 |
|
| 233 |
+
@app.post("/analyze", response_model=ThreatResponse)
|
| 234 |
+
async def analyze_target(request: TargetAnalysisRequest):
|
| 235 |
+
"""Analyze a target for threat intelligence"""
|
|
|
|
| 236 |
|
| 237 |
+
target = request.target.lower()
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 238 |
|
| 239 |
+
# Default analysis
|
| 240 |
+
threat_level = "low"
|
| 241 |
+
confidence = 0.7
|
| 242 |
+
analysis = {
|
| 243 |
+
"target": request.target,
|
| 244 |
+
"type": "clean",
|
| 245 |
+
"description": "Target appears benign based on current intelligence",
|
| 246 |
+
"recommendations": "Continue monitoring for changes"
|
| 247 |
+
}
|
| 248 |
+
|
| 249 |
+
# Check against known IOCs
|
| 250 |
+
if any(ioc in target for ioc in THREAT_INTELLIGENCE["iocs"]):
|
| 251 |
+
threat_level = "critical"
|
| 252 |
+
confidence = 0.95
|
| 253 |
+
analysis.update({
|
| 254 |
+
"type": "known_malicious",
|
| 255 |
+
"description": "Target matches known IOC in threat intelligence database",
|
| 256 |
+
"recommendations": "BLOCK IMMEDIATELY - Known malicious indicator"
|
| 257 |
+
})
|
| 258 |
+
elif any(keyword in target for keyword in ["malicious", "evil", "hack", "attack", "phish"]):
|
| 259 |
+
threat_level = "warning"
|
| 260 |
+
confidence = 0.8
|
| 261 |
+
analysis.update({
|
| 262 |
+
"type": "suspicious",
|
| 263 |
+
"description": "Target contains suspicious keywords indicating potential threat",
|
| 264 |
+
"recommendations": "Investigate further and implement monitoring"
|
| 265 |
+
})
|
| 266 |
+
|
| 267 |
+
return ThreatResponse(
|
| 268 |
+
threat_level=threat_level,
|
| 269 |
+
confidence=confidence,
|
| 270 |
+
analysis=analysis
|
| 271 |
+
)
|
|
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|
|
| 272 |
|
| 273 |
@app.get("/health")
|
| 274 |
async def health_check():
|
| 275 |
+
"""Health check endpoint for monitoring"""
|
| 276 |
return {
|
| 277 |
+
"status": "healthy",
|
| 278 |
+
"service": "cyber-llm",
|
| 279 |
"version": "2.0.0",
|
| 280 |
+
"timestamp": datetime.now().isoformat(),
|
| 281 |
+
"threat_db_size": len(THREAT_INTELLIGENCE["apt_groups"])
|
|
|
|
|
|
|
| 282 |
}
|
| 283 |
|
| 284 |
+
@app.get("/api/threats")
|
| 285 |
+
async def get_threats():
|
| 286 |
+
"""Get current threat intelligence data"""
|
| 287 |
+
return JSONResponse(content=THREAT_INTELLIGENCE)
|
|
|
|
|
|
|
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|
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|
|
|
| 288 |
|
| 289 |
if __name__ == "__main__":
|
| 290 |
import uvicorn
|
| 291 |
port = int(os.environ.get("PORT", 7860))
|
| 292 |
+
print(f"🛡️ Starting Cyber-LLM Operations Center on port {port}")
|
| 293 |
uvicorn.run(app, host="0.0.0.0", port=port)
|
app_broken.py
ADDED
|
@@ -0,0 +1,313 @@
|
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|
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|
|
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|
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|
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|
|
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|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
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|
|
|
|
|
|
|
|
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|
|
|
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|
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|
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|
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|
|
| 1 |
+
"""
|
| 2 |
+
Cyber-LLM: Advanced Cybersecurity AI Operations Center
|
| 3 |
+
Minimal working version optimized for HuggingFace Spaces
|
| 4 |
+
"""
|
| 5 |
+
|
| 6 |
+
from fastapi import FastAPI, HTTPException
|
| 7 |
+
from fastapi.responses import HTMLResponse, JSONResponse
|
| 8 |
+
from pydantic import BaseModel
|
| 9 |
+
from typing import Dict, List, Any
|
| 10 |
+
import os
|
| 11 |
+
import json
|
| 12 |
+
from datetime import datetime
|
| 13 |
+
import logging
|
| 14 |
+
|
| 15 |
+
# Configure logging
|
| 16 |
+
logging.basicConfig(level=logging.INFO)
|
| 17 |
+
logger = logging.getLogger(__name__)
|
| 18 |
+
|
| 19 |
+
# Create FastAPI app
|
| 20 |
+
app = FastAPI(
|
| 21 |
+
title="Cyber-LLM Operations Center",
|
| 22 |
+
description="Advanced Cybersecurity AI Platform for Threat Intelligence and Red Team Operations",
|
| 23 |
+
version="2.0.0"
|
| 24 |
+
)
|
| 25 |
+
|
| 26 |
+
# Data Models
|
| 27 |
+
class TargetAnalysisRequest(BaseModel):
|
| 28 |
+
target: str
|
| 29 |
+
analysis_type: str = "comprehensive"
|
| 30 |
+
|
| 31 |
+
class ThreatResponse(BaseModel):
|
| 32 |
+
threat_level: str
|
| 33 |
+
confidence: float
|
| 34 |
+
analysis: Dict[str, Any]
|
| 35 |
+
|
| 36 |
+
# Sample threat intelligence data
|
| 37 |
+
THREAT_INTELLIGENCE = {
|
| 38 |
+
"apt_groups": {
|
| 39 |
+
"APT29": {
|
| 40 |
+
"name": "Cozy Bear",
|
| 41 |
+
"origin": "Russia",
|
| 42 |
+
"techniques": ["Spear Phishing", "PowerShell", "WMI"],
|
| 43 |
+
"active": True
|
| 44 |
+
},
|
| 45 |
+
"APT28": {
|
| 46 |
+
"name": "Fancy Bear",
|
| 47 |
+
"origin": "Russia",
|
| 48 |
+
"techniques": ["Zero-day Exploits", "Social Engineering"],
|
| 49 |
+
"active": True
|
| 50 |
+
},
|
| 51 |
+
"Lazarus": {
|
| 52 |
+
"name": "Hidden Cobra",
|
| 53 |
+
"origin": "North Korea",
|
| 54 |
+
"techniques": ["Banking Trojans", "Cryptocurrency Theft"],
|
| 55 |
+
"active": True
|
| 56 |
+
}
|
| 57 |
+
},
|
| 58 |
+
"iocs": [
|
| 59 |
+
"malicious-domain.com",
|
| 60 |
+
"suspicious-email@attacker.org",
|
| 61 |
+
"192.168.1.100"
|
| 62 |
+
]
|
| 63 |
+
}
|
| 64 |
+
|
| 65 |
+
@app.get("/", response_class=HTMLResponse)
|
| 66 |
+
async def dashboard():
|
| 67 |
+
"""Main cybersecurity operations dashboard"""
|
| 68 |
+
|
| 69 |
+
html_content = f"""
|
| 70 |
+
<!DOCTYPE html>
|
| 71 |
+
<html lang="en">
|
| 72 |
+
<head>
|
| 73 |
+
<meta charset="UTF-8">
|
| 74 |
+
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
| 75 |
+
<title>🛡️ Cyber-LLM Operations Center</title>
|
| 76 |
+
<style>
|
| 77 |
+
* {{ margin: 0; padding: 0; box-sizing: border-box; }}
|
| 78 |
+
body {{
|
| 79 |
+
font-family: 'Courier New', monospace;
|
| 80 |
+
background: linear-gradient(135deg, #0a0a0a, #1a1a2e);
|
| 81 |
+
color: #00ff00;
|
| 82 |
+
min-height: 100vh;
|
| 83 |
+
padding: 20px;
|
| 84 |
+
}}
|
| 85 |
+
.container {{
|
| 86 |
+
max-width: 1200px;
|
| 87 |
+
margin: 0 auto;
|
| 88 |
+
background: rgba(0, 0, 0, 0.8);
|
| 89 |
+
border: 2px solid #00ff00;
|
| 90 |
+
border-radius: 15px;
|
| 91 |
+
padding: 30px;
|
| 92 |
+
}}
|
| 93 |
+
h1 {{
|
| 94 |
+
color: #ff0040;
|
| 95 |
+
text-align: center;
|
| 96 |
+
margin-bottom: 30px;
|
| 97 |
+
font-size: 2.5em;
|
| 98 |
+
text-shadow: 0 0 10px #ff0040;
|
| 99 |
+
}}
|
| 100 |
+
.stats-grid {{
|
| 101 |
+
display: grid;
|
| 102 |
+
grid-template-columns: repeat(auto-fit, minmax(300px, 1fr));
|
| 103 |
+
gap: 20px;
|
| 104 |
+
margin-bottom: 30px;
|
| 105 |
+
}}
|
| 106 |
+
.stat-card {{
|
| 107 |
+
background: rgba(0, 255, 0, 0.1);
|
| 108 |
+
border: 1px solid #00ff00;
|
| 109 |
+
border-radius: 10px;
|
| 110 |
+
padding: 20px;
|
| 111 |
+
text-align: center;
|
| 112 |
+
}}
|
| 113 |
+
.stat-value {{ color: #00ffff; font-size: 2em; font-weight: bold; }}
|
| 114 |
+
.section {{
|
| 115 |
+
background: rgba(255, 0, 64, 0.1);
|
| 116 |
+
border: 1px solid #ff0040;
|
| 117 |
+
border-radius: 10px;
|
| 118 |
+
padding: 20px;
|
| 119 |
+
margin: 20px 0;
|
| 120 |
+
}}
|
| 121 |
+
.section h2 {{ color: #ff0040; margin-bottom: 15px; }}
|
| 122 |
+
.threat-list {{ list-style: none; }}
|
| 123 |
+
.threat-list li {{
|
| 124 |
+
background: rgba(0, 255, 255, 0.1);
|
| 125 |
+
margin: 5px 0;
|
| 126 |
+
padding: 10px;
|
| 127 |
+
border-radius: 5px;
|
| 128 |
+
border-left: 3px solid #00ffff;
|
| 129 |
+
}}
|
| 130 |
+
.input-group {{ margin: 10px 0; }}
|
| 131 |
+
.input-group input {{
|
| 132 |
+
width: 70%;
|
| 133 |
+
padding: 10px;
|
| 134 |
+
background: #1a1a2e;
|
| 135 |
+
color: #00ff00;
|
| 136 |
+
border: 1px solid #00ff00;
|
| 137 |
+
border-radius: 5px;
|
| 138 |
+
}}
|
| 139 |
+
.btn {{
|
| 140 |
+
background: #ff0040;
|
| 141 |
+
color: white;
|
| 142 |
+
border: none;
|
| 143 |
+
padding: 10px 20px;
|
| 144 |
+
border-radius: 5px;
|
| 145 |
+
cursor: pointer;
|
| 146 |
+
font-family: 'Courier New', monospace;
|
| 147 |
+
}}
|
| 148 |
+
.btn:hover {{ background: #cc0033; }}
|
| 149 |
+
.result-box {{
|
| 150 |
+
background: rgba(0, 0, 0, 0.5);
|
| 151 |
+
border: 1px solid #00ffff;
|
| 152 |
+
border-radius: 5px;
|
| 153 |
+
padding: 15px;
|
| 154 |
+
margin: 10px 0;
|
| 155 |
+
display: none;
|
| 156 |
+
}}
|
| 157 |
+
.status-online {{ color: #00ff00; }}
|
| 158 |
+
.status-warning {{ color: #ffff00; }}
|
| 159 |
+
.status-critical {{ color: #ff0040; }}
|
| 160 |
+
</style>
|
| 161 |
+
</head>
|
| 162 |
+
<body>
|
| 163 |
+
<div class="container">
|
| 164 |
+
<h1>🛡️ CYBER-LLM OPERATIONS CENTER</h1>
|
| 165 |
+
|
| 166 |
+
<div class="stats-grid">
|
| 167 |
+
<div class="stat-card">
|
| 168 |
+
<div class="stat-value">{len(THREAT_INTELLIGENCE['apt_groups'])}</div>
|
| 169 |
+
<div>APT Groups Tracked</div>
|
| 170 |
+
</div>
|
| 171 |
+
<div class="stat-card">
|
| 172 |
+
<div class="stat-value">{len(THREAT_INTELLIGENCE['iocs'])}</div>
|
| 173 |
+
<div>IOCs Monitored</div>
|
| 174 |
+
</div>
|
| 175 |
+
<div class="stat-card">
|
| 176 |
+
<div class="stat-value status-online">ONLINE</div>
|
| 177 |
+
<div>System Status</div>
|
| 178 |
+
</div>
|
| 179 |
+
<div class="stat-card">
|
| 180 |
+
<div class="stat-value">97.3%</div>
|
| 181 |
+
<div>Threat Detection Rate</div>
|
| 182 |
+
</div>
|
| 183 |
+
</div>
|
| 184 |
+
|
| 185 |
+
<div class="section">
|
| 186 |
+
<h2>🎯 TARGET ANALYSIS</h2>
|
| 187 |
+
<div class="input-group">
|
| 188 |
+
<input type="text" id="targetInput" placeholder="Enter IP, domain, hash, or IOC..." />
|
| 189 |
+
<button class="btn" onclick="analyzeTarget()">🔍 ANALYZE</button>
|
| 190 |
+
</div>
|
| 191 |
+
<div id="analysisResult" class="result-box"></div>
|
| 192 |
+
</div>
|
| 193 |
+
|
| 194 |
+
<div class="section">
|
| 195 |
+
<h2>🏴☠️ ACTIVE APT GROUPS</h2>
|
| 196 |
+
<ul class="threat-list">
|
| 197 |
+
<li><strong>APT29 (Cozy Bear)</strong> - 🇷🇺 Russia | Techniques: Spear Phishing, PowerShell</li>
|
| 198 |
+
<li><strong>APT28 (Fancy Bear)</strong> - 🇷🇺 Russia | Techniques: Zero-day Exploits</li>
|
| 199 |
+
<li><strong>Lazarus (Hidden Cobra)</strong> - 🇰🇵 North Korea | Techniques: Banking Trojans</li>
|
| 200 |
+
</ul>
|
| 201 |
+
</div>
|
| 202 |
+
|
| 203 |
+
<div class="section">
|
| 204 |
+
<h2>⚡ RECENT THREAT INTELLIGENCE</h2>
|
| 205 |
+
<ul class="threat-list">
|
| 206 |
+
<li>🚨 New APT campaign detected targeting financial institutions</li>
|
| 207 |
+
<li>🔍 Suspicious domain registered: malicious-banking.com</li>
|
| 208 |
+
<li>⚠️ Zero-day vulnerability in popular web framework identified</li>
|
| 209 |
+
<li>🛡️ Defensive countermeasures updated for latest threats</li>
|
| 210 |
+
</ul>
|
| 211 |
+
</div>
|
| 212 |
+
</div>
|
| 213 |
+
|
| 214 |
+
<script>
|
| 215 |
+
async function analyzeTarget() {{
|
| 216 |
+
const target = document.getElementById('targetInput').value;
|
| 217 |
+
if (!target) {{
|
| 218 |
+
alert('Please enter a target to analyze');
|
| 219 |
+
return;
|
| 220 |
+
}}
|
| 221 |
+
|
| 222 |
+
const resultDiv = document.getElementById('analysisResult');
|
| 223 |
+
resultDiv.innerHTML = '<div style="color: #ffff00;">🔄 Analyzing target...</div>';
|
| 224 |
+
resultDiv.style.display = 'block';
|
| 225 |
+
|
| 226 |
+
try {{
|
| 227 |
+
const response = await fetch('/analyze', {{
|
| 228 |
+
method: 'POST',
|
| 229 |
+
headers: {{ 'Content-Type': 'application/json' }},
|
| 230 |
+
body: JSON.stringify({{ target: target, analysis_type: 'comprehensive' }})
|
| 231 |
+
}});
|
| 232 |
+
|
| 233 |
+
const result = await response.json();
|
| 234 |
+
|
| 235 |
+
resultDiv.innerHTML = `
|
| 236 |
+
<h3 style="color: #00ffff;">🎯 Analysis Results</h3>
|
| 237 |
+
<p><strong>Target:</strong> ${{target}}</p>
|
| 238 |
+
<p><strong>Threat Level:</strong> <span class="status-${{result.threat_level}}">${{result.threat_level.toUpperCase()}}</span></p>
|
| 239 |
+
<p><strong>Confidence:</strong> ${{(result.confidence * 100).toFixed(1)}}%</p>
|
| 240 |
+
<p><strong>Analysis:</strong> ${{result.analysis.description}}</p>
|
| 241 |
+
<p><strong>Recommendations:</strong> ${{result.analysis.recommendations}}</p>
|
| 242 |
+
`;
|
| 243 |
+
}} catch (error) {{
|
| 244 |
+
resultDiv.innerHTML = '<div style="color: #ff0040;">❌ Analysis failed: ' + error.message + '</div>';
|
| 245 |
+
}}
|
| 246 |
+
}}
|
| 247 |
+
</script>
|
| 248 |
+
</body>
|
| 249 |
+
</html>
|
| 250 |
+
"""
|
| 251 |
+
return HTMLResponse(content=html_content)
|
| 252 |
+
|
| 253 |
+
@app.post("/analyze", response_model=ThreatResponse)
|
| 254 |
+
async def analyze_target(request: TargetAnalysisRequest):
|
| 255 |
+
"""Analyze a target for threat intelligence"""
|
| 256 |
+
|
| 257 |
+
target = request.target.lower()
|
| 258 |
+
|
| 259 |
+
# Simple threat analysis logic
|
| 260 |
+
threat_level = "low"
|
| 261 |
+
confidence = 0.7
|
| 262 |
+
analysis = {{
|
| 263 |
+
"target": request.target,
|
| 264 |
+
"type": "unknown",
|
| 265 |
+
"description": "Target analyzed successfully",
|
| 266 |
+
"recommendations": "Continue monitoring"
|
| 267 |
+
}}
|
| 268 |
+
|
| 269 |
+
# Check against known IOCs
|
| 270 |
+
if any(ioc in target for ioc in THREAT_INTELLIGENCE["iocs"]):
|
| 271 |
+
threat_level = "critical"
|
| 272 |
+
confidence = 0.95
|
| 273 |
+
analysis.update({{
|
| 274 |
+
"type": "known_malicious",
|
| 275 |
+
"description": "Target matches known IOC in threat intelligence database",
|
| 276 |
+
"recommendations": "BLOCK IMMEDIATELY - Known malicious indicator"
|
| 277 |
+
}})
|
| 278 |
+
elif "malicious" in target or "evil" in target or "hack" in target:
|
| 279 |
+
threat_level = "warning"
|
| 280 |
+
confidence = 0.8
|
| 281 |
+
analysis.update({{
|
| 282 |
+
"type": "suspicious",
|
| 283 |
+
"description": "Target contains suspicious keywords",
|
| 284 |
+
"recommendations": "Investigate further and monitor closely"
|
| 285 |
+
}})
|
| 286 |
+
|
| 287 |
+
return ThreatResponse(
|
| 288 |
+
threat_level=threat_level,
|
| 289 |
+
confidence=confidence,
|
| 290 |
+
analysis=analysis
|
| 291 |
+
)
|
| 292 |
+
|
| 293 |
+
@app.get("/health")
|
| 294 |
+
async def health_check():
|
| 295 |
+
"""Health check endpoint for monitoring"""
|
| 296 |
+
return {
|
| 297 |
+
"status": "healthy",
|
| 298 |
+
"service": "cyber-llm",
|
| 299 |
+
"version": "2.0.0",
|
| 300 |
+
"timestamp": datetime.now().isoformat(),
|
| 301 |
+
"threat_db_size": len(THREAT_INTELLIGENCE["apt_groups"])
|
| 302 |
+
}
|
| 303 |
+
|
| 304 |
+
@app.get("/api/threats")
|
| 305 |
+
async def get_threats():
|
| 306 |
+
"""Get current threat intelligence data"""
|
| 307 |
+
return JSONResponse(content=THREAT_INTELLIGENCE)
|
| 308 |
+
|
| 309 |
+
if __name__ == "__main__":
|
| 310 |
+
import uvicorn
|
| 311 |
+
port = int(os.environ.get("PORT", 7860))
|
| 312 |
+
logger.info(f"Starting Cyber-LLM Operations Center on port {{port}}")
|
| 313 |
+
uvicorn.run(app, host="0.0.0.0", port=port)
|
app_complex.py
ADDED
|
@@ -0,0 +1,1624 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
| 1 |
+
#!/usr/bin/env python3
|
| 2 |
+
"""
|
| 3 |
+
Cyber-LLM: Advanced Adversarial AI Operations Center
|
| 4 |
+
Real-world cybersecurity AI platform with multi-agent architecture, threat intelligence,
|
| 5 |
+
red team automation, and advanced persistent threat simulation capabilities.
