mirror of
https://github.com/CyberSecurityUP/NeuroSploit.git
synced 2026-02-12 22:12:45 +00:00
257 lines
9.4 KiB
Python
257 lines
9.4 KiB
Python
#!/usr/bin/env python3
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"""
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Exploitation Agent - Vulnerability exploitation and access gaining
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"""
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import json
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import logging
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from typing import Dict, List
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from core.llm_manager import LLMManager
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from tools.exploitation import (
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ExploitDatabase,
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MetasploitWrapper,
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WebExploiter,
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SQLInjector,
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RCEExploiter,
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BufferOverflowExploiter
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)
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logger = logging.getLogger(__name__)
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class ExploitationAgent:
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"""Agent responsible for vulnerability exploitation"""
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def __init__(self, config: Dict):
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"""Initialize exploitation agent"""
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self.config = config
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self.llm = LLMManager(config)
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self.exploit_db = ExploitDatabase(config)
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self.metasploit = MetasploitWrapper(config)
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self.web_exploiter = WebExploiter(config)
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self.sql_injector = SQLInjector(config)
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self.rce_exploiter = RCEExploiter(config)
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self.bof_exploiter = BufferOverflowExploiter(config)
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logger.info("ExploitationAgent initialized")
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def execute(self, target: str, context: Dict) -> Dict:
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"""Execute exploitation phase"""
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logger.info(f"Starting exploitation on {target}")
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results = {
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"target": target,
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"status": "running",
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"successful_exploits": [],
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"failed_attempts": [],
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"shells_obtained": [],
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"credentials_found": [],
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"ai_recommendations": {}
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}
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try:
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# Get reconnaissance data from context
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recon_data = context.get("phases", {}).get("recon", {})
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# Phase 1: Vulnerability Analysis
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logger.info("Phase 1: Analyzing vulnerabilities")
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vulnerabilities = self._identify_vulnerabilities(recon_data)
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# Phase 2: AI-powered Exploit Selection
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logger.info("Phase 2: AI exploit selection")
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exploit_plan = self._ai_exploit_planning(vulnerabilities, recon_data)
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results["ai_recommendations"] = exploit_plan
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# Phase 3: Execute Exploits
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logger.info("Phase 3: Executing exploits")
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for vuln in vulnerabilities[:5]: # Limit to top 5 vulnerabilities
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exploit_result = self._attempt_exploitation(vuln, target)
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if exploit_result.get("success"):
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results["successful_exploits"].append(exploit_result)
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logger.info(f"Successful exploit: {vuln.get('type')}")
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# Check for shell access
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if exploit_result.get("shell_access"):
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results["shells_obtained"].append(exploit_result["shell_info"])
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else:
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results["failed_attempts"].append(exploit_result)
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# Phase 4: Post-Exploitation Intelligence
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if results["successful_exploits"]:
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logger.info("Phase 4: Post-exploitation intelligence gathering")
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results["post_exploit_intel"] = self._gather_post_exploit_intel(
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results["successful_exploits"]
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)
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results["status"] = "completed"
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logger.info("Exploitation phase completed")
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except Exception as e:
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logger.error(f"Error during exploitation: {e}")
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results["status"] = "error"
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results["error"] = str(e)
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return results
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def _identify_vulnerabilities(self, recon_data: Dict) -> List[Dict]:
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"""Identify exploitable vulnerabilities from recon data"""
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vulnerabilities = []
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# Check network scan results
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network_scan = recon_data.get("network_scan", {})
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for host, data in network_scan.get("hosts", {}).items():
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for port in data.get("open_ports", []):
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vuln = {
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"type": "network_service",
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"host": host,
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"port": port.get("port"),
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"service": port.get("service"),
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"version": port.get("version")
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}
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vulnerabilities.append(vuln)
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# Check web vulnerabilities
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web_analysis = recon_data.get("web_analysis", {})
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for vuln_type in ["sql_injection", "xss", "lfi", "rfi", "rce"]:
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if web_analysis.get(vuln_type):
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vulnerabilities.append({
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"type": vuln_type,
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"details": web_analysis[vuln_type]
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})
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return vulnerabilities
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def _ai_exploit_planning(self, vulnerabilities: List[Dict], recon_data: Dict) -> Dict:
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"""Use AI to plan exploitation strategy"""
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prompt = self.llm.get_prompt(
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"exploitation",
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"ai_exploit_planning_user",
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default=f"""
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Plan an exploitation strategy based on the following data:
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Vulnerabilities Identified:
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{json.dumps(vulnerabilities, indent=2)}
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Reconnaissance Data:
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{json.dumps(recon_data, indent=2)}
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Provide:
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1. Prioritized exploitation order
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2. Recommended exploits for each vulnerability
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3. Payload suggestions
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4. Evasion techniques
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5. Fallback strategies
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6. Success probability estimates
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Response in JSON format with detailed exploitation roadmap.
