MCP Kali Pentest

""" Autonomous Penetration Testing Decision Engine Makes intelligent decisions about next steps based on findings """ import asyncio import logging from typing import Dict, List, Any, Optional from datetime import datetime import json from lm_studio_client import LMStudioClient import tools logger = logging.getLogger(__name__) class AutonomousDecisionEngine: """AI-powered autonomous penetration testing engine""" def __init__(self, lm_studio_client: LMStudioClient): self.lm_client = lm_studio_client self.decision_history: List[Dict[str, Any]] = [] async def create_initial_plan(self, session: Dict[str, Any]) -> Dict[str, Any]: """Create initial penetration testing plan""" target = session["target"] scope = session.get("scope", [target]) roe = session.get("roe", {}) depth = session.get("depth", "vulnerability_scan") objectives = [] if depth == "reconnaissance": objectives = ["Gather information about target"] elif depth == "vulnerability_scan": objectives = ["Identify services", "Find vulnerabilities"] elif depth == "exploitation": objectives = ["Identify services", "Find vulnerabilities", "Attempt safe exploitation"] elif depth == "post_exploitation": objectives = ["Full penetration test", "Demonstrate impact"] plan = await self.lm_client.create_attack_plan( target=target, scope=scope, objectives=objectives, constraints=roe ) return plan async def run_pentest(self, session: Dict[str, Any]): """Execute autonomous penetration test""" logger.info(f"Starting autonomous pentest for session {session['id']}") try: # Phase 1: Reconnaissance await self._run_reconnaissance_phase(session) # Phase 2: Vulnerability Identification if session["depth"] in ["vulnerability_scan", "exploitation", "post_exploitation"]: await self._run_vulnerability_phase(session) # Phase 3: Exploitation (if authorized) if session["depth"] in ["exploitation", "post_exploitation"]: await self._run_exploitation_phase(session) # Phase 4: Post-exploitation (if authorized) if session["depth"] == "post_exploitation": await self._run_post_exploitation_phase(session) session["status"] = "completed" session["completed_at"] = datetime.now().isoformat() except Exception as e: logger.error(f"Error in autonomous pentest: {e}", exc_info=True) session["status"] = "error" session["error"] = str(e) async def _run_reconnaissance_phase(self, session: Dict[str, Any]): """Phase 1: Information gathering""" target = session["target"] logger.info(f"Running reconnaissance phase on {target}") session["timeline"].append({ "phase": "reconnaissance", "started_at": datetime.now().isoformat() }) # Determine target type (IP, domain, URL) target_type = self._determine_target_type(target) if target_type == "domain": # DNS enumeration logger.info("Running DNS enumeration") dns_result = await tools.dns_enum(target) self._record_finding(session, "dns_enum", dns_result) # Subdomain enumeration results if dns_result.get("subdomains"): session["scope"].extend(dns_result["subdomains"][:10]) # Add top 10 subdomains elif target_type in ["ip", "domain"]: # Network reconnaissance logger.info("Running Nmap scan") nmap_result = await tools.nmap_scan(target, scan_type="full") self._record_finding(session, "nmap_scan", nmap_result) # Analyze services and suggest next steps await self._analyze_services(session, nmap_result) elif target_type == "url": # Web application reconnaissance logger.info("Running web reconnaissance") # Nikto scan nikto_result = await tools.nikto_scan(target) self._record_finding(session, "nikto_scan", nikto_result) # Directory enumeration gobuster_result = await tools.gobuster_scan( target, wordlist="/usr/share/wordlists/dirb/common.txt", extensions=["php", "asp", "aspx", "jsp", "html"] ) self._record_finding(session, "gobuster_scan", gobuster_result) # Get AI suggestions for next phase suggestion = await self.get_suggestions(session, "Reconnaissance complete. What should we do next?") session["timeline"][-1]["completed_at"] = datetime.now().isoformat() session["timeline"][-1]["suggestion"] = suggestion async def _run_vulnerability_phase(self, session: Dict[str, Any]): """Phase 2: Vulnerability identification""" logger.info("Running vulnerability identification phase") session["timeline"].append({ "phase": "vulnerability_identification", "started_at": datetime.now().isoformat() }) target = session["target"] target_type = self._determine_target_type(target) # Get findings from reconnaissance recon_findings = [f for f in session["findings"] if f["phase"] == "reconnaissance"] if target_type == "url": # Web application vulnerability scanning logger.info("Running web vulnerability scans") # Nuclei scan nuclei_result = await tools.nuclei_scan( target, severity=["critical", "high", "medium"] ) self._record_finding(session, "nuclei_scan", nuclei_result, "vulnerability_identification") # Check if it's WordPress if any("wordpress" in str(f).lower() for f in recon_findings): logger.info("WordPress detected, running WPScan") wpscan_result = await tools.wpscan(target, enumerate="vp") self._record_finding(session, "wpscan", wpscan_result, "vulnerability_identification") # SQL injection testing on discovered forms/parameters sqlmap_result = await tools.sqlmap_scan(target, level=2, risk=2) self._record_finding(session, "sqlmap_scan", sqlmap_result, "vulnerability_identification") # SSL/TLS analysis if HTTPS if target.startswith("https://"): hostname = target.replace("https://", "").split("/")[0] ssl_result = await tools.ssl_scan(hostname, 443) self._record_finding(session, "ssl_scan", ssl_result, "vulnerability_identification") else: # Network vulnerability scanning logger.info("Running network vulnerability scans") # Service-specific vulnerability checks based on open ports for finding in recon_findings: if finding["tool"] == "nmap" and "findings" in finding["result"]: services = finding["result"]["findings"].get("services", []) for service in services[:5]: # Limit to first 5 services await self._scan_service_vulnerabilities(session, target, service) # Analyze all vulnerabilities and prioritize await self._analyze_vulnerabilities(session) session["timeline"][-1]["completed_at"] = datetime.now().isoformat() async def _run_exploitation_phase(self, session: Dict[str, Any]): """Phase 3: Safe exploitation attempts""" logger.info("Running exploitation phase") # Check rules of engagement if not session.get("roe", {}).get("allow_exploitation", False): logger.warning("Exploitation not authorized in rules of engagement") return session["timeline"].append({ "phase": "exploitation", "started_at": datetime.now().isoformat() }) # Get high-risk vulnerabilities vulnerabilities = [ f for f in session["findings"] if f["phase"] == "vulnerability_identification" and self._is_exploitable(f) ] # Sort by risk/severity vulnerabilities.sort(key=lambda x: self._get_risk_score(x), reverse=True) # Attempt exploitation on top vulnerabilities for vuln in vulnerabilities[:3]: # Limit to top 3 await self._attempt_exploitation(session, vuln) session["timeline"][-1]["completed_at"] = datetime.now().isoformat() async def _run_post_exploitation_phase(self, session: Dict[str, Any]): """Phase 4: Post-exploitation activities""" logger.info("Running post-exploitation phase") if not session.get("roe", {}).get("allow_post_exploitation", False): logger.warning("Post-exploitation not authorized") return session["timeline"].append({ "phase": "post_exploitation", "started_at": datetime.now().isoformat() }) # Check if we have any successful exploits successful_exploits = [ f for f in session["findings"] if f["phase"] == "exploitation" and f.get("result", {}).get("success") ] if not successful_exploits: logger.info("No successful exploits to follow up on") return # Post-exploitation activities would go here # This is a placeholder for actual post-exploitation modules session["timeline"][-1]["completed_at"] = datetime.now().isoformat() async def _analyze_services(self, session: Dict[str, Any], nmap_result: Dict[str, Any]): """Analyze discovered services and identify potential vulnerabilities""" if "findings" not in nmap_result or "services" not in nmap_result["findings"]: return services = nmap_result["findings"]["services"] # Use AI to identify vulnerabilities for service in services[:10]: # Limit to 10 services vulnerabilities = await self.lm_client.identify_vulnerabilities(service) if vulnerabilities: self._record_finding( session, "vulnerability_identification", { "service": service, "vulnerabilities": vulnerabilities }, "reconnaissance" ) async def _scan_service_vulnerabilities( self, session: Dict[str, Any], target: str, service: Dict[str, Any] ): """Scan specific service for vulnerabilities""" service_name = service.get("service", "").lower() port = service.get("port") logger.info(f"Scanning service {service_name} on port {port}") # Service-specific scanning if service_name in ["smb", "microsoft-ds"]: # SMB enumeration enum_result = await tools.enum4linux(target) self._record_finding(session, "enum4linux", enum_result, "vulnerability_identification") elif service_name == "snmp": # SNMP enumeration snmp_result = await tools.snmp_check(target) self._record_finding(session, "snmp_check", snmp_result, "vulnerability_identification") elif service_name in ["http", "https"]: # Web service scanning url = f"http{'s' if service_name == 