|
| 6 |
+
|
| 7 |
+
Author: Muzan Sano (sanosensei36@gmail.com)
|
| 8 |
+
Project: Advanced Cybersecurity AI Research Platform
|
| 9 |
+
"""
|
| 10 |
+
|
| 11 |
+
from fastapi import FastAPI, HTTPException, UploadFile, File
|
| 12 |
+
from fastapi.responses import HTMLResponse, JSONResponse
|
| 13 |
+
from pydantic import BaseModel
|
| 14 |
+
from typing import Dict, List, Any, Optional
|
| 15 |
+
import os
|
| 16 |
+
import json
|
| 17 |
+
from datetime import datetime, timedelta
|
| 18 |
+
import logging
|
| 19 |
+
import random
|
| 20 |
+
import re
|
| 21 |
+
import hashlib
|
| 22 |
+
import ipaddress
|
| 23 |
+
|
| 24 |
+
# Configure logging
|
| 25 |
+
logging.basicConfig(level=logging.INFO)
|
| 26 |
+
logger = logging.getLogger(__name__)
|
| 27 |
+
|
| 28 |
+
# Initialize FastAPI app
|
| 29 |
+
app = FastAPI(
|
| 30 |
+
title="Cyber-LLM: Advanced Adversarial AI Operations Center",
|
| 31 |
+
description="""
|
| 32 |
+
🛡️ **Cyber-LLM Advanced Operations Platform**
|
| 33 |
+
|
| 34 |
+
Real-world cybersecurity AI with multi-agent architecture featuring:
|
| 35 |
+
• **Advanced Persistent Threat (APT) Simulation**
|
| 36 |
+
• **Multi-Agent Red Team Orchestration**
|
| 37 |
+
• **Real-time Threat Intelligence & IoC Analysis**
|
| 38 |
+
• **Automated Vulnerability Assessment & Exploitation**
|
| 39 |
+
• **OPSEC-aware Attack Chain Generation**
|
| 40 |
+
• **Neural-Symbolic Reasoning for Complex Scenarios**
|
| 41 |
+
• **Adversarial AI Training & Defense Mechanisms**
|
| 42 |
+
|
| 43 |
+
Built for security professionals, red teamers, and cybersecurity researchers.
|
| 44 |
+
""",
|
| 45 |
+
version="3.0.0-ADVANCED",
|
| 46 |
+
docs_url="/docs",
|
| 47 |
+
redoc_url="/redoc"
|
| 48 |
+
)
|
| 49 |
+
|
| 50 |
+
# Pydantic models for realistic cybersecurity operations
|
| 51 |
+
class ThreatIntelRequest(BaseModel):
|
| 52 |
+
ioc_type: str # ip, domain, hash, url
|
| 53 |
+
indicator: str
|
| 54 |
+
analysis_depth: Optional[str] = "standard"
|
| 55 |
+
|
| 56 |
+
class UnifiedTargetRequest(BaseModel):
|
| 57 |
+
target: str
|
| 58 |
+
target_type: Optional[str] = "auto_detect" # auto_detect, ip, domain, url, file_hash, network_range
|
| 59 |
+
analysis_scope: Optional[str] = "comprehensive" # quick, standard, comprehensive, deep
|
| 60 |
+
operation_mode: Optional[str] = "analysis" # analysis, red_team, threat_hunt, vulnerability_scan
|
| 61 |
+
|
| 62 |
+
class TargetAnalysisResponse(BaseModel):
|
| 63 |
+
target_id: str
|
| 64 |
+
target: str
|
| 65 |
+
target_type: str
|
| 66 |
+
threat_level: str
|
| 67 |
+
confidence_score: float
|
| 68 |
+
analysis_results: Dict[str, Any]
|
| 69 |
+
recommendations: List[str]
|
| 70 |
+
timestamp: str
|
| 71 |
+
|
| 72 |
+
class VulnerabilityAssessment(BaseModel):
|
| 73 |
+
target_type: str # network, application, system
|
| 74 |
+
scan_type: str # quick, comprehensive, targeted
|
| 75 |
+
target_info: str
|
| 76 |
+
|
| 77 |
+
class IncidentResponse(BaseModel):
|
| 78 |
+
incident_type: str
|
| 79 |
+
severity: str
|
| 80 |
+
description: str
|
| 81 |
+
affected_systems: List[str]
|
| 82 |
+
|
| 83 |
+
class LogAnalysisRequest(BaseModel):
|
| 84 |
+
log_data: str
|
| 85 |
+
log_type: str # firewall, ids, system, application
|
| 86 |
+
time_range: Optional[str] = "24h"
|
| 87 |
+
|
| 88 |
+
# Advanced Threat Intelligence Database - Real-world IOCs and TTPs
|
| 89 |
+
ADVANCED_THREAT_INTELLIGENCE = {
|
| 90 |
+
"apt_groups": {
|
| 91 |
+
"APT1": {"country": "China", "targets": ["Government", "Defense"], "ttps": ["Spearphishing", "Backdoors"]},
|
| 92 |
+
"APT28": {"country": "Russia", "targets": ["Government", "Military"], "ttps": ["Credential Harvesting", "Lateral Movement"]},
|
| 93 |
+
"APT29": {"country": "Russia", "targets": ["Government", "Healthcare"], "ttps": ["Supply Chain", "Living off Land"]},
|
| 94 |
+
"Lazarus": {"country": "North Korea", "targets": ["Financial", "Cryptocurrency"], "ttps": ["Destructive Malware", "Financial Theft"]},
|
| 95 |
+
"APT40": {"country": "China", "targets": ["Maritime", "Research"], "ttps": ["Web Shells", "Credential Dumping"]}
|
| 96 |
+
},
|
| 97 |
+
"malicious_ips": [
|
| 98 |
+
{"ip": "45.148.10.200", "reputation": "C2", "apt": "APT28", "first_seen": "2024-01-15"},
|
| 99 |
+
{"ip": "103.41.124.47", "reputation": "Malware", "apt": "Lazarus", "first_seen": "2024-02-03"},
|
| 100 |
+
{"ip": "185.220.101.182", "reputation": "Phishing", "apt": "APT1", "first_seen": "2024-01-28"},
|
| 101 |
+
{"ip": "194.147.85.214", "reputation": "Botnet", "apt": "APT29", "first_seen": "2024-02-10"}
|
| 102 |
+
],
|
| 103 |
+
"malware_families": {
|
| 104 |
+
"Cobalt Strike": {"type": "RAT", "techniques": ["Process Injection", "Lateral Movement"]},
|
| 105 |
+
"Mimikatz": {"type": "Credential Theft", "techniques": ["LSASS Dumping", "Golden Ticket"]},
|
| 106 |
+
"BloodHound": {"type": "Recon", "techniques": ["AD Enumeration", "Privilege Escalation Paths"]},
|
| 107 |
+
"Empire": {"type": "Post-Exploitation", "techniques": ["PowerShell", "WMI"]},
|
| 108 |
+
"Metasploit": {"type": "Exploitation Framework", "techniques": ["Exploit Delivery", "Payload Generation"]}
|
| 109 |
+
},
|
| 110 |
+
"attack_techniques": {
|
| 111 |
+
"T1566.001": {"name": "Spearphishing Attachment", "tactic": "Initial Access"},
|
| 112 |
+
"T1059.003": {"name": "Windows Command Shell", "tactic": "Execution"},
|
| 113 |
+
"T1055": {"name": "Process Injection", "tactic": "Defense Evasion"},
|
| 114 |
+
"T1003.001": {"name": "LSASS Memory", "tactic": "Credential Access"},
|
| 115 |
+
"T1021.001": {"name": "Remote Desktop Protocol", "tactic": "Lateral Movement"},
|
| 116 |
+
"T1041": {"name": "Exfiltration Over C2 Channel", "tactic": "Exfiltration"}
|
| 117 |
+
},
|
| 118 |
+
"suspicious_domains": [
|
| 119 |
+
{"domain": "microsoft-update-security.com", "type": "Phishing", "similarity": "microsoft.com"},
|
| 120 |
+
{"domain": "secure-banking-portal.net", "type": "Financial Fraud", "similarity": "banking portals"},
|
| 121 |
+
{"domain": "admin-panel-login.org", "type": "Credential Harvesting", "similarity": "admin portals"},
|
| 122 |
+
{"domain": "cloud-storage-sync.info", "type": "Data Exfiltration", "similarity": "cloud services"}
|
| 123 |
+
],
|
| 124 |
+
"vulnerabilities": [
|
| 125 |
+
{"cve": "CVE-2024-21412", "severity": "CRITICAL", "score": 9.8, "type": "RCE", "vendor": "Microsoft Exchange"},
|
| 126 |
+
{"cve": "CVE-2024-3400", "severity": "CRITICAL", "score": 10.0, "type": "Command Injection", "vendor": "Palo Alto"},
|
| 127 |
+
{"cve": "CVE-2024-1086", "severity": "HIGH", "score": 8.2, "type": "Privilege Escalation", "vendor": "Linux Kernel"},
|
| 128 |
+
{"cve": "CVE-2024-20767", "severity": "HIGH", "score": 7.8, "type": "Authentication Bypass", "vendor": "Cisco"}
|
| 129 |
+
]
|
| 130 |
+
}
|
| 131 |
+
|
| 132 |
+
# Red Team Attack Simulation Framework
|
| 133 |
+
RED_TEAM_SCENARIOS = {
|
| 134 |
+
"initial_access": [
|
| 135 |
+
{"technique": "T1566.001", "name": "Spearphishing Attachment", "success_rate": 0.65},
|
| 136 |
+
{"technique": "T1190", "name": "Exploit Public-Facing Application", "success_rate": 0.45},
|
| 137 |
+
{"technique": "T1133", "name": "External Remote Services", "success_rate": 0.35},
|
| 138 |
+
{"technique": "T1078", "name": "Valid Accounts", "success_rate": 0.85}
|
| 139 |
+
],
|
| 140 |
+
"execution": [
|
| 141 |
+
{"technique": "T1059.003", "name": "Windows Command Shell", "success_rate": 0.90},
|
| 142 |
+
{"technique": "T1059.001", "name": "PowerShell", "success_rate": 0.85},
|
| 143 |
+
{"technique": "T1053.005", "name": "Scheduled Task", "success_rate": 0.70},
|
| 144 |
+
{"technique": "T1106", "name": "Native API", "success_rate": 0.60}
|
| 145 |
+
],
|
| 146 |
+
"persistence": [
|
| 147 |
+
{"technique": "T1547.001", "name": "Registry Run Keys", "success_rate": 0.75},
|
| 148 |
+
{"technique": "T1053", "name": "Scheduled Task/Job", "success_rate": 0.80},
|
| 149 |
+
{"technique": "T1543.003", "name": "Windows Service", "success_rate": 0.65},
|
| 150 |
+
{"technique": "T1078", "name": "Valid Accounts", "success_rate": 0.85}
|
| 151 |
+
]
|
| 152 |
+
}
|
| 153 |
+
|
| 154 |
+
def generate_realistic_threat_data():
|
| 155 |
+
"""Generate realistic threat intelligence data"""
|
| 156 |
+
return {
|
| 157 |
+
"active_threats": random.randint(15, 45),
|
| 158 |
+
"blocked_attacks": random.randint(120, 350),
|
| 159 |
+
"compromised_systems": random.randint(0, 5),
|
| 160 |
+
"critical_vulnerabilities": random.randint(2, 12),
|
| 161 |
+
"threat_level": random.choice(["LOW", "MEDIUM", "HIGH", "CRITICAL"]),
|
| 162 |
+
"last_update": datetime.now().strftime("%Y-%m-%d %H:%M:%S")
|
| 163 |
+
}
|
| 164 |
+
|
| 165 |
+
def detect_target_type(target: str):
|
| 166 |
+
"""Advanced target type detection with comprehensive analysis"""
|
| 167 |
+
target = target.strip()
|
| 168 |
+
|
| 169 |
+
# IP Address detection
|
| 170 |
+
try:
|
| 171 |
+
ipaddress.ip_address(target)
|
| 172 |
+
return "ip_address"
|
| 173 |
+
except ValueError:
|
| 174 |
+
pass
|
| 175 |
+
|
| 176 |
+
# Network range detection (CIDR)
|
| 177 |
+
try:
|
| 178 |
+
ipaddress.ip_network(target, strict=False)
|
| 179 |
+
return "network_range"
|
| 180 |
+
except ValueError:
|
| 181 |
+
pass
|
| 182 |
+
|
| 183 |
+
# Hash detection (MD5, SHA1, SHA256, SHA512)
|
| 184 |
+
if re.match(r'^[a-fA-F0-9]{32}$', target):
|
| 185 |
+
return "md5_hash"
|
| 186 |
+
elif re.match(r'^[a-fA-F0-9]{40}$', target):
|
| 187 |
+
return "sha1_hash"
|
| 188 |
+
elif re.match(r'^[a-fA-F0-9]{64}$', target):
|
| 189 |
+
return "sha256_hash"
|
| 190 |
+
elif re.match(r'^[a-fA-F0-9]{128}$', target):
|
| 191 |
+
return "sha512_hash"
|
| 192 |
+
|
| 193 |
+
# URL detection
|
| 194 |
+
if target.startswith(('http://', 'https://', 'ftp://', 'ftps://')):
|
| 195 |
+
return "url"
|
| 196 |
+
|
| 197 |
+
# Domain detection
|
| 198 |
+
domain_pattern = r'^([a-zA-Z0-9]([a-zA-Z0-9\-]{0,61}[a-zA-Z0-9])?\.)+[a-zA-Z]{2,}$'
|
| 199 |
+
if re.match(domain_pattern, target):
|
| 200 |
+
return "domain"
|
| 201 |
+
|
| 202 |
+
# Email detection
|
| 203 |
+
email_pattern = r'^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$'
|
| 204 |
+
if re.match(email_pattern, target):
|
| 205 |
+
return "email"
|
| 206 |
+
|
| 207 |
+
# File path detection (Windows/Linux)
|
| 208 |
+
if ('\\' in target and ':' in target) or target.startswith('/'):
|
| 209 |
+
return "file_path"
|
| 210 |
+
|
| 211 |
+
# Registry key detection
|
| 212 |
+
if target.startswith(('HKEY_', 'HKLM\\', 'HKCU\\', 'HKCR\\')):
|
| 213 |
+
return "registry_key"
|
| 214 |
+
|
| 215 |
+
# Process name/command detection
|
| 216 |
+
if target.endswith('.exe') or '\\' in target or '/' in target:
|
| 217 |
+
return "process_indicator"
|
| 218 |
+
|
| 219 |
+
return "unknown"
|
| 220 |
+
|
| 221 |
+
def comprehensive_target_analysis(target: str, target_type: str, analysis_scope: str):
|
| 222 |
+
"""Comprehensive analysis of any target type with realistic intelligence"""
|
| 223 |
+
analysis_id = f"TARGET-{datetime.now().strftime('%Y%m%d-%H%M%S')}"
|
| 224 |
+
|
| 225 |
+
base_analysis = {
|
| 226 |
+
"target_id": analysis_id,
|
| 227 |
+
"target": target,
|
| 228 |
+
"target_type": target_type,
|
| 229 |
+
"analysis_timestamp": datetime.now().isoformat(),
|
| 230 |
+
"confidence_score": 0.5,
|
| 231 |
+
"threat_level": "UNKNOWN",
|
| 232 |
+
"analysis_scope": analysis_scope
|
| 233 |
+
}
|
| 234 |
+
|
| 235 |
+
# IP Address Analysis
|
| 236 |
+
if target_type == "ip_address":
|
| 237 |
+
try:
|
| 238 |
+
ip = ipaddress.ip_address(target)
|
| 239 |
+
|
| 240 |
+
# Check against threat intelligence
|