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"""
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)
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system_prompt = self.llm.get_prompt(
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"exploitation",
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"ai_exploit_planning_system",
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default="""You are an expert exploit developer and penetration tester.
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Create sophisticated exploitation plans considering detection, success rates, and impact.
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Prioritize stealthy, reliable exploits over noisy attempts."""
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)
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try:
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formatted_prompt = prompt.format(
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vulnerabilities_json=json.dumps(vulnerabilities, indent=2),
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recon_data_json=json.dumps(recon_data, indent=2)
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)
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response = self.llm.generate(formatted_prompt, system_prompt)
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return json.loads(response)
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except Exception as e:
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logger.error(f"AI exploit planning error: {e}")
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return {"error": str(e)}
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def _attempt_exploitation(self, vulnerability: Dict, target: str) -> Dict:
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"""Attempt to exploit a specific vulnerability"""
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vuln_type = vulnerability.get("type")
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result = {
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"vulnerability": vulnerability,
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"success": False,
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"method": None,
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"details": {}
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}
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try:
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if vuln_type == "sql_injection":
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result = self.sql_injector.exploit(target, vulnerability)
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elif vuln_type in ["xss", "csrf"]:
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result = self.web_exploiter.exploit(target, vulnerability)
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elif vuln_type in ["rce", "command_injection"]:
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result = self.rce_exploiter.exploit(target, vulnerability)
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elif vuln_type == "buffer_overflow":
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result = self.bof_exploiter.exploit(target, vulnerability)
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elif vuln_type == "network_service":
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result = self._exploit_network_service(target, vulnerability)
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else:
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# Use Metasploit for generic exploitation
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result = self.metasploit.exploit(target, vulnerability)
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except Exception as e:
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logger.error(f"Exploitation error for {vuln_type}: {e}")
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result["error"] = str(e)
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return result
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def _exploit_network_service(self, target: str, vulnerability: Dict) -> Dict:
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"""Exploit network service vulnerabilities"""
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service = vulnerability.get("service", "").lower()
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# Check exploit database for known exploits
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exploits = self.exploit_db.search(service, vulnerability.get("version"))
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if exploits:
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logger.info(f"Found {len(exploits)} exploits for {service}")
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for exploit in exploits[:3]: # Try top 3 exploits
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result = self.metasploit.run_exploit(
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exploit["module"],
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target,
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vulnerability.get("port")
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)
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if result.get("success"):
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return result
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return {"success": False, "message": "No suitable exploits found"}
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def _gather_post_exploit_intel(self, successful_exploits: List[Dict]) -> Dict:
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"""Gather intelligence after successful exploitation"""
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intel = {
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"system_info": [],
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"user_accounts": [],
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"network_info": [],
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"installed_software": [],
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"credentials": []
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}
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for exploit in successful_exploits:
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if exploit.get("shell_access"):
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shell = exploit["shell_info"]
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# Gather system information
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# This would execute actual commands on compromised system
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# Placeholder for demonstration
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intel["system_info"].append({
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"os": "detected_os",
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"hostname": "detected_hostname",
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"architecture": "x64"
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})
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return intel
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def generate_custom_exploit(self, vulnerability: Dict) -> str:
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"""Generate custom exploit using AI"""
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target_info = {
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"vulnerability": vulnerability,
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"requirements": "Create working exploit code"
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}
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return self.llm.generate_payload(target_info, vulnerability.get("type"))
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