'https' else ''}://{target}:{port}" nikto_result = await tools.nikto_scan(url) self._record_finding(session, "nikto_scan", nikto_result, "vulnerability_identification") # Search for known exploits search_query = f"{service_name} {service.get('version', '')}" exploits = await tools.searchsploit(search_query) if exploits.get("exploits"): self._record_finding( session, "exploit_search", { "service": service, "exploits": exploits["exploits"][:5] # Top 5 }, "vulnerability_identification" ) async def _analyze_vulnerabilities(self, session: Dict[str, Any]): """Analyze all vulnerabilities and create risk assessment""" vuln_findings = [ f for f in session["findings"] if f["phase"] == "vulnerability_identification" ] if not vuln_findings: return # Use AI to analyze and prioritize analysis = await self.lm_client.analyze_scan_results( "vulnerability_assessment", { "target": session["target"], "findings": vuln_findings } ) self._record_finding( session, "vulnerability_analysis", analysis, "vulnerability_identification" ) async def _attempt_exploitation(self, session: Dict[str, Any], vulnerability: Dict[str, Any]): """Safely attempt to exploit a vulnerability""" logger.info(f"Attempting exploitation of {vulnerability.get('tool')}") # Get AI recommendation on exploitation approach messages = [ { "role": "system", "content": "You are a penetration testing expert. Suggest a safe exploitation approach." }, { "role": "user", "content": f"Vulnerability: {json.dumps(vulnerability)}\n\nSuggest exploitation approach." } ] suggestion = await self.lm_client.chat_completion(messages) self._record_finding( session, "exploitation_attempt", { "vulnerability": vulnerability, "approach": suggestion, "status": "attempted" }, "exploitation" ) def _record_finding( self, session: Dict[str, Any], tool: str, result: Dict[str, Any], phase: Optional[str] = None ): """Record finding in session""" finding = { "timestamp": datetime.now().isoformat(), "tool": tool, "result": result, "phase": phase or "reconnaissance" } session["findings"].append(finding) logger.info(f"Recorded finding from {tool} in phase {phase}") def _determine_target_type(self, target: str) -> str: """Determine if target is IP, domain, or URL""" if target.startswith("http://") or target.startswith("https://"): return "url" elif target.replace(".", "").isdigit(): return "ip" else: return "domain" def _is_exploitable(self, finding: Dict[str, Any]) -> bool: """Determine if a finding is exploitable""" result = finding.get("result", {}) # Check for explicit vulnerability markers if result.get("vulnerable"): return True if result.get("vulnerabilities") and len(result["vulnerabilities"]) > 0: return True if result.get("exploits") and len(result["exploits"]) > 0: return True return False def _get_risk_score(self, finding: Dict[str, Any]) -> int: """Calculate risk score for a finding""" score = 0 result = finding.get("result", {}) # Check severity if "critical" in str(result).lower(): score += 10 elif "high" in str(result).lower(): score += 7 elif "medium" in str(result).lower(): score += 5 elif "low" in str(result).lower(): score += 2 # Check for known exploits if result.get("exploits"): score += 5 # Check for CVE if "cve" in str(result).lower(): score += 3 return score async def get_suggestions( self, session: Dict[str, Any], context: Optional[str] = None ) -> Dict[str, Any]: """Get AI-powered suggestions for next steps""" completed_tools = list(set([f["tool"] for f in session["findings"]])) suggestion = await self.lm_client.suggest_next_action( current_findings=session["findings"], completed_scans=completed_tools, target_info={ "target": session["target"], "scope": session["scope"] }, rules_of_engagement=session.get("roe", {}) ) self.decision_history.append({ "timestamp": datetime.now().isoformat(), "session_id": session["id"], "context": context, "suggestion": suggestion }) return suggestion async def auto_execute_suggestion( self, session: Dict[str, Any], suggestion: Dict[str, Any] ) -> Dict[str, Any]: """Automatically execute the suggested action""" action = suggestion.get("recommended_action") parameters = suggestion.get("parameters", {}) logger.info(f"Auto-executing: {action} with parameters: {parameters}") try: # Get the tool function tool_func = getattr(tools, action, None) if tool_func and callable(tool_func): result = await tool_func(**parameters) self._record_finding(session, action, result) return { "success": True, "action": action, "result": result } else: return { "success": False, "error": f"Tool {action} not found" } except Exception as e: logger.error(f"Error auto-executing {action}: {e}") return { "success": False, "error": str(e) }