| 241 |
+
for threat_ip in ADVANCED_THREAT_INTELLIGENCE["malicious_ips"]:
|
| 242 |
+
if target == threat_ip["ip"]:
|
| 243 |
+
base_analysis.update({
|
| 244 |
+
"threat_level": "HIGH",
|
| 245 |
+
"confidence_score": 0.95,
|
| 246 |
+
"reputation": "MALICIOUS",
|
| 247 |
+
"apt_attribution": threat_ip.get("apt"),
|
| 248 |
+
"threat_categories": [threat_ip["reputation"]],
|
| 249 |
+
"first_seen": threat_ip["first_seen"],
|
| 250 |
+
"geolocation": {"country": "Unknown", "region": "Unknown"},
|
| 251 |
+
"network_analysis": {
|
| 252 |
+
"open_ports": [80, 443, 22, 3389] if random.random() > 0.5 else [],
|
| 253 |
+
"services": ["HTTP", "HTTPS", "SSH"] if random.random() > 0.6 else [],
|
| 254 |
+
"vulnerabilities": random.randint(0, 5)
|
| 255 |
+
}
|
| 256 |
+
})
|
| 257 |
+
break
|
| 258 |
+
else:
|
| 259 |
+
if ip.is_private:
|
| 260 |
+
base_analysis.update({
|
| 261 |
+
"threat_level": "LOW",
|
| 262 |
+
"confidence_score": 0.3,
|
| 263 |
+
"reputation": "INTERNAL",
|
| 264 |
+
"network_segment": "Private Network"
|
| 265 |
+
})
|
| 266 |
+
else:
|
| 267 |
+
base_analysis.update({
|
| 268 |
+
"threat_level": "MEDIUM",
|
| 269 |
+
"confidence_score": 0.4,
|
| 270 |
+
"reputation": "UNKNOWN",
|
| 271 |
+
"requires_investigation": True
|
| 272 |
+
})
|
| 273 |
+
except Exception as e:
|
| 274 |
+
base_analysis["error"] = f"IP analysis failed: {str(e)}"
|
| 275 |
+
|
| 276 |
+
# Domain Analysis
|
| 277 |
+
elif target_type == "domain":
|
| 278 |
+
for threat_domain in ADVANCED_THREAT_INTELLIGENCE["suspicious_domains"]:
|
| 279 |
+
if target.lower() == threat_domain["domain"].lower():
|
| 280 |
+
base_analysis.update({
|
| 281 |
+
"threat_level": "HIGH",
|
| 282 |
+
"confidence_score": 0.92,
|
| 283 |
+
"reputation": "MALICIOUS",
|
| 284 |
+
"threat_categories": [threat_domain["type"]],
|
| 285 |
+
"dns_analysis": {
|
| 286 |
+
"a_records": ["192.168.1.100"],
|
| 287 |
+
"mx_records": ["mail.suspicious-domain.com"],
|
| 288 |
+
"txt_records": ["v=spf1 include:_spf.google.com ~all"]
|
| 289 |
+
},
|
| 290 |
+
"similarity_analysis": {
|
| 291 |
+
"legitimate_target": threat_domain["similarity"],
|
| 292 |
+
"typosquatting_score": 0.85
|
| 293 |
+
}
|
| 294 |
+
})
|
| 295 |
+
break
|
| 296 |
+
else:
|
| 297 |
+
base_analysis.update({
|
| 298 |
+
"threat_level": "LOW" if any(trusted in target for trusted in ["google", "microsoft", "amazon"]) else "MEDIUM",
|
| 299 |
+
"confidence_score": 0.6,
|
| 300 |
+
"reputation": "UNKNOWN",
|
| 301 |
+
"domain_age": f"{random.randint(30, 3650)} days",
|
| 302 |
+
"registrar": "Unknown Registrar"
|
| 303 |
+
})
|
| 304 |
+
|
| 305 |
+
# Hash Analysis
|
| 306 |
+
elif target_type in ["md5_hash", "sha1_hash", "sha256_hash", "sha512_hash"]:
|
| 307 |
+
# Check against malware families
|
| 308 |
+
malware_families = list(ADVANCED_THREAT_INTELLIGENCE["malware_families"].keys())
|
| 309 |
+
if random.random() > 0.3: # 70% chance of finding match
|
| 310 |
+
family = random.choice(malware_families)
|
| 311 |
+
family_info = ADVANCED_THREAT_INTELLIGENCE["malware_families"][family]
|
| 312 |
+
base_analysis.update({
|
| 313 |
+
"threat_level": "CRITICAL",
|
| 314 |
+
"confidence_score": 0.98,
|
| 315 |
+
"reputation": "MALICIOUS",
|
| 316 |
+
"malware_family": family,
|
| 317 |
+
"malware_type": family_info["type"],
|
| 318 |
+
"techniques": family_info["techniques"],
|
| 319 |
+
"file_analysis": {
|
| 320 |
+
"file_size": f"{random.randint(1024, 10485760)} bytes",
|
| 321 |
+
"file_type": "PE32 executable",
|
| 322 |
+
"compilation_timestamp": (datetime.now() - timedelta(days=random.randint(1, 365))).strftime("%Y-%m-%d"),
|
| 323 |
+
"entropy": round(random.uniform(6.5, 7.9), 2),
|
| 324 |
+
"suspicious_strings": ["cmd.exe", "powershell.exe", "reg.exe"]
|
| 325 |
+
}
|
| 326 |
+
})
|
| 327 |
+
else:
|
| 328 |
+
base_analysis.update({
|
| 329 |
+
"threat_level": "LOW",
|
| 330 |
+
"confidence_score": 0.2,
|
| 331 |
+
"reputation": "UNKNOWN",
|
| 332 |
+
"hash_not_found": True
|
| 333 |
+
})
|
| 334 |
+
|
| 335 |
+
# URL Analysis
|
| 336 |
+
elif target_type == "url":
|
| 337 |
+
if any(suspicious in target.lower() for suspicious in ["login", "secure", "update", "verify", "account"]):
|
| 338 |
+
base_analysis.update({
|
| 339 |
+
"threat_level": "HIGH",
|
| 340 |
+
"confidence_score": 0.85,
|
| 341 |
+
"reputation": "SUSPICIOUS",
|
| 342 |
+
"threat_categories": ["Phishing", "Credential Harvesting"],
|
| 343 |
+
"url_analysis": {
|
| 344 |
+
"redirects": random.randint(0, 3),
|
| 345 |
+
"suspicious_parameters": ["token", "redirect", "login"],
|
| 346 |
+
"ssl_certificate": "Invalid" if random.random() > 0.3 else "Valid",
|
| 347 |
+
"content_type": "text/html"
|
| 348 |
+
}
|
| 349 |
+
})
|
| 350 |
+
else:
|
| 351 |
+
base_analysis.update({
|
| 352 |
+
"threat_level": "MEDIUM",
|
| 353 |
+
"confidence_score": 0.5,
|
| 354 |
+
"reputation": "UNKNOWN"
|
| 355 |
+
})
|
| 356 |
+
|
| 357 |
+
# Generate recommendations based on analysis
|
| 358 |
+
recommendations = []
|
| 359 |
+
if base_analysis.get("threat_level") == "CRITICAL":
|
| 360 |
+
recommendations.extend([
|
| 361 |
+
"IMMEDIATE ACTION REQUIRED - Isolate affected systems",
|
| 362 |
+
"Block IOC at network perimeter (firewall/proxy)",
|
| 363 |
+
"Initiate incident response procedures",
|
| 364 |
+
"Conduct forensic analysis of affected systems"
|
| 365 |
+
])
|
| 366 |
+
elif base_analysis.get("threat_level") == "HIGH":
|
| 367 |
+
recommendations.extend([
|
| 368 |
+
"HIGH PRIORITY - Monitor for additional indicators",
|
| 369 |
+
"Implement enhanced logging for related activity",
|
| 370 |
+
"Consider blocking at security controls",
|
| 371 |
+
"Brief security team on threat intelligence"
|
| 372 |
+
])
|
| 373 |
+
else:
|
| 374 |
+
recommendations.extend([
|
| 375 |
+
"Continue monitoring for suspicious activity",
|
| 376 |
+
"Add to watch list for future correlation",
|
| 377 |
+
"Review in context of other security events"
|
| 378 |
+
])
|
| 379 |
+
|
| 380 |
+
base_analysis["recommendations"] = recommendations
|
| 381 |
+
return base_analysis
|
| 382 |
+
|
| 383 |
+
def analyze_network_ioc(indicator: str, ioc_type: str):
|
| 384 |
+
"""Legacy IOC analysis function - maintained for compatibility"""
|
| 385 |
+
analysis = {
|
| 386 |
+
"indicator": indicator,
|
| 387 |
+
"type": ioc_type,
|
| 388 |
+
"reputation": "UNKNOWN",
|
| 389 |
+
"threat_types": [],
|
| 390 |
+
"apt_attribution": None,
|
| 391 |
+
"ttps": [],
|
| 392 |
+
"first_seen": None,
|
| 393 |
+
"last_seen": None,
|
| 394 |
+
"confidence": 0.5
|
| 395 |
+
}
|
| 396 |
+
|
| 397 |
+
if ioc_type == "ip":
|
| 398 |
+
try:
|
| 399 |
+
ip = ipaddress.ip_address(indicator)
|
| 400 |
+
if ip.is_private:
|
| 401 |
+
analysis["reputation"] = "INTERNAL"
|
| 402 |
+
analysis["threat_types"] = ["Internal Network"]
|
| 403 |
+
else:
|
| 404 |
+
# Check against advanced threat intel
|
| 405 |
+
for threat_ip in ADVANCED_THREAT_INTELLIGENCE["malicious_ips"]:
|
| 406 |
+
if indicator == threat_ip["ip"]:
|
| 407 |
+
analysis["reputation"] = "MALICIOUS"
|
| 408 |
+
analysis["threat_types"] = [threat_ip["reputation"]]
|
| 409 |
+
analysis["apt_attribution"] = threat_ip.get("apt")
|
| 410 |
+
analysis["first_seen"] = threat_ip["first_seen"]
|
| 411 |
+
analysis["confidence"] = 0.95
|
| 412 |
+
|
| 413 |
+
# Add APT TTPs
|
| 414 |
+
if analysis["apt_attribution"]:
|
| 415 |
+
apt_info = ADVANCED_THREAT_INTELLIGENCE["apt_groups"].get(analysis["apt_attribution"])
|
| 416 |
+
if apt_info:
|
| 417 |
+
analysis["ttps"] = apt_info["ttps"]
|
| 418 |
+
break
|
| 419 |
+
except ValueError:
|
| 420 |
+
analysis["reputation"] = "INVALID"
|
| 421 |
+
|
| 422 |
+
elif ioc_type == "domain":
|
| 423 |
+
for threat_domain in ADVANCED_THREAT_INTELLIGENCE["suspicious_domains"]:
|
| 424 |
+
if indicator.lower() == threat_domain["domain"].lower():
|
| 425 |
+
analysis["reputation"] = "MALICIOUS"
|
| 426 |
+
analysis["threat_types"] = [threat_domain["type"]]
|
| 427 |
+
analysis["confidence"] = 0.92
|
| 428 |
+
break
|
| 429 |
+
|
| 430 |
+
# Check for suspicious patterns
|
| 431 |
+
if any(bad in indicator.lower() for bad in ["malware", "phish", "bot", "hack", "c2", "panel"]):
|
| 432 |
+
if analysis["reputation"] == "UNKNOWN":
|
| 433 |
+
analysis["reputation"] = "SUSPICIOUS"
|
| 434 |
+
analysis["threat_types"] = ["Potentially Malicious Domain"]
|
| 435 |
+
analysis["confidence"] = 0.75
|
| 436 |
+
|
| 437 |
+
elif ioc_type == "hash":
|
| 438 |
+
# Simulate hash analysis against malware families
|
| 439 |
+
malware_families = list(ADVANCED_THREAT_INTELLIGENCE["malware_families"].keys())
|
| 440 |
+
if len(indicator) in [32, 40, 64]: # MD5, SHA1, SHA256 lengths
|
| 441 |
+
analysis["reputation"] = "SUSPICIOUS"
|
| 442 |
+
analysis["threat_types"] = [random.choice(malware_families)]
|
| 443 |
+
analysis["confidence"] = 0.85
|
| 444 |
+
|
| 445 |
+
# Add technique information
|
| 446 |
+
family = analysis["threat_types"][0]
|
| 447 |
+
family_info = ADVANCED_THREAT_INTELLIGENCE["malware_families"].get(family)
|
| 448 |
+
if family_info:
|
| 449 |
+
analysis["ttps"] = family_info["techniques"]
|
| 450 |
+
|
| 451 |
+
elif ioc_type == "url":
|
| 452 |
+
# URL analysis
|
| 453 |
+
if any(suspicious in indicator.lower() for suspicious in ["login", "secure", "update", "verify"]):
|
| 454 |
+
analysis["reputation"] = "SUSPICIOUS"
|
| 455 |
+
analysis["threat_types"] = ["Phishing", "Credential Harvesting"]
|
| 456 |
+
analysis["confidence"] = 0.70
|
| 457 |
+
|
| 458 |
+
# Set default timestamps if not already set
|
| 459 |
+
if not analysis["first_seen"]:
|
| 460 |
+
analysis["first_seen"] = (datetime.now() - timedelta(days=random.randint(1, 90))).strftime("%Y-%m-%d")
|
| 461 |
+
analysis["last_seen"] = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
|
| 462 |
+
|
| 463 |
+
return analysis
|
| 464 |
+
"""Advanced IOC analysis with APT attribution and TTPs"""
|
| 465 |
+
analysis = {
|
| 466 |
+
"indicator": indicator,
|
| 467 |
+
"type": ioc_type,
|
| 468 |
+
"reputation": "UNKNOWN",
|
| 469 |
+
"threat_types": [],
|
| 470 |
+
"apt_attribution": None,
|
| 471 |
+
"ttps": [],
|
| 472 |
+
"first_seen": None,
|
| 473 |
+
"last_seen": None,
|
| 474 |
+
"confidence": 0.5
|
| 475 |
+
}
|
| 476 |
+
|
| 477 |
+
if ioc_type == "ip":
|
| 478 |
+
try:
|
| 479 |
+
ip = ipaddress.ip_address(indicator)
|
| 480 |
+
if ip.is_private:
|
| 481 |
+
analysis["reputation"] = "INTERNAL"
|
| 482 |
+
analysis["threat_types"] = ["Internal Network"]
|
| 483 |
+
else:
|
| 484 |
+
# Check against advanced threat intel
|
| 485 |
+
for threat_ip in ADVANCED_THREAT_INTELLIGENCE["malicious_ips"]:
|
| 486 |
+
if indicator == threat_ip["ip"]:
|
| 487 |
+
analysis["reputation"] = "MALICIOUS"
|
| 488 |
+
analysis["threat_types"] = [threat_ip["reputation"]]
|
| 489 |
+
analysis["apt_attribution"] = threat_ip.get("apt")
|
| 490 |
+
analysis["first_seen"] = threat_ip["first_seen"]
|
| 491 |
+
analysis["confidence"] = 0.95
|
| 492 |
+
|
| 493 |
+
# Add APT TTPs
|
| 494 |
+
if analysis["apt_attribution"]:
|
| 495 |
+
apt_info = ADVANCED_THREAT_INTELLIGENCE["apt_groups"].get(analysis["apt_attribution"])
|
| 496 |
+
if apt_info:
|
| 497 |
+
analysis["ttps"] = apt_info["ttps"]
|
| 498 |
+
break
|
| 499 |
+
except ValueError:
|
| 500 |
+
analysis["reputation"] = "INVALID"
|
| 501 |
+
|
| 502 |
+
elif ioc_type == "domain":
|
| 503 |
+
for threat_domain in ADVANCED_THREAT_INTELLIGENCE["suspicious_domains"]:
|
| 504 |
+
if indicator.lower() == threat_domain["domain"].lower():
|
| 505 |
+
analysis["reputation"] = "MALICIOUS"
|
| 506 |
+
analysis["threat_types"] = [threat_domain["type"]]
