mirror of
https://github.com/mblanke/ThreatHunt.git
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166 lines
4.8 KiB
Python
166 lines
4.8 KiB
Python
"""
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Playbook Execution Engine
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Executes automated response playbooks based on triggers.
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"""
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from typing import Dict, Any, List
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from datetime import datetime, timezone
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import asyncio
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class PlaybookEngine:
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"""Engine for executing playbooks"""
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def __init__(self):
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"""Initialize playbook engine"""
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self.actions_registry = {
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"send_notification": self._action_send_notification,
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"create_case": self._action_create_case,
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"isolate_host": self._action_isolate_host,
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"collect_artifact": self._action_collect_artifact,
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"block_ip": self._action_block_ip,
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"send_email": self._action_send_email,
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}
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async def execute_playbook(
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self,
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playbook: Dict[str, Any],
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context: Dict[str, Any]
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) -> Dict[str, Any]:
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"""
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Execute a playbook
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Args:
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playbook: Playbook definition
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context: Execution context with relevant data
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Returns:
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Execution result
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"""
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results = []
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errors = []
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actions = playbook.get("actions", [])
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for action in actions:
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action_type = action.get("type")
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action_params = action.get("params", {})
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try:
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# Get action handler
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handler = self.actions_registry.get(action_type)
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if not handler:
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errors.append(f"Unknown action type: {action_type}")
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continue
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# Execute action
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result = await handler(action_params, context)
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results.append({
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"action": action_type,
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"status": "success",
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"result": result
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})
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except Exception as e:
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errors.append(f"Error in action {action_type}: {str(e)}")
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results.append({
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"action": action_type,
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"status": "failed",
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"error": str(e)
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})
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return {
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"status": "completed" if not errors else "completed_with_errors",
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"results": results,
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"errors": errors
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}
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async def _action_send_notification(
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self,
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params: Dict[str, Any],
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context: Dict[str, Any]
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) -> Dict[str, Any]:
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"""Send a notification"""
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# In production, this would create a notification in the database
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# and push it via WebSocket
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return {
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"notification_sent": True,
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"message": params.get("message", "Playbook notification")
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}
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async def _action_create_case(
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self,
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params: Dict[str, Any],
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context: Dict[str, Any]
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) -> Dict[str, Any]:
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"""Create a new case"""
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# In production, this would create a case in the database
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return {
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"case_created": True,
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"case_title": params.get("title", "Automated Case"),
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"case_id": "placeholder_id"
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}
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async def _action_isolate_host(
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self,
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params: Dict[str, Any],
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context: Dict[str, Any]
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) -> Dict[str, Any]:
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"""Isolate a host"""
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# In production, this would call Velociraptor or other tools
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# to isolate the host from the network
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host_id = params.get("host_id")
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return {
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"host_isolated": True,
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"host_id": host_id
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}
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async def _action_collect_artifact(
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self,
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params: Dict[str, Any],
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context: Dict[str, Any]
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) -> Dict[str, Any]:
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"""Collect an artifact from a host"""
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# In production, this would trigger Velociraptor collection
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return {
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"collection_started": True,
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"artifact": params.get("artifact_name"),
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"client_id": params.get("client_id")
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}
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async def _action_block_ip(
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self,
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params: Dict[str, Any],
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context: Dict[str, Any]
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) -> Dict[str, Any]:
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"""Block an IP address"""
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# In production, this would update firewall rules
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ip_address = params.get("ip_address")
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return {
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"ip_blocked": True,
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"ip_address": ip_address
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}
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async def _action_send_email(
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self,
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params: Dict[str, Any],
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context: Dict[str, Any]
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) -> Dict[str, Any]:
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"""Send an email"""
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# In production, this would send an actual email
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return {
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"email_sent": True,
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"to": params.get("to"),
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"subject": params.get("subject")
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}
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def get_playbook_engine() -> PlaybookEngine:
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"""
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Factory function to create playbook engine
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Returns:
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Configured PlaybookEngine instance
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"""
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return PlaybookEngine()
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