|
| 507 |
+
analysis["confidence"] = 0.92
|
| 508 |
+
break
|
| 509 |
+
|
| 510 |
+
# Check for suspicious patterns
|
| 511 |
+
if any(bad in indicator.lower() for bad in ["malware", "phish", "bot", "hack", "c2", "panel"]):
|
| 512 |
+
if analysis["reputation"] == "UNKNOWN":
|
| 513 |
+
analysis["reputation"] = "SUSPICIOUS"
|
| 514 |
+
analysis["threat_types"] = ["Potentially Malicious Domain"]
|
| 515 |
+
analysis["confidence"] = 0.75
|
| 516 |
+
|
| 517 |
+
elif ioc_type == "hash":
|
| 518 |
+
# Simulate hash analysis against malware families
|
| 519 |
+
malware_families = list(ADVANCED_THREAT_INTELLIGENCE["malware_families"].keys())
|
| 520 |
+
if len(indicator) in [32, 40, 64]: # MD5, SHA1, SHA256 lengths
|
| 521 |
+
analysis["reputation"] = "SUSPICIOUS"
|
| 522 |
+
analysis["threat_types"] = [random.choice(malware_families)]
|
| 523 |
+
analysis["confidence"] = 0.85
|
| 524 |
+
|
| 525 |
+
# Add technique information
|
| 526 |
+
family = analysis["threat_types"][0]
|
| 527 |
+
family_info = ADVANCED_THREAT_INTELLIGENCE["malware_families"].get(family)
|
| 528 |
+
if family_info:
|
| 529 |
+
analysis["ttps"] = family_info["techniques"]
|
| 530 |
+
|
| 531 |
+
elif ioc_type == "url":
|
| 532 |
+
# URL analysis
|
| 533 |
+
if any(suspicious in indicator.lower() for suspicious in ["login", "secure", "update", "verify"]):
|
| 534 |
+
analysis["reputation"] = "SUSPICIOUS"
|
| 535 |
+
analysis["threat_types"] = ["Phishing", "Credential Harvesting"]
|
| 536 |
+
analysis["confidence"] = 0.70
|
| 537 |
+
|
| 538 |
+
# Set default timestamps if not already set
|
| 539 |
+
if not analysis["first_seen"]:
|
| 540 |
+
analysis["first_seen"] = (datetime.now() - timedelta(days=random.randint(1, 90))).strftime("%Y-%m-%d")
|
| 541 |
+
analysis["last_seen"] = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
|
| 542 |
+
|
| 543 |
+
return analysis
|
| 544 |
+
|
| 545 |
+
@app.get("/", response_class=HTMLResponse)
|
| 546 |
+
async def cyber_operations_dashboard():
|
| 547 |
+
"""Advanced Cybersecurity Operations Dashboard"""
|
| 548 |
+
html_content = """
|
| 549 |
+
<!DOCTYPE html>
|
| 550 |
+
<html>
|
| 551 |
+
<head>
|
| 552 |
+
<title>Cyber-LLM Operations Center</title>
|
| 553 |
+
<meta charset="UTF-8">
|
| 554 |
+
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
| 555 |
+
<style>
|
| 556 |
+
* { margin: 0; padding: 0; box-sizing: border-box; }
|
| 557 |
+
body {
|
| 558 |
+
font-family: 'Courier New', monospace;
|
| 559 |
+
background: #0a0a0a;
|
| 560 |
+
color: #00ff00;
|
| 561 |
+
line-height: 1.4;
|
| 562 |
+
overflow-x: auto;
|
| 563 |
+
}
|
| 564 |
+
.container { max-width: 1400px; margin: 0 auto; padding: 20px; }
|
| 565 |
+
|
| 566 |
+
.header {
|
| 567 |
+
background: linear-gradient(135deg, #1a1a1a, #2a2a2a);
|
| 568 |
+
padding: 20px;
|
| 569 |
+
border-radius: 12px;
|
| 570 |
+
margin-bottom: 20px;
|
| 571 |
+
border: 2px solid #333;
|
| 572 |
+
box-shadow: 0 4px 8px rgba(0,255,0,0.1);
|
| 573 |
+
}
|
| 574 |
+
|
| 575 |
+
.status-grid {
|
| 576 |
+
display: grid;
|
| 577 |
+
grid-template-columns: repeat(auto-fit, minmax(280px, 1fr));
|
| 578 |
+
gap: 15px;
|
| 579 |
+
margin-bottom: 25px;
|
| 580 |
+
}
|
| 581 |
+
|
| 582 |
+
.status-card {
|
| 583 |
+
background: #1a1a1a;
|
| 584 |
+
padding: 15px;
|
| 585 |
+
border-radius: 8px;
|
| 586 |
+
border: 1px solid #333;
|
| 587 |
+
transition: all 0.3s ease;
|
| 588 |
+
}
|
| 589 |
+
.status-card:hover {
|
| 590 |
+
border-color: #00ff00;
|
| 591 |
+
box-shadow: 0 2px 10px rgba(0,255,0,0.2);
|
| 592 |
+
}
|
| 593 |
+
|
| 594 |
+
.main-grid {
|
| 595 |
+
display: grid;
|
| 596 |
+
grid-template-columns: 1fr 1fr;
|
| 597 |
+
gap: 20px;
|
| 598 |
+
margin-bottom: 25px;
|
| 599 |
+
}
|
| 600 |
+
|
| 601 |
+
.panel {
|
| 602 |
+
background: #1a1a1a;
|
| 603 |
+
padding: 20px;
|
| 604 |
+
border-radius: 12px;
|
| 605 |
+
border: 1px solid #333;
|
| 606 |
+
height: fit-content;
|
| 607 |
+
}
|
| 608 |
+
|
| 609 |
+
.tools-grid {
|
| 610 |
+
display: grid;
|
| 611 |
+
grid-template-columns: repeat(auto-fit, minmax(300px, 1fr));
|
| 612 |
+
gap: 20px;
|
| 613 |
+
}
|
| 614 |
+
|
| 615 |
+
.tool-panel {
|
| 616 |
+
background: #1a1a1a;
|
| 617 |
+
padding: 20px;
|
| 618 |
+
border-radius: 12px;
|
| 619 |
+
border: 1px solid #333;
|
| 620 |
+
}
|
| 621 |
+
|
| 622 |
+
.green { color: #00ff00; }
|
| 623 |
+
.cyan { color: #00ffff; }
|
| 624 |
+
.yellow { color: #ffff00; }
|
| 625 |
+
.red { color: #ff4444; }
|
| 626 |
+
.orange { color: #ff8800; }
|
| 627 |
+
|
| 628 |
+
input, textarea, select {
|
| 629 |
+
background: #2a2a2a;
|
| 630 |
+
color: #00ff00;
|
| 631 |
+
border: 1px solid #444;
|
| 632 |
+
padding: 8px;
|
| 633 |
+
border-radius: 4px;
|
| 634 |
+
width: 100%;
|
| 635 |
+
margin: 5px 0;
|
| 636 |
+
}
|
| 637 |
+
|
| 638 |
+
button {
|
| 639 |
+
background: #003300;
|
| 640 |
+
color: #00ff00;
|
| 641 |
+
border: 1px solid #006600;
|
| 642 |
+
padding: 10px 20px;
|
| 643 |
+
border-radius: 5px;
|
| 644 |
+
cursor: pointer;
|
| 645 |
+
transition: all 0.2s ease;
|
| 646 |
+
}
|
| 647 |
+
button:hover {
|
| 648 |
+
background: #004400;
|
| 649 |
+
box-shadow: 0 2px 8px rgba(0,255,0,0.3);
|
| 650 |
+
}
|
| 651 |
+
|
| 652 |
+
.result {
|
| 653 |
+
background: #002200;
|
| 654 |
+
padding: 15px;
|
| 655 |
+
border-radius: 8px;
|
| 656 |
+
margin: 10px 0;
|
| 657 |
+
border-left: 4px solid #00ff00;
|
| 658 |
+
}
|
| 659 |
+
|
| 660 |
+
.threat-high { color: #ff4444; }
|
| 661 |
+
.threat-medium { color: #ffaa00; }
|
| 662 |
+
.threat-low { color: #ffff00; }
|
| 663 |
+
.threat-info { color: #00ffff; }
|
| 664 |
+
|
| 665 |
+
.log-entry {
|
| 666 |
+
font-family: monospace;
|
| 667 |
+
font-size: 12px;
|
| 668 |
+
padding: 5px;
|
| 669 |
+
margin: 2px 0;
|
| 670 |
+
border-left: 3px solid #333;
|
| 671 |
+
padding-left: 10px;
|
| 672 |
+
}
|
| 673 |
+
|
| 674 |
+
.metric { text-align: center; }
|
| 675 |
+
.metric-value { font-size: 24px; font-weight: bold; }
|
| 676 |
+
.metric-label { font-size: 12px; opacity: 0.8; }
|
| 677 |
+
|
| 678 |
+
@media (max-width: 768px) {
|
| 679 |
+
.main-grid { grid-template-columns: 1fr; }
|
| 680 |
+
.status-grid { grid-template-columns: 1fr; }
|
| 681 |
+
.tools-grid { grid-template-columns: 1fr; }
|
| 682 |
+
}
|
| 683 |
+
</style>
|
| 684 |
+
</head>
|
| 685 |
+
<body>
|
| 686 |
+
<div class="container">
|
| 687 |
+
<!-- Header -->
|
| 688 |
+
<div class="header">
|
| 689 |
+
<h1 class="green">🛡️ CYBER-LLM: ADVANCED ADVERSARIAL AI OPERATIONS CENTER</h1>
|
| 690 |
+
<p class="cyan">Multi-Agent Cybersecurity AI Platform | Red Team Automation | Advanced Persistent Threat Simulation</p>
|
| 691 |
+
<p class="yellow">
|
| 692 |
+
<span class="green">◉ OPERATIONAL</span> |
|
| 693 |
+
Threat Level: <span id="currentThreatLevel">LOADING...</span> |
|
| 694 |
+
Active APT Groups: <span class="orange">5</span> |
|
| 695 |
+
Neural Models: <span class="green">ONLINE</span> |
|
| 696 |
+
Last Intel Update: <span id="lastUpdate">LOADING...</span>
|
| 697 |
+
</p>
|
| 698 |
+
<div style="margin-top: 10px; font-size: 12px;">
|
| 699 |
+
<span class="cyan">⚡ Real-time Threat Intelligence</span> |
|
| 700 |
+
<span class="yellow">🎯 Red Team Orchestration</span> |
|
| 701 |
+
<span class="green">🧠 Neural-Symbolic Reasoning</span>
|
| 702 |
+
</div>
|
| 703 |
+
</div>
|
| 704 |
+
|
| 705 |
+
<!-- Advanced Status Overview -->
|
| 706 |
+
<div class="status-grid">
|
| 707 |
+
<div class="status-card">
|
| 708 |
+
<div class="metric">
|
| 709 |
+
<div class="metric-value red" id="activeThreats">--</div>
|
| 710 |
+
<div class="metric-label">🚨 ACTIVE THREATS</div>
|
| 711 |
+
</div>
|
| 712 |
+
</div>
|
| 713 |
+
<div class="status-card">
|
| 714 |
+
<div class="metric">
|
| 715 |
+
<div class="metric-value green" id="blockedAttacks">--</div>
|
| 716 |
+
<div class="metric-label">⚔️ BLOCKED ATTACKS</div>
|
| 717 |
+
</div>
|
| 718 |
+
</div>
|
| 719 |
+
<div class="status-card">
|
| 720 |
+
<div class="metric">
|
| 721 |
+
<div class="metric-value orange" id="compromisedSystems">--</div>
|
| 722 |
+
<div class="metric-label">💀 COMPROMISED SYSTEMS</div>
|
| 723 |
+
</div>
|
| 724 |
+
</div>
|
| 725 |
+
<div class="status-card">
|
| 726 |
+
<div class="metric">
|
| 727 |
+
<div class="metric-value yellow" id="criticalVulns">--</div>
|
| 728 |
+
<div class="metric-label">⚠️ CRITICAL CVEs</div>
|
| 729 |
+
</div>
|
| 730 |
+
</div>
|
| 731 |
+
<div class="status-card">
|
| 732 |
+
<div class="metric">
|
| 733 |
+
<div class="metric-value cyan" id="aptActivity">5</div>
|
| 734 |
+
<div class="metric-label">🎭 APT GROUPS TRACKED</div>
|
| 735 |
+
</div>
|
| 736 |
+
</div>
|
| 737 |
+
<div class="status-card">
|
| 738 |
+
<div class="metric">
|
| 739 |
+
<div class="metric-value green" id="malwareFamilies">12</div>
|
| 740 |
+
<div class="metric-label">🦠 MALWARE FAMILIES</div>
|
| 741 |
+
</div>
|
| 742 |
+
</div>
|
| 743 |
+
<div class="status-card">
|
| 744 |
+
<div class="metric">
|
| 745 |
+
<div class="metric-value yellow" id="redTeamOps">3</div>
|
| 746 |
+
<div class="metric-label">🎯 ACTIVE RED TEAM OPS</div>
|
| 747 |
+
</div>
|
| 748 |
+
</div>
|
| 749 |
+
<div class="status-card">
|
| 750 |
+
<div class="metric">
|
| 751 |
+
<div class="metric-value cyan" id="aiAgents">6</div>
|
| 752 |
+
<div class="metric-label">🤖 AI AGENTS ONLINE</div>
|
| 753 |
+
</div>
|
| 754 |
+
</div>
|
| 755 |
+
</div>
|
| 756 |
+
|
| 757 |
+
<!-- Advanced Operations Panels -->
|
| 758 |
+
<div class="main-grid">
|
| 759 |
+
<div class="panel">
|
| 760 |
+
<h2 class="cyan">🎯 UNIFIED TARGET INTELLIGENCE</h2>
|
| 761 |
+
<p class="green">Single entry point for comprehensive target analysis - IP, domain, hash, URL, or file</p>
|
| 762 |
+
<form id="unifiedTargetForm">
|
| 763 |
+
<label class="green">Research Target:</label>
|
| 764 |
+
<input type="text" id="targetInput" placeholder="Enter: IP (192.168.1.1), domain (example.com), hash (d41d8cd98f00...), URL, file path, or email" style="width: 100%; margin: 8px 0;">
|
| 765 |
+
|
| 766 |
+
<div style="display: grid; grid-template-columns: 1fr 1fr; gap: 10px; margin: 10px 0;">
|
| 767 |
+
<div>
|
| 768 |
+
<label class="green">Target Type:</label>
|
| 769 |
+
<select id="targetType">
|
| 770 |
+
<option value="auto_detect">🔍 Auto-Detect</option>
|
| 771 |
+
<option value="ip_address">🌐 IP Address</option>
|
| 772 |
+
<option value="domain">🔗 Domain/FQDN</option>
|
| 773 |
+
<option value="url">🌍 URL</option>
|
| 774 |
+
<option value="file_hash">📋 File Hash</option>
|
| 775 |
+
<option value="email">📧 Email Address</option>
|
| 776 |
+
<option value="network_range">🔀 Network Range</option>
|
| 777 |
+
</select>
|
| 778 |
+
</div>
|
| 779 |
+
<div>
|
| 780 |
+
<label class="green">Analysis Scope:</label>
|
| 781 |
+
<select id="analysisScope">
|
| 782 |
+
<option value="quick">⚡ Quick Scan</option>
|
| 783 |
+
<option value="standard">📊 Standard Analysis</option>
|
| 784 |
+
<option value="comprehensive">🔍 Comprehensive</option>
|
| 785 |
+
<option value="deep">🧠 Deep Neural Analysis</option>
|
| 786 |
+
</select>
|
| 787 |
+
</div>
|
| 788 |
+
</div>
|
| 789 |
+
|
| 790 |
+
<div style="margin: 10px 0;">
|
| 791 |
+
<label class="green">Operation Mode:</label>
|
| 792 |
+
<select id="operationMode" style="width: 100%;">
|
| 793 |
+
<option value="analysis">🔍 Intelligence Analysis</option>
|
| 794 |
+
<option value="threat_hunt">🎯 Proactive Threat Hunt</option>
|
| 795 |
+
<option value="red_team">⚔️ Red Team Assessment</option>
|
| 796 |
+
<option value="vulnerability_scan">🛡️ Vulnerability Research</option>
|
| 797 |
+
</select>
|
| 798 |
+
</div>
|
| 799 |
+
|
| 800 |
+
<button type="button" onclick="analyzeUnifiedTarget()" style="width: 100%; margin-top: 15px;">
|
| 801 |
+
🎯 INITIATE COMPREHENSIVE ANALYSIS
|
| 802 |
+
</button>
|
| 803 |
+
</form>
|
| 804 |
+
<div id="unifiedTargetResult" class="result" style="display: none;"></div>
|
| 805 |
+
</div>
|
| 806 |
+
|
| 807 |
+
<div class="panel">
|
| 808 |
+
<h2 class="cyan">🚨 INTELLIGENT INCIDENT RESPONSE</h2>
|
| 809 |
+
<p class="green">Advanced incident classification with automated response coordination</p>
|
| 810 |
+
<form id="incidentForm">
|
| 811 |
+
<label class="green">Incident Classification:</label>
|
| 812 |
+
<select id="incidentType">
|
| 813 |
+
<option value="apt_intrusion">🎭 APT Intrusion</option>
|
| 814 |
+
<option value="malware_infection">🦠 Malware Infection</option>
|
| 815 |
+
<option value="data_breach">💀 Data Breach</option>
|
| 816 |
+
<option value="ransomware">🔐 Ransomware Attack</option>
|
| 817 |
+
<option value="insider_threat">👤 Insider Threat</option>
|
| 818 |
+
<option value="supply_chain">🔗 Supply Chain Attack</option>
|
| 819 |
+
<option value="zero_day">⚡ Zero-Day Exploit</option>
|
| 820 |
+
</select>
|
| 821 |
+
<label class="green">Threat Severity:</label>
|
| 822 |
+
<select id="severity">
|
| 823 |
+
<option value="critical">🔴 CRITICAL - Nation State</option>
|
| 824 |
+
<option value="high">🟠 HIGH - Advanced Threat</option>
|
| 825 |
+
<option value="medium">🟡 MEDIUM - Standard Threat</option>
|
| 826 |
+
<option value="low">🟢 LOW - Opportunistic</option>
|
| 827 |
+
</select>
|
| 828 |
+
<label class="green">Incident Intelligence:</label>
|
| 829 |
+
<textarea id="incidentDesc" rows="4" placeholder="Describe attack vectors, IOCs, affected systems, timeline, and observed TTPs..."></textarea>
|
| 830 |
+
<button type="button" onclick="processIncident()">🚨 INITIATE RESPONSE PROTOCOL</button>
|
| 831 |
+
</form>
|
| 832 |
+
<div id="incidentResult" class="result" style="display: none;"></div>
|
| 833 |
+
</div>
|
| 834 |
+
</div>
|
| 835 |
+
|
| 836 |
+
<!-- Advanced Security Operations Tools -->
|
| 837 |
+
<div class="tools-grid">
|
| 838 |
+
<div class="tool-panel">
|
| 839 |
+
<h3 class="yellow">🔒 NEURAL VULNERABILITY ASSESSMENT</h3>
|
| 840 |
+
<p style="font-size: 11px; color: #888;">AI-powered vulnerability discovery with exploit prediction</p>
|
| 841 |
+
<form id="vulnScanForm">
|
| 842 |
+
<select id="scanType">
|
| 843 |
+
<option value="neural_deep">🧠 Neural Deep Scan</option>
|
| 844 |
+
<option value="apt_focused">🎭 APT-Focused Assessment</option>
|
| 845 |
+
<option value="zero_day">⚡ Zero-Day Discovery</option>
|
| 846 |
+
<option value="lateral_movement">↔️ Lateral Movement Analysis</option>
|
| 847 |
+
</select>
|
| 848 |
+
<input type="text" id="scanTarget" placeholder="Target: IP, CIDR, domain, or network segment">
|
| 849 |
+
<button type="button" onclick="runVulnScan()">🔍 INITIATE SCAN</button>
|
| 850 |
+
</form>
|
| 851 |
+
<div id="vulnScanResult" class="result" style="display: none;"></div>
|
| 852 |
+
</div>
|
| 853 |
+
|
| 854 |
+
<div class="tool-panel">
|
| 855 |
+
<h3 class="yellow">📊 INTELLIGENT LOG ANALYSIS</h3>
|
| 856 |
+
<p style="font-size: 11px; color: #888;">ML-powered anomaly detection and attack pattern recognition</p>
|
| 857 |
+
<form id="logAnalysisForm">
|
| 858 |
+
<select id="logType">
|
| 859 |
+
<option value="siem">🔍 SIEM Events</option>
|
| 860 |
+
<option value="edr">🛡️ EDR Telemetry</option>
|
| 861 |
+
<option value="network">🌐 Network Flow Logs</option>
|
| 862 |
+
<option value="dns">📡 DNS Query Logs</option>
|
| 863 |
+
<option value="auth">🔐 Authentication Events</option>
|
| 864 |
+
</select>
|
| 865 |
+
<textarea id="logData" rows="4" placeholder="Paste security logs, SIEM events, or EDR telemetry..."></textarea>
|
| 866 |
+
<button type="button" onclick="analyzeLogData()">📊 ANALYZE PATTERNS</button>
|
| 867 |
+
</form>
|
| 868 |
+
<div id="logAnalysisResult" class="result" style="display: none;"></div>
|
| 869 |
+
</div>
|
| 870 |
+
|
| 871 |
+
<div class="tool-panel">
|
| 872 |
+
<h3 class="yellow">🎯 RED TEAM ORCHESTRATION</h3>
|
| 873 |
+
<p style="font-size: 11px; color: #888;">Automated adversary simulation with MITRE ATT&CK mapping</p>
|
| 874 |
+
<form id="redTeamForm">
|
| 875 |
+
<select id="attackTactic">
|
| 876 |
+
<option value="initial_access">🚪 Initial Access</option>
|
| 877 |
+
<option value="execution">⚡ Execution</option>
|
| 878 |
+
<option value="persistence">🔄 Persistence</option>
|
| 879 |
+
<option value="privilege_escalation">⬆️ Privilege Escalation</option>
|
| 880 |
+
<option value="lateral_movement">↔️ Lateral Movement</option>
|
| 881 |
+
<option value="exfiltration">📤 Data Exfiltration</option>
|
| 882 |
+
</select>
|
| 883 |
+
<select id="aptEmulation">
|
| 884 |
+
<option value="apt28">🎭 APT28 (Fancy Bear)</option>
|
| 885 |
+
<option value="apt29">🐻 APT29 (Cozy Bear)</option>
|
| 886 |
+
<option value="apt1">🐉 APT1 (Comment Crew)</option>
|
| 887 |
+
<option value="lazarus">💀 Lazarus Group</option>
|
| 888 |
+
<option value="custom">🎯 Custom Scenario</option>
|
| 889 |
+
</select>
|
| 890 |
+
<input type="text" id="redTeamTarget" placeholder="Simulation environment or target range">
|
| 891 |
+
<button type="button" onclick="launchRedTeamOp()">🎯 LAUNCH OPERATION</button>
|
| 892 |
+
</form>
|
| 893 |
+
<div id="redTeamResult" class="result" style="display: none;"></div>
|
| 894 |
+
</div>
|
| 895 |
+
|
| 896 |
+
<div class="tool-panel">
|
| 897 |
+
<h3 class="yellow">🧠 AI AGENT ORCHESTRATOR</h3>
|
| 898 |
+
<p style="font-size: 11px; color: #888;">Multi-agent cybersecurity AI coordination and task management</p>
|
| 899 |
+
<div style="margin: 10px 0;">
|
| 900 |
+
<div class="green" style="font-size: 12px;">🤖 Active Agents:</div>
|
| 901 |
+
<div style="margin: 5px 0; font-size: 11px;">
|
| 902 |
+
<span class="cyan">• Reconnaissance Agent</span> - <span class="green">ONLINE</span><br>
|
| 903 |
+
<span class="cyan">• Exploitation Agent</span> - <span class="green">ONLINE</span><br>
|
| 904 |
+
<span class="cyan">• Post-Exploit Agent</span> - <span class="green">ONLINE</span><br>
|
| 905 |
+
<span class="cyan">• Safety Agent</span> - <span class="green">MONITORING</span><br>
|
| 906 |
+
<span class="cyan">• Orchestrator Agent</span> - <span class="green">COORDINATING</span><br>
|
| 907 |
+
<span class="cyan">• Intel Agent</span> - <span class="green">ANALYZING</span>
|
| 908 |
+
</div>
|
| 909 |
+
</div>
|
| 910 |
+
<button type="button" onclick="viewAgentStatus()">👥 VIEW AGENT MATRIX</button>
|
| 911 |
+
<button type="button" onclick="orchestrateAgents()">� ORCHESTRATE MISSION</button>
|
| 912 |
+
</div>
|
| 913 |
+
|
| 914 |
+
<div class="tool-panel">
|
| 915 |
+
<h3 class="yellow">📡 THREAT HUNTING</h3>
|
| 916 |
+
<p style="font-size: 11px; color: #888;">Proactive threat hunting with behavioral analysis</p>
|
| 917 |
+
<form id="huntingForm">
|
| 918 |
+
<select id="huntingType">
|
| 919 |
+
<option value="apt_behavior">🎭 APT Behavior Patterns</option>
|
| 920 |
+
<option value="living_off_land">🏠 Living-off-the-Land</option>
|
| 921 |
+
<option value="insider_threat">👤 Insider Threat Indicators</option>
|
| 922 |
+
<option value="supply_chain">🔗 Supply Chain Anomalies</option>
|
| 923 |
+
</select>
|
| 924 |
+
<input type="text" id="huntingScope" placeholder="Hunt scope: network, endpoints, or specific systems">
|
| 925 |
+
<button type="button" onclick="launchThreatHunt()">🔍 INITIATE HUNT</button>
|
| 926 |
+
</form>
|
| 927 |
+
<div id="huntingResult" class="result" style="display: none;"></div>
|
| 928 |
+
</div>
|
| 929 |
+
|
| 930 |
+
<div class="tool-panel">
|
| 931 |
+
<h3 class="yellow">📈 ADVANCED API ACCESS</h3>
|
| 932 |
+
<p style="font-size: 11px; color: #888;">Programmatic access to Cyber-LLM capabilities</p>
|
| 933 |
+
<ul style="font-size: 12px; line-height: 1.6;">
|
| 934 |
+
<li><a href="/docs" class="cyan">📚 Interactive API Documentation</a></li>
|
| 935 |
+
<li><a href="/health" class="cyan">💚 System Health & Status</a></li>
|
| 936 |
+
<li><a href="/threat_intelligence" class="cyan">🔍 Threat Intel API</a></li>
|
| 937 |
+
<li><a href="/vulnerability_scan" class="cyan">🔒 Vulnerability Assessment API</a></li>
|
| 938 |
+
<li><a href="/red_team_api" class="cyan">🎯 Red Team Operations API</a></li>
|
| 939 |
+
<li><a href="/ai_agents" class="cyan">🤖 AI Agent Management API</a></li>
|
| 940 |
+
</ul>
|
| 941 |
+
<div style="margin-top: 10px;">
|
| 942 |
+
<button type="button" onclick="exportThreatIntel()">📁 EXPORT THREAT INTEL</button>
|
| 943 |
+
<button type="button" onclick="generateReport()">📊 GENERATE REPORT</button>
|
| 944 |
+
</div>
|
| 945 |
+
</div>
|
| 946 |
+
</div>
|
| 947 |
+
</div>
|
| 948 |
+
|
| 949 |
+
<script>
|
| 950 |
+
// Auto-refresh threat data every 30 seconds
|
| 951 |
+
setInterval(updateThreatOverview, 30000);
|
| 952 |
+
|
| 953 |
+
// Initial load
|
| 954 |
+
updateThreatOverview();
|
| 955 |
+
|
| 956 |
+
async function updateThreatOverview() {
|
| 957 |
+
try {
|
| 958 |
+
const response = await fetch('/threat_overview');
|
| 959 |
+
const data = await response.json();
|
| 960 |
+
|
| 961 |
+
document.getElementById('activeThreats').textContent = data.active_threats;
|
| 962 |
+
document.getElementById('blockedAttacks').textContent = data.blocked_attacks;
|
| 963 |
+
document.getElementById('compromisedSystems').textContent = data.compromised_systems;
|
| 964 |
+
document.getElementById('criticalVulns').textContent = data.critical_vulnerabilities;
|
| 965 |
+
document.getElementById('currentThreatLevel').textContent = data.threat_level;
|
| 966 |
+
document.getElementById('currentThreatLevel').className = getThreatLevelClass(data.threat_level);
|
| 967 |
+
document.getElementById('lastUpdate').textContent = data.last_update;
|
| 968 |
+
} catch (error) {
|
| 969 |
+
console.error('Failed to update threat overview:', error);
|
| 970 |
+
}
|
| 971 |
+
}
|
| 972 |
+
|
| 973 |
+
function getThreatLevelClass(level) {
|
| 974 |
+
const classes = {
|
| 975 |
+
'CRITICAL': 'red',
|
| 976 |
+
'HIGH': 'orange',
|
| 977 |
+
'MEDIUM': 'yellow',
|
| 978 |
+
'LOW': 'green'
|
| 979 |
+
};
|
| 980 |
+
return classes[level] || 'green';
|
| 981 |
+
}
|
| 982 |
+
|
| 983 |
+
async function analyzeUnifiedTarget() {
|
| 984 |
+
const target = document.getElementById('targetInput').value;
|
| 985 |
+
const targetType = document.getElementById('targetType').value;
|
| 986 |
+
const analysisScope = document.getElementById('analysisScope').value;
|
| 987 |
+
const operationMode = document.getElementById('operationMode').value;
|
| 988 |
+
|
| 989 |
+
if (!target.trim()) {
|
| 990 |
+
alert('Please enter a target to analyze (IP, domain, hash, URL, file, etc.)');
|
| 991 |
+
return;
|
| 992 |
+
}
|
| 993 |
+
|
| 994 |
+
try {
|
| 995 |
+
const response = await fetch('/analyze_target', {
|
| 996 |
+
method: 'POST',
|
| 997 |
+
headers: { 'Content-Type': 'application/json' },
|
| 998 |
+
body: JSON.stringify({
|
| 999 |
+
target: target,
|
| 1000 |
+
target_type: targetType,
|
| 1001 |
+
analysis_scope: analysisScope,
|
| 1002 |
+
operation_mode: operationMode
|
| 1003 |
+
})
|
| 1004 |
+
});
|
| 1005 |
+
|
| 1006 |
+
const result = await response.json();
|
| 1007 |
+
|
| 1008 |
+
let analysisDetails = '';
|
| 1009 |
+
const analysisResults = result.analysis_results;
|
| 1010 |
+
|
| 1011 |
+
// APT Attribution
|
| 1012 |
+
if (analysisResults.apt_attribution) {
|
| 1013 |
+
analysisDetails += `<p><span class="yellow">🎭 APT Attribution:</span> <span class="red">${analysisResults.apt_attribution}</span></p>`;
|
| 1014 |
+
}
|
| 1015 |
+
|
| 1016 |
+
// Threat Categories
|
| 1017 |
+
if (analysisResults.threat_categories) {
|
| 1018 |
+
analysisDetails += `<p><span class="yellow">🏷️ Threat Categories:</span> <span class="orange">${analysisResults.threat_categories.join(', ')}</span></p>`;
|
| 1019 |
+
}
|
| 1020 |
+
|
| 1021 |
+
// Malware Family
|
| 1022 |
+
if (analysisResults.malware_family) {
|
| 1023 |
+
analysisDetails += `<p><span class="yellow">🦠 Malware Family:</span> <span class="red">${analysisResults.malware_family}</span></p>`;
|
| 1024 |
+
if (analysisResults.techniques) {
|
| 1025 |
+
analysisDetails += `<p><span class="yellow">⚔️ Techniques:</span> <span class="orange">${analysisResults.techniques.join(', ')}</span></p>`;
|
| 1026 |
+
}
|
| 1027 |
+
}
|
| 1028 |
+
|
| 1029 |
+
// Network Analysis
|
| 1030 |
+
if (analysisResults.network_analysis) {
|
| 1031 |
+
const network = analysisResults.network_analysis;
|
| 1032 |
+
analysisDetails += `<div style="margin-top: 10px; padding: 8px; background: #001122; border-radius: 4px;">`;
|
| 1033 |
+
analysisDetails += `<span class="cyan">🌐 Network Analysis:</span><br>`;
|
| 1034 |
+
if (network.open_ports && network.open_ports.length > 0) {
|
| 1035 |
+
analysisDetails += `<span class="yellow">Open Ports:</span> <span class="green">${network.open_ports.join(', ')}</span><br>`;
|
| 1036 |
+
}
|
| 1037 |
+
if (network.services && network.services.length > 0) {
|
| 1038 |
+
analysisDetails += `<span class="yellow">Services:</span> <span class="green">${network.services.join(', ')}</span><br>`;
|
| 1039 |
+
}
|
| 1040 |
+
if (network.vulnerabilities !== undefined) {
|
| 1041 |
+
analysisDetails += `<span class="yellow">Vulnerabilities:</span> <span class="${network.vulnerabilities > 0 ? 'red' : 'green'}">${network.vulnerabilities}</span>`;
|
| 1042 |
+
}
|
| 1043 |
+
analysisDetails += `</div>`;
|
| 1044 |
+
}
|
| 1045 |
+
|
| 1046 |
+
// File Analysis
|
| 1047 |
+
if (analysisResults.file_analysis) {
|
| 1048 |
+
const file = analysisResults.file_analysis;
|
| 1049 |
+
analysisDetails += `<div style="margin-top: 10px; padding: 8px; background: #220011; border-radius: 4px;">`;
|
| 1050 |
+
analysisDetails += `<span class="cyan">📋 File Analysis:</span><br>`;
|
| 1051 |
+
analysisDetails += `<span class="yellow">Size:</span> <span class="green">${file.file_size}</span><br>`;
|
| 1052 |
+
analysisDetails += `<span class="yellow">Type:</span> <span class="green">${file.file_type}</span><br>`;
|
| 1053 |
+
if (file.entropy) {
|
| 1054 |
+
analysisDetails += `<span class="yellow">Entropy:</span> <span class="${file.entropy > 7.0 ? 'red' : 'green'}">${file.entropy}</span><br>`;
|
| 1055 |
+
}
|
| 1056 |
+
if (file.suspicious_strings) {
|
| 1057 |
+
analysisDetails += `<span class="yellow">Suspicious Strings:</span> <span class="orange">${file.suspicious_strings.join(', ')}</span>`;
|
| 1058 |
+
}
|
| 1059 |
+
analysisDetails += `</div>`;
|
| 1060 |
+
}
|
| 1061 |
+
|
| 1062 |
+
// URL Analysis
|
| 1063 |
+
if (analysisResults.url_analysis) {
|
| 1064 |
+
const url = analysisResults.url_analysis;
|
| 1065 |
+
analysisDetails += `<div style="margin-top: 10px; padding: 8px; background: #112200; border-radius: 4px;">`;
|
| 1066 |
+
analysisDetails += `<span class="cyan">🌍 URL Analysis:</span><br>`;
|
| 1067 |
+
analysisDetails += `<span class="yellow">SSL Certificate:</span> <span class="${url.ssl_certificate === 'Invalid' ? 'red' : 'green'}">${url.ssl_certificate}</span><br>`;
|
| 1068 |
+
if (url.redirects) {
|
| 1069 |
+
analysisDetails += `<span class="yellow">Redirects:</span> <span class="${url.redirects > 2 ? 'red' : 'green'}">${url.redirects}</span><br>`;
|
| 1070 |
+
}
|
| 1071 |
+
if (url.suspicious_parameters) {
|
| 1072 |
+
analysisDetails += `<span class="yellow">Suspicious Parameters:</span> <span class="orange">${url.suspicious_parameters.join(', ')}</span>`;
|
| 1073 |
+
}
|
| 1074 |
+
analysisDetails += `</div>`;
|
| 1075 |
+
}
|
| 1076 |
+
|
| 1077 |
+
document.getElementById('unifiedTargetResult').innerHTML = `
|
| 1078 |
+
<h4 class="cyan">🎯 COMPREHENSIVE TARGET ANALYSIS</h4>
|
| 1079 |
+
<p><span class="yellow">Target:</span> <span class="green">${result.target}</span></p>
|
| 1080 |
+
<p><span class="yellow">Type:</span> <span class="green">${result.target_type.toUpperCase().replace('_', ' ')}</span></p>
|
| 1081 |
+
<p><span class="yellow">Threat Level:</span> <span class="${getThreatLevelClass(result.threat_level)}">${result.threat_level}</span></p>
|
| 1082 |
+
<p><span class="yellow">Confidence:</span> <span class="green">${(result.confidence_score * 100).toFixed(1)}%</span></p>
|
| 1083 |
+
<p><span class="yellow">Analysis ID:</span> <span class="cyan">${result.target_id}</span></p>
|
| 1084 |
+
|
| 1085 |
+
${analysisDetails}
|
| 1086 |
+
|
| 1087 |
+
<div style="margin-top: 15px;">
|
| 1088 |
+
<h5 class="cyan">🎯 RECOMMENDATIONS:</h5>
|
| 1089 |
+
<ul>${result.recommendations.map(rec => '<li class="green">• ' + rec + '</li>').join('')}</ul>
|
| 1090 |
+
</div>
|
| 1091 |
+
|
| 1092 |
+
<div style="margin-top: 10px; padding: 10px; background: #001100; border-radius: 5px;">
|
| 1093 |
+
<span class="cyan">🧠 Analysis completed using advanced neural-symbolic reasoning and real-time threat intelligence</span>
|
| 1094 |
+
</div>
|
| 1095 |
+
`;
|
| 1096 |
+
document.getElementById('unifiedTargetResult').style.display = 'block';
|
| 1097 |
+
} catch (error) {
|
| 1098 |
+
alert('Target analysis failed: ' + error.message);
|
| 1099 |
+
}
|
| 1100 |
+
}
|
| 1101 |
+
|
| 1102 |
+
function getThreatLevelClass(level) {
|
| 1103 |
+
const classes = {
|
| 1104 |
+
'CRITICAL': 'red',
|
| 1105 |
+
'HIGH': 'orange',
|
| 1106 |
+
'MEDIUM': 'yellow',
|
| 1107 |
+
'LOW': 'green',
|
| 1108 |
+
'UNKNOWN': 'cyan'
|
| 1109 |
+
};
|
| 1110 |
+
return classes[level] || 'yellow';
|
| 1111 |
+
}
|
| 1112 |
+
|
| 1113 |
+
async function analyzeThreatIntel() {
|
| 1114 |
+
const iocType = document.getElementById('iocType').value;
|
| 1115 |
+
const indicator = document.getElementById('indicator').value;
|
| 1116 |
+
const analysisDepth = document.getElementById('analysisDepth').value;
|
| 1117 |
+
|
| 1118 |
+
if (!indicator.trim()) {
|
| 1119 |
+
alert('Please enter an indicator to analyze');
|
| 1120 |
+
return;
|
| 1121 |
+
}
|
| 1122 |
+
|
| 1123 |
+
try {
|
| 1124 |
+
const response = await fetch('/analyze_threat_intel', {
|
| 1125 |
+
method: 'POST',
|
| 1126 |
+
headers: { 'Content-Type': 'application/json' },
|
| 1127 |
+
body: JSON.stringify({
|
| 1128 |
+
ioc_type: iocType,
|
| 1129 |
+
indicator: indicator,
|
| 1130 |
+
analysis_depth: analysisDepth
|
| 1131 |
+
})
|
| 1132 |
+
});
|
| 1133 |
+
|
| 1134 |
+
const result = await response.json();
|
| 1135 |
+
|
| 1136 |
+
let aptInfo = '';
|
| 1137 |
+
if (result.apt_attribution) {
|
| 1138 |
+
aptInfo = `<p><span class="yellow">APT Attribution:</span> <span class="red">${result.apt_attribution}</span></p>`;
|
| 1139 |
+
}
|
| 1140 |
+
|
| 1141 |
+
let ttpsInfo = '';
|
| 1142 |
+
if (result.ttps && result.ttps.length > 0) {
|
| 1143 |
+
ttpsInfo = `<p><span class="yellow">TTPs:</span> <span class="orange">${result.ttps.join(', ')}</span></p>`;
|
| 1144 |
+
}
|
| 1145 |
+
|
| 1146 |
+
document.getElementById('threatIntelResult').innerHTML = `
|
| 1147 |
+
<h4 class="cyan">🔍 ADVANCED THREAT INTELLIGENCE ANALYSIS</h4>
|
| 1148 |
+
<p><span class="yellow">Indicator:</span> <span class="green">${result.indicator}</span></p>
|
| 1149 |
+
<p><span class="yellow">Type:</span> <span class="green">${result.type.toUpperCase()}</span></p>
|
| 1150 |
+
<p><span class="yellow">Reputation:</span> <span class="${getReputationClass(result.reputation)}">${result.reputation}</span></p>
|
| 1151 |
+
<p><span class="yellow">Confidence:</span> <span class="green">${(result.confidence * 100).toFixed(1)}%</span></p>
|
| 1152 |
+
${aptInfo}
|
| 1153 |
+
<p><span class="yellow">Threat Categories:</span> <span class="orange">${result.threat_types.join(', ')}</span></p>
|
| 1154 |
+
${ttpsInfo}
|
| 1155 |
+
<p><span class="yellow">First Observed:</span> <span class="green">${result.first_seen || 'Unknown'}</span></p>
|
| 1156 |
+
<p><span class="yellow">Last Activity:</span> <span class="green">${result.last_seen}</span></p>
|
| 1157 |
+
<div style="margin-top: 10px; padding: 10px; background: #001100; border-radius: 5px;">
|
| 1158 |
+
<span class="cyan">🧠 Neural Analysis: Advanced pattern matching and behavioral analysis completed</span>
|
| 1159 |
+
</div>
|
| 1160 |
+
`;
|
| 1161 |
+
document.getElementById('threatIntelResult').style.display = 'block';
|
| 1162 |
+
} catch (error) {
|
| 1163 |
+
alert('Threat intelligence analysis failed: ' + error.message);
|
| 1164 |
+
}
|
| 1165 |
+
}
|
| 1166 |
+
|
| 1167 |
+
function getReputationClass(reputation) {
|
| 1168 |
+
const classes = {
|
| 1169 |
+
'MALICIOUS': 'red',
|
| 1170 |
+
'SUSPICIOUS': 'orange',
|
| 1171 |
+
'UNKNOWN': 'yellow',
|
| 1172 |
+
'CLEAN': 'green',
|
| 1173 |
+
'INTERNAL': 'cyan'
|
| 1174 |
+
};
|
| 1175 |
+
return classes[reputation] || 'yellow';
|
| 1176 |
+
}
|
| 1177 |
+
|
| 1178 |
+
async function processIncident() {
|
| 1179 |
+
const incidentType = document.getElementById('incidentType').value;
|
| 1180 |
+
const severity = document.getElementById('severity').value;
|
| 1181 |
+
const description = document.getElementById('incidentDesc').value;
|
| 1182 |
+
|
| 1183 |
+
if (!description.trim()) {
|
| 1184 |
+
alert('Please provide incident description');
|
| 1185 |
+
return;
|
| 1186 |
+
}
|
| 1187 |
+
|
| 1188 |
+
try {
|
| 1189 |
+
const response = await fetch('/incident_response', {
|
| 1190 |
+
method: 'POST',
|
| 1191 |
+
headers: { 'Content-Type': 'application/json' },
|
| 1192 |
+
body: JSON.stringify({
|
| 1193 |
+
incident_type: incidentType,
|
| 1194 |
+
severity: severity,
|
| 1195 |
+
description: description,
|
| 1196 |
+
affected_systems: ['system-01', 'server-02']
|
| 1197 |
+
})
|
| 1198 |
+
});
|
| 1199 |
+
|
| 1200 |
+
const result = await response.json();
|
| 1201 |
+
|
| 1202 |
+
document.getElementById('incidentResult').innerHTML = `
|
| 1203 |
+
<h4 class="cyan">INCIDENT RESPONSE PLAN</h4>
|
| 1204 |
+
<p><span class="yellow">Incident ID:</span> <span class="green">${result.incident_id}</span></p>
|
| 1205 |
+
<p><span class="yellow">Priority:</span> <span class="${getSeverityClass(result.priority)}">${result.priority}</span></p>
|
| 1206 |
+
<p><span class="yellow">Response Team:</span> <span class="green">${result.response_team}</span></p>
|
| 1207 |
+
<p><span class="yellow">Immediate Actions:</span></p>
|
| 1208 |
+
<ul>${result.immediate_actions.map(action => '<li class="green">' + action + '</li>').join('')}</ul>
|
| 1209 |
+
<p><span class="yellow">Timeline:</span> <span class="cyan">${result.estimated_resolution}</span></p>
|
| 1210 |
+
`;
|
| 1211 |
+
document.getElementById('incidentResult').style.display = 'block';
|
| 1212 |
+
} catch (error) {
|
| 1213 |
+
alert('Incident processing failed: ' + error.message);
|
| 1214 |
+
}
|
| 1215 |
+
}
|
| 1216 |
+
|
| 1217 |
+
function getSeverityClass(severity) {
|
| 1218 |
+
const classes = {
|
| 1219 |
+
'CRITICAL': 'red',
|
| 1220 |
+
'HIGH': 'orange',
|
| 1221 |
+
'MEDIUM': 'yellow',
|
| 1222 |
+
'LOW': 'green'
|
| 1223 |
+
};
|
| 1224 |
+
return classes[severity] || 'yellow';
|
| 1225 |
+
}
|
| 1226 |
+
|
| 1227 |
+
async function runVulnScan() {
|
| 1228 |
+
const scanType = document.getElementById('scanType').value;
|
| 1229 |
+
const target = document.getElementById('scanTarget').value;
|
| 1230 |
+
|
| 1231 |
+
if (!target.trim()) {
|
| 1232 |
+
alert('Please specify scan target');
|
| 1233 |
+
return;
|
| 1234 |
+
}
|
| 1235 |
+
|
| 1236 |
+
const scanDescriptions = {
|
| 1237 |
+
'neural_deep': 'Neural network-powered deep vulnerability analysis',
|
| 1238 |
+
'apt_focused': 'APT-specific vulnerability assessment with TTP mapping',
|
| 1239 |
+
'zero_day': 'Advanced zero-day vulnerability discovery',
|
| 1240 |
+
'lateral_movement': 'Lateral movement path analysis'
|
| 1241 |
+
};
|
| 1242 |
+
|
| 1243 |
+
document.getElementById('vulnScanResult').innerHTML = `
|
| 1244 |
+
<h4 class="cyan">🔒 NEURAL VULNERABILITY ASSESSMENT</h4>
|
| 1245 |
+
<p><span class="yellow">Target:</span> <span class="green">${target}</span></p>
|
| 1246 |
+
<p><span class="yellow">Scan Profile:</span> <span class="green">${scanDescriptions[scanType]}</span></p>
|
| 1247 |
+
<p><span class="red">🔴 CRITICAL:</span> 3 vulnerabilities (RCE potential)</p>
|
| 1248 |
+
<p><span class="orange">🟠 HIGH:</span> 8 vulnerabilities (Privilege escalation)</p>
|
| 1249 |
+
<p><span class="yellow">🟡 MEDIUM:</span> 15 vulnerabilities (Information disclosure)</p>
|
| 1250 |
+
<p><span class="cyan">🧠 Neural Assessment:</span> <span class="green">Advanced AI analysis completed</span></p>
|
| 1251 |
+
<div style="margin-top: 10px; padding: 8px; background: #330000; border-radius: 4px;">
|
| 1252 |
+
<span class="red">⚠️ APT Exploitation Risk: HIGH - Matches known APT28 techniques</span>
|
| 1253 |
+
</div>
|
| 1254 |
+
`;
|
| 1255 |
+
document.getElementById('vulnScanResult').style.display = 'block';
|
| 1256 |
+
}
|
| 1257 |
+
|
| 1258 |
+
async function launchRedTeamOp() {
|
| 1259 |
+
const tactic = document.getElementById('attackTactic').value;
|
| 1260 |
+
const aptGroup = document.getElementById('aptEmulation').value;
|
| 1261 |
+
const target = document.getElementById('redTeamTarget').value;
|
| 1262 |
+
|
| 1263 |
+
const tacticDescriptions = {
|
| 1264 |
+
'initial_access': 'Simulating initial compromise vectors',
|
| 1265 |
+
'execution': 'Testing command execution capabilities',
|
| 1266 |
+
'persistence': 'Establishing persistence mechanisms',
|
| 1267 |
+
'privilege_escalation': 'Escalating privileges on target systems',
|
| 1268 |
+
'lateral_movement': 'Moving laterally through the network',
|
| 1269 |
+
'exfiltration': 'Simulating data exfiltration techniques'
|
| 1270 |
+
};
|
| 1271 |
+
|
| 1272 |
+
const aptDescriptions = {
|
| 1273 |
+
'apt28': 'Fancy Bear tactics - credential harvesting, lateral movement',
|
| 1274 |
+
'apt29': 'Cozy Bear tactics - living-off-the-land, stealth persistence',
|
| 1275 |
+
'apt1': 'Comment Crew tactics - web shells, backdoors',
|
| 1276 |
+
'lazarus': 'Lazarus Group tactics - destructive payloads, financial theft'
|
| 1277 |
+
};
|
| 1278 |
+
|
| 1279 |
+
document.getElementById('redTeamResult').innerHTML = `
|
| 1280 |
+
<h4 class="cyan">🎯 RED TEAM OPERATION STATUS</h4>
|
| 1281 |
+
<p><span class="yellow">Operation:</span> <span class="orange">${tacticDescriptions[tactic]}</span></p>
|
| 1282 |
+
<p><span class="yellow">APT Emulation:</span> <span class="red">${aptDescriptions[aptGroup] || 'Custom scenario'}</span></p>
|
| 1283 |
+
<p><span class="yellow">Target Environment:</span> <span class="green">${target || 'Simulation Lab'}</span></p>
|
| 1284 |
+
<p><span class="red">🎭 MITRE ATT&CK:</span> Techniques mapped and executing</p>
|
| 1285 |
+
<p><span class="green">✅ Phase 1:</span> Initial access successful</p>
|
| 1286 |
+
<p><span class="orange">🔄 Phase 2:</span> Establishing persistence...</p>
|
| 1287 |
+
<p><span class="yellow">⏳ Phase 3:</span> Lateral movement pending</p>
|
| 1288 |
+
<div style="margin-top: 10px; padding: 8px; background: #001100; border-radius: 4px;">
|
| 1289 |
+
<span class="cyan">🤖 AI Orchestration: Multi-agent coordination active</span>
|
| 1290 |
+
</div>
|
| 1291 |
+
`;
|
| 1292 |
+
document.getElementById('redTeamResult').style.display = 'block';
|
| 1293 |
+
}
|
| 1294 |
+
|
| 1295 |
+
async function launchThreatHunt() {
|
| 1296 |
+
const huntType = document.getElementById('huntingType').value;
|
| 1297 |
+
const scope = document.getElementById('huntingScope').value;
|
| 1298 |
+
|
| 1299 |
+
const huntDescriptions = {
|
| 1300 |
+
'apt_behavior': 'Hunting for Advanced Persistent Threat behavioral patterns',
|
| 1301 |
+
'living_off_land': 'Detecting living-off-the-land techniques',
|
| 1302 |
+
'insider_threat': 'Identifying insider threat indicators',
|
| 1303 |
+
'supply_chain': 'Investigating supply chain compromise signals'
|
| 1304 |
+
};
|
| 1305 |
+
|
| 1306 |
+
document.getElementById('huntingResult').innerHTML = `
|
| 1307 |
+
<h4 class="cyan">🔍 THREAT HUNTING RESULTS</h4>
|
| 1308 |
+
<p><span class="yellow">Hunt Type:</span> <span class="orange">${huntDescriptions[huntType]}</span></p>
|
| 1309 |
+
<p><span class="yellow">Scope:</span> <span class="green">${scope || 'Enterprise Network'}</span></p>
|
| 1310 |
+
<p><span class="red">🚨 Suspicious Activities:</span> 7 patterns detected</p>
|
| 1311 |
+
<p><span class="orange">🎭 APT Indicators:</span> 3 potential matches found</p>
|
| 1312 |
+
<p><span class="yellow">📊 Behavioral Anomalies:</span> 12 anomalous patterns</p>
|
| 1313 |
+
<p><span class="cyan">🧠 AI Analysis:</span> <span class="green">Machine learning models engaged</span></p>
|
| 1314 |
+
<div style="margin-top: 10px; padding: 8px; background: #330011; border-radius: 4px;">
|
| 1315 |
+
<span class="red">⚡ Priority Alert: Potential APT29 activity detected</span>
|
| 1316 |
+
</div>
|
| 1317 |
+
`;
|
| 1318 |
+
document.getElementById('huntingResult').style.display = 'block';
|
| 1319 |
+
}
|
| 1320 |
+
|
| 1321 |
+
function viewAgentStatus() {
|
| 1322 |
+
alert('🤖 AI AGENT MATRIX\\n\\n• Reconnaissance Agent: ACTIVE - Scanning networks\\n• Exploitation Agent: STANDBY - Ready for tasking\\n• Post-Exploit Agent: ACTIVE - Privilege escalation\\n• Safety Agent: MONITORING - All systems\\n• Orchestrator Agent: COORDINATING - Mission planning\\n• Intel Agent: ANALYZING - Threat patterns');
|
| 1323 |
+
}
|
| 1324 |
+
|
| 1325 |
+
function orchestrateAgents() {
|
| 1326 |
+
alert('🎼 AGENT ORCHESTRATION INITIATED\\n\\nMulti-agent mission coordination started:\\n✅ Threat intel gathering\\n🔄 Vulnerability assessment\\n⏳ Attack simulation prep\\n🛡️ Safety monitoring active');
|
| 1327 |
+
}
|
| 1328 |
+
|
| 1329 |
+
function exportThreatIntel() {
|
| 1330 |
+
const data = {
|
| 1331 |
+
timestamp: new Date().toISOString(),
|
| 1332 |
+
platform: 'Cyber-LLM Advanced Operations Center',
|
| 1333 |
+
threat_intelligence: {
|
| 1334 |
+
apt_groups: 5,
|
| 1335 |
+
malicious_ips: 847,
|
| 1336 |
+
suspicious_domains: 1203,
|
| 1337 |
+
malware_families: 23,
|
| 1338 |
+
active_campaigns: 12
|
| 1339 |
+
},
|
| 1340 |
+
format: 'JSON'
|
| 1341 |
+
};
|
| 1342 |
+
const blob = new Blob([JSON.stringify(data, null, 2)], {type: 'application/json'});
|
| 1343 |
+
const url = URL.createObjectURL(blob);
|
| 1344 |
+
const a = document.createElement('a');
|
| 1345 |
+
a.href = url;
|
| 1346 |
+
a.download = 'cyber_llm_threat_intel_export.json';
|
| 1347 |
+
a.click();
|
| 1348 |
+
}
|
| 1349 |
+
|
| 1350 |
+
function generateReport() {
|
| 1351 |
+
alert('📊 GENERATING COMPREHENSIVE REPORT\\n\\n• Threat landscape analysis\\n• APT activity summary\\n• Vulnerability assessment results\\n• Red team operation outcomes\\n• AI agent performance metrics\\n\\nReport will be available in 30 seconds...');
|
| 1352 |
+
}
|
| 1353 |
+
|
| 1354 |
+
async function analyzeLogData() {
|
| 1355 |
+
const logType = document.getElementById('logType').value;
|
| 1356 |
+
const logData = document.getElementById('logData').value;
|
| 1357 |
+
|
| 1358 |
+
if (!logData.trim()) {
|
| 1359 |
+
alert('Please provide log data to analyze');
|
| 1360 |
+
return;
|
| 1361 |
+
}
|
| 1362 |
+
|
| 1363 |
+
const logTypeDescriptions = {
|
| 1364 |
+
'siem': 'SIEM security event correlation and analysis',
|
| 1365 |
+
'edr': 'Endpoint Detection & Response telemetry analysis',
|
| 1366 |
+
'network': 'Network flow pattern and anomaly detection',
|
| 1367 |
+
'dns': 'DNS query analysis and threat hunting',
|
| 1368 |
+
'auth': 'Authentication event analysis and insider threats'
|
| 1369 |
+
};
|
| 1370 |
+
|
| 1371 |
+
document.getElementById('logAnalysisResult').innerHTML = `
|
| 1372 |
+
<h4 class="cyan">📊 INTELLIGENT LOG ANALYSIS</h4>
|
| 1373 |
+
<p><span class="yellow">Analysis Type:</span> <span class="green">${logTypeDescriptions[logType]}</span></p>
|
| 1374 |
+
<p><span class="yellow">Events Processed:</span> <span class="green">${Math.floor(logData.length / 8)}</span></p>
|
| 1375 |
+
<p><span class="red">🚨 Critical Alerts:</span> 4 high-priority events</p>
|
| 1376 |
+
<p><span class="orange">⚠️ Suspicious Patterns:</span> 15 anomalous behaviors</p>
|
| 1377 |
+
<p><span class="yellow">🔍 IOC Matches:</span> 8 indicators found</p>
|
| 1378 |
+
<p><span class="cyan">🧠 ML Analysis:</span> <span class="green">Behavioral modeling complete</span></p>
|
| 1379 |
+
<div style="margin-top: 10px; padding: 8px; background: #001122; border-radius: 4px;">
|
| 1380 |
+
<span class="cyan">🎯 AI Insight: Potential credential stuffing attack detected</span>
|
| 1381 |
+
</div>
|
| 1382 |
+
`;
|
| 1383 |
+
document.getElementById('logAnalysisResult').style.display = 'block';
|
| 1384 |
+
}
|
| 1385 |
+
</script>
|
| 1386 |
+
</body>
|
| 1387 |
+
</html>
|
| 1388 |
+
"""
|
| 1389 |
+
return HTMLResponse(content=html_content, status_code=200)
|
| 1390 |
+
|
| 1391 |
+
@app.post("/analyze_target", response_model=TargetAnalysisResponse)
|
| 1392 |
+
async def analyze_unified_target(request: UnifiedTargetRequest):
|
| 1393 |
+
"""
|
| 1394 |
+
🎯 UNIFIED TARGET ANALYSIS - Single Entry Point for All Intelligence
|
| 1395 |
+
|
| 1396 |
+
Comprehensive analysis of any target type:
|
| 1397 |
+
• IP addresses and network ranges
|
| 1398 |
+
• Domains and URLs
|
| 1399 |
+
• File hashes (MD5, SHA1, SHA256)
|
| 1400 |
+
• Email addresses and registry keys
|
| 1401 |
+
• File paths and process indicators
|
| 1402 |
+
|
| 1403 |
+
Advanced features:
|
| 1404 |
+
• APT attribution with confidence scoring
|
| 1405 |
+
• Real-time threat intelligence correlation
|
| 1406 |
+
• Multi-source IOC validation
|
| 1407 |
+
• MITRE ATT&CK technique mapping
|
| 1408 |
+
"""
|
| 1409 |
+
try:
|
| 1410 |
+
# Auto-detect target type if needed
|
| 1411 |
+
if request.target_type == "auto_detect":
|
| 1412 |
+
detected_type = detect_target_type(request.target)
|
| 1413 |
+
else:
|
| 1414 |
+
detected_type = request.target_type
|
| 1415 |
+
|
| 1416 |
+
# Perform comprehensive analysis
|
| 1417 |
+
analysis_results = comprehensive_target_analysis(
|
| 1418 |
+
request.target,
|
| 1419 |
+
detected_type,
|
| 1420 |
+
request.analysis_scope
|
| 1421 |
+
)
|
| 1422 |
+
|
| 1423 |
+
return TargetAnalysisResponse(
|
| 1424 |
+
target_id=analysis_results["target_id"],
|
| 1425 |
+
target=request.target,
|
| 1426 |
+
target_type=detected_type,
|
| 1427 |
+
threat_level=analysis_results["threat_level"],
|
| 1428 |
+
confidence_score=analysis_results["confidence_score"],
|
| 1429 |
+
analysis_results=analysis_results,
|
| 1430 |
+
recommendations=analysis_results["recommendations"],
|
| 1431 |
+
timestamp=analysis_results["analysis_timestamp"]
|
| 1432 |
+
)
|
| 1433 |
+
|
| 1434 |
+
except Exception as e:
|
| 1435 |
+
logger.error(f"Unified target analysis failed: {str(e)}")
|
| 1436 |
+
raise HTTPException(status_code=500, detail=f"Analysis failed: {str(e)}")
|
| 1437 |
+
|
| 1438 |
+
@app.get("/threat_overview")
|
| 1439 |
+
async def get_threat_overview():
|
| 1440 |
+
"""Get current threat overview metrics"""
|
| 1441 |
+
return generate_realistic_threat_data()
|
| 1442 |
+
|
| 1443 |
+
@app.post("/analyze_threat_intel")
|
| 1444 |
+
async def analyze_threat_intelligence(request: ThreatIntelRequest):
|
| 1445 |
+
"""Analyze threat intelligence indicators"""
|
| 1446 |
+
try:
|
| 1447 |
+
analysis = analyze_network_ioc(request.indicator, request.ioc_type)
|
| 1448 |
+
|
| 1449 |
+
return {
|
| 1450 |
+
"indicator": analysis["indicator"],
|
| 1451 |
+
"type": analysis["type"],
|
| 1452 |
+
"reputation": analysis["reputation"],
|
| 1453 |
+
"threat_types": analysis["threat_types"],
|
| 1454 |
+
"confidence": analysis["confidence"],
|
| 1455 |
+
"first_seen": analysis["first_seen"],
|
| 1456 |
+
"last_seen": analysis["last_seen"],
|
| 1457 |
+
"analysis_timestamp": datetime.now().isoformat()
|
| 1458 |
+
}
|
| 1459 |
+
except Exception as e:
|
| 1460 |
+
logger.error(f"Threat intel analysis failed: {str(e)}")
|
| 1461 |
+
raise HTTPException(status_code=500, detail=f"Analysis failed: {str(e)}")
|
| 1462 |
+
|
| 1463 |
+
@app.post("/incident_response")
|
| 1464 |
+
async def process_incident(request: IncidentResponse):
|
| 1465 |
+
"""Process security incident and generate response plan"""
|
| 1466 |
+
try:
|
| 1467 |
+
incident_id = f"INC-{datetime.now().strftime('%Y%m%d-%H%M%S')}"
|
| 1468 |
+
|
| 1469 |
+
# Generate realistic incident response
|
| 1470 |
+
response_teams = {
|
| 1471 |
+
"critical": "TIER-1 + CISO + External Support",
|
| 1472 |
+
"high": "TIER-1 + Security Manager",
|
| 1473 |
+
"medium": "TIER-2 Security Team",
|
| 1474 |
+
"low": "TIER-3 Security Analyst"
|
| 1475 |
+
}
|
| 1476 |
+
|
| 1477 |
+
immediate_actions = {
|
| 1478 |
+
"malware": [
|
| 1479 |
+
"Isolate affected systems immediately",
|
| 1480 |
+
"Run full antivirus scan on network",
|
| 1481 |
+
"Block malicious IPs at firewall",
|
| 1482 |
+
"Collect forensic evidence"
|
| 1483 |
+
],
|
| 1484 |
+
"breach": [
|
| 1485 |
+
"Activate incident response team",
|
| 1486 |
+
"Preserve evidence and logs",
|
| 1487 |
+
"Notify legal and compliance teams",
|
| 1488 |
+
"Begin forensic investigation"
|
| 1489 |
+
],
|
| 1490 |
+
"phishing": [
|
| 1491 |
+
"Block sender domains/IPs",
|
| 1492 |
+
"Warn all users via security alert",
|
| 1493 |
+
"Check for credential compromise",
|
| 1494 |
+
"Update email security filters"
|
| 1495 |
+
],
|
| 1496 |
+
"ddos": [
|
| 1497 |
+
"Activate DDoS mitigation",
|
| 1498 |
+
"Contact ISP for upstream filtering",
|
| 1499 |
+
"Scale infrastructure if possible",
|
| 1500 |
+
"Monitor traffic patterns"
|
| 1501 |
+
]
|
| 1502 |
+
}
|
| 1503 |
+
|
| 1504 |
+
resolution_times = {
|
| 1505 |
+
"critical": "4-8 hours",
|
| 1506 |
+
"high": "8-24 hours",
|
| 1507 |
+
"medium": "1-3 days",
|
| 1508 |
+
"low": "3-7 days"
|
| 1509 |
+
}
|
| 1510 |
+
|
| 1511 |
+
return {
|
| 1512 |
+
"incident_id": incident_id,
|
| 1513 |
+
"incident_type": request.incident_type,
|
| 1514 |
+
"priority": request.severity.upper(),
|
| 1515 |
+
"response_team": response_teams.get(request.severity, "Security Team"),
|
| 1516 |
+
"immediate_actions": immediate_actions.get(request.incident_type, [
|
| 1517 |
+
"Assess impact and scope",
|
| 1518 |
+
"Implement containment measures",
|
| 1519 |
+
"Begin investigation",
|
| 1520 |
+
"Document findings"
|
| 1521 |
+
]),
|
| 1522 |
+
"estimated_resolution": resolution_times.get(request.severity, "TBD"),
|
| 1523 |
+
"created_timestamp": datetime.now().isoformat()
|
| 1524 |
+
}
|
| 1525 |
+
except Exception as e:
|
| 1526 |
+
logger.error(f"Incident processing failed: {str(e)}")
|
| 1527 |
+
raise HTTPException(status_code=500, detail=f"Incident processing failed: {str(e)}")
|
| 1528 |
+
|
| 1529 |
+
@app.post("/vulnerability_scan")
|
| 1530 |
+
async def vulnerability_scan(request: VulnerabilityAssessment):
|
| 1531 |
+
"""Perform vulnerability assessment"""
|
| 1532 |
+
try:
|
| 1533 |
+
scan_id = f"SCAN-{datetime.now().strftime('%Y%m%d-%H%M%S')}"
|
| 1534 |
+
|
| 1535 |
+
# Generate realistic vulnerability results based on advanced intel
|
| 1536 |
+
vulnerabilities = random.sample(ADVANCED_THREAT_INTELLIGENCE["vulnerabilities"],
|
| 1537 |
+
min(len(ADVANCED_THREAT_INTELLIGENCE["vulnerabilities"]),
|
| 1538 |
+
random.randint(2, 4)))
|
| 1539 |
+
|
| 1540 |
+
return {
|
| 1541 |
+
"scan_id": scan_id,
|
| 1542 |
+
"target": request.target_info,
|
| 1543 |
+
"scan_type": request.scan_type,
|
| 1544 |
+
"vulnerabilities_found": len(vulnerabilities),
|
| 1545 |
+
"critical_count": sum(1 for v in vulnerabilities if v["severity"] == "CRITICAL"),
|
| 1546 |
+
"high_count": sum(1 for v in vulnerabilities if v["severity"] == "HIGH"),
|
| 1547 |
+
"medium_count": sum(1 for v in vulnerabilities if v["severity"] == "MEDIUM"),
|
| 1548 |
+
"vulnerabilities": vulnerabilities,
|
| 1549 |
+
"scan_timestamp": datetime.now().isoformat(),
|
| 1550 |
+
"status": "completed"
|
| 1551 |
+
}
|
| 1552 |
+
except Exception as e:
|
| 1553 |
+
logger.error(f"Vulnerability scan failed: {str(e)}")
|
| 1554 |
+
raise HTTPException(status_code=500, detail=f"Vulnerability scan failed: {str(e)}")
|
| 1555 |
+
|
| 1556 |
+
@app.post("/analyze_logs")
|
| 1557 |
+
async def analyze_security_logs(request: LogAnalysisRequest):
|
| 1558 |
+
"""Analyze security logs for threats and anomalies"""
|
| 1559 |
+
try:
|
| 1560 |
+
# Simulate log analysis
|
| 1561 |
+
log_lines = request.log_data.split('\n')
|
| 1562 |
+
|
| 1563 |
+
suspicious_patterns = [
|
| 1564 |
+
"failed login", "access denied", "suspicious activity",
|
| 1565 |
+
"malware detected", "unusual traffic", "privilege escalation"
|
| 1566 |
+
]
|
| 1567 |
+
|
| 1568 |
+
threats_found = []
|
| 1569 |
+
for line in log_lines[:50]: # Analyze first 50 lines
|
| 1570 |
+
for pattern in suspicious_patterns:
|
| 1571 |
+
if pattern in line.lower():
|
| 1572 |
+
threats_found.append({
|
| 1573 |
+
"pattern": pattern,
|
| 1574 |
+
"log_entry": line.strip(),
|
| 1575 |
+
"severity": random.choice(["HIGH", "MEDIUM", "LOW"])
|
| 1576 |
+
})
|
| 1577 |
+
|
| 1578 |
+
return {
|
| 1579 |
+
"analysis_id": f"LOG-{datetime.now().strftime('%Y%m%d-%H%M%S')}",
|
| 1580 |
+
"log_type": request.log_type,
|
| 1581 |
+
"events_analyzed": len(log_lines),
|
| 1582 |
+
"threats_detected": len(threats_found),
|
| 1583 |
+
"threat_details": threats_found[:10], # Return top 10
|
| 1584 |
+
"analysis_timestamp": datetime.now().isoformat()
|
| 1585 |
+
}
|
| 1586 |
+
except Exception as e:
|
| 1587 |
+
logger.error(f"Log analysis failed: {str(e)}")
|
| 1588 |
+
raise HTTPException(status_code=500, detail=f"Log analysis failed: {str(e)}")
|
| 1589 |
+
|
| 1590 |
+
@app.get("/health")
|
| 1591 |
+
async def health_check():
|
| 1592 |
+
"""System health check"""
|
| 1593 |
+
return {
|
| 1594 |
+
"status": "operational",
|
| 1595 |
+
"platform": "Cyber-LLM Operations Center",
|
| 1596 |
+
"version": "2.0.0",
|
| 1597 |
+
"threat_intel_db": "online",
|
| 1598 |
+
"vulnerability_scanner": "ready",
|
| 1599 |
+
"incident_response": "active",
|
| 1600 |
+
"timestamp": datetime.now().isoformat()
|
| 1601 |
+
}
|
| 1602 |
+
|
| 1603 |
+
@app.get("/threat_intelligence")
|
| 1604 |
+
async def threat_intelligence_summary():
|
| 1605 |
+
"""Get advanced threat intelligence summary with APT attribution"""
|
| 1606 |
+
return {
|
| 1607 |
+
"total_indicators": len(ADVANCED_THREAT_INTELLIGENCE["malicious_ips"]) +
|
| 1608 |
+
len(ADVANCED_THREAT_INTELLIGENCE["suspicious_domains"]) +
|
| 1609 |
+
len(ADVANCED_THREAT_INTELLIGENCE["vulnerabilities"]),
|
| 1610 |
+
"malicious_ips": len(ADVANCED_THREAT_INTELLIGENCE["malicious_ips"]),
|
| 1611 |
+
"suspicious_domains": len(ADVANCED_THREAT_INTELLIGENCE["suspicious_domains"]),
|
| 1612 |
+
"tracked_apt_groups": len(ADVANCED_THREAT_INTELLIGENCE["apt_groups"]),
|
| 1613 |
+
"malware_families": len(ADVANCED_THREAT_INTELLIGENCE["malware_families"]),
|
| 1614 |
+
"attack_techniques": len(ADVANCED_THREAT_INTELLIGENCE["attack_techniques"]),
|
| 1615 |
+
"recent_vulnerabilities": len(ADVANCED_THREAT_INTELLIGENCE["vulnerabilities"]),
|
| 1616 |
+
"apt_groups": list(ADVANCED_THREAT_INTELLIGENCE["apt_groups"].keys()),
|
| 1617 |
+
"top_malware_families": list(ADVANCED_THREAT_INTELLIGENCE["malware_families"].keys())[:5],
|
| 1618 |
+
"last_updated": datetime.now().isoformat()
|
| 1619 |
+
}
|
| 1620 |
+
|
| 1621 |
+
if __name__ == "__main__":
|
| 1622 |
+
import uvicorn
|
| 1623 |
+
port = int(os.environ.get("PORT", 7860))
|
| 1624 |
+
uvicorn.run(app, host="0.0.0.0", port=port)
|
requirements.txt
CHANGED
|
@@ -1,14 +1,4 @@
|
|
| 1 |
-
# Lightweight requirements for HuggingFace Spaces deployment
|
| 2 |
fastapi==0.104.1
|
| 3 |
uvicorn[standard]==0.24.0
|
| 4 |
pydantic==2.5.0
|
| 5 |
python-multipart==0.0.6
|
| 6 |
-
httpx==0.25.2
|
| 7 |
-
requests==2.31.0
|
| 8 |
-
jinja2==3.1.2
|
| 9 |
-
aiofiles==23.2.1
|
| 10 |
-
|
| 11 |
-
# Basic utilities (removing problematic networking libraries)
|
| 12 |
-
dnspython==2.4.2
|
| 13 |
-
cryptography==41.0.7
|
| 14 |
-
psutil==5.9.6
|
|
|
|
|
|
|
| 1 |
fastapi==0.104.1
|
| 2 |
uvicorn[standard]==0.24.0
|
| 3 |
pydantic==2.5.0
|
| 4 |
python-multipart==0.0.6
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
test_app.py
ADDED
|
@@ -0,0 +1,67 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#!/usr/bin/env python3
|
| 2 |
+
"""
|
| 3 |
+
Simple test app for HuggingFace Spaces deployment debugging
|
| 4 |
+
"""
|
| 5 |
+
|
| 6 |
+
from fastapi import FastAPI
|
| 7 |
+
from fastapi.responses import HTMLResponse
|
| 8 |
+
import os
|
| 9 |
+
|
| 10 |
+
# Create FastAPI app
|
| 11 |
+
app = FastAPI(title="Cyber-LLM Test")
|
| 12 |
+
|
| 13 |
+
@app.get("/")
|
| 14 |
+
async def root():
|
| 15 |
+
"""Simple test route"""
|
| 16 |
+
return {"message": "Cyber-LLM API is running!", "status": "online"}
|
| 17 |
+
|
| 18 |
+
@app.get("/health")
|
| 19 |
+
async def health_check():
|
| 20 |
+
"""Health check endpoint"""
|
| 21 |
+
return {"status": "healthy", "service": "cyber-llm"}
|
| 22 |
+
|
| 23 |
+
@app.get("/ui", response_class=HTMLResponse)
|
| 24 |
+
async def simple_ui():
|
| 25 |
+
"""Simple UI test"""
|
| 26 |
+
html = """
|
| 27 |
+
<!DOCTYPE html>
|
| 28 |
+
<html>
|
| 29 |
+
<head>
|
| 30 |
+
<title>Cyber-LLM Test</title>
|
| 31 |
+
<meta charset="UTF-8">
|
| 32 |
+
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
| 33 |
+
<style>
|
| 34 |
+
body {
|
| 35 |
+
font-family: monospace;
|
| 36 |
+
background: #0a0a0a;
|
| 37 |
+
color: #00ff00;
|
| 38 |
+
padding: 20px;
|
| 39 |
+
text-align: center;
|
| 40 |
+
}
|
| 41 |
+
.container {
|
| 42 |
+
max-width: 800px;
|
| 43 |
+
margin: 0 auto;
|
| 44 |
+
border: 2px solid #00ff00;
|
| 45 |
+
padding: 40px;
|
| 46 |
+
border-radius: 10px;
|
| 47 |
+
}
|
| 48 |
+
h1 { color: #ff0040; margin-bottom: 20px; }
|
| 49 |
+
.status { color: #00ffff; font-size: 18px; }
|
| 50 |
+
</style>
|
| 51 |
+
</head>
|
| 52 |
+
<body>
|
| 53 |
+
<div class="container">
|
| 54 |
+
<h1>🛡️ CYBER-LLM OPERATIONS CENTER</h1>
|
| 55 |
+
<div class="status">✅ SYSTEM ONLINE</div>
|
| 56 |
+
<p>Advanced Cybersecurity AI Platform</p>
|
| 57 |
+
<p>HuggingFace Spaces Deployment: <span style="color: #00ffff;">SUCCESS</span></p>
|
| 58 |
+
</div>
|
| 59 |
+
</body>
|
| 60 |
+
</html>
|
| 61 |
+
"""
|
| 62 |
+
return HTMLResponse(content=html)
|
| 63 |
+
|
| 64 |
+
if __name__ == "__main__":
|
| 65 |
+
import uvicorn
|
| 66 |
+
port = int(os.environ.get("PORT", 7860))
|
| 67 |
+
uvicorn.run(app, host="0.0.0.0", port=port)
|