misp_analyzer.py aktualisiert
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misp_analyzer.py
505
misp_analyzer.py
@ -1,9 +1,12 @@
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"""Index analyzer plugin for MISP."""
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"""Index analyzer plugin for MISP - Enhanced for large-scale processing."""
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import logging
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import ntpath
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import re
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import requests
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import time
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from collections import defaultdict
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from typing import List, Dict, Set, Any
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from flask import current_app
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from timesketch.lib.analyzers import interface
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@ -14,11 +17,11 @@ logger = logging.getLogger("timesketch.analyzers.misp")
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class MispAnalyzer(interface.BaseAnalyzer):
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"""Analyzer for MISP."""
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"""Enhanced Analyzer for MISP with large-scale processing capabilities."""
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NAME = "misp_analyzer"
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DISPLAY_NAME = "MISP"
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DESCRIPTION = "Mark events using MISP"
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DISPLAY_NAME = "MISP Enhanced"
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DESCRIPTION = "Mark events using MISP with cross-org and large-scale support"
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def __init__(self, index_name, sketch_id, timeline_id=None, **kwargs):
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"""Initialize the Analyzer."""
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@ -30,285 +33,431 @@ class MispAnalyzer(interface.BaseAnalyzer):
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self._query_string = kwargs.get("query_string")
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self._attr = kwargs.get("attr")
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self._timesketch_attr = kwargs.get("timesketch_attr")
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# Enhanced configuration
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self.include_community = kwargs.get("include_community", True)
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self.batch_size = kwargs.get("batch_size", 100) # Process events in batches
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self.api_batch_size = kwargs.get("api_batch_size", 50) # API call batching
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self.max_retries = kwargs.get("max_retries", 3)
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self.request_timeout = kwargs.get("request_timeout", 120) # 2 minutes
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self.chunk_size = kwargs.get("chunk_size", 1000) # Memory management
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# Regex patterns
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self.ip_pattern = re.compile(r'\b(?:[0-9]{1,3}\.){3}[0-9]{1,3}\b')
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# Track marked events to prevent duplicates
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# Track processed items to prevent duplicates
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self.marked_events = set()
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self.processed_indicators = set()
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# Statistics
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self.stats = {
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'events_processed': 0,
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'indicators_extracted': 0,
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'api_calls_made': 0,
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'events_marked': 0,
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'errors': 0
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}
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@staticmethod
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def get_kwargs():
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"""Get kwargs for the analyzer."""
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"""Get kwargs for the analyzer with enhanced options."""
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to_query = [
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{
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"query_string": "md5_hash:*",
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"attr": "md5",
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"timesketch_attr": "md5_hash",
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"include_community": True,
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"batch_size": 100,
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"api_batch_size": 50,
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},
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{
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"query_string": "sha1_hash:*",
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"attr": "sha1",
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"timesketch_attr": "sha1_hash",
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"include_community": True,
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"batch_size": 100,
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"api_batch_size": 50,
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},
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{
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"query_string": "sha256_hash:*",
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"attr": "sha256",
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"timesketch_attr": "sha256_hash",
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"include_community": True,
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"batch_size": 100,
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"api_batch_size": 50,
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},
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{
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"query_string": "filename:*",
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"attr": "filename",
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"timesketch_attr": "filename",
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"include_community": True,
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"batch_size": 100,
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"api_batch_size": 50,
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},
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{
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"query_string": "message:*",
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"attr": "ip", # Generic IP instead of ip-src/ip-dst
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"attr": "ip",
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"timesketch_attr": "message",
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"include_community": True,
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"batch_size": 100,
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"api_batch_size": 50,
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},
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{
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"query_string": "source_ip:*",
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"query_string": "source_ip:* OR src_ip:* OR client_ip:*",
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"attr": "ip",
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"timesketch_attr": "source_ip",
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"include_community": True,
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"batch_size": 100,
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"api_batch_size": 50,
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},
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]
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return to_query
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def _is_valid_ip(self, ip_str):
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"""Validate IP address."""
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def _is_valid_ip(self, ip_str: str) -> bool:
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"""Validate IP address with enhanced filtering."""
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try:
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import ipaddress
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ip_str = ip_str.strip()
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ipaddress.ip_address(ip_str)
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if ip_str.startswith(('0.', '127.', '255.255.255.255')):
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ip_obj = ipaddress.ip_address(ip_str)
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# Filter out private, loopback, and other non-routable IPs
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if (ip_obj.is_private or ip_obj.is_loopback or
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ip_obj.is_multicast or ip_obj.is_reserved or
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ip_obj.is_link_local):
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return False
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# Additional nginx log specific filters
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if ip_str.startswith(('0.', '255.255.255.255', '169.254.')):
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return False
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return True
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except (ValueError, AttributeError):
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return False
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def _is_valid_hash(self, hash_str, hash_type):
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def _is_valid_hash(self, hash_str: str, hash_type: str) -> bool:
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"""Validate hash format."""
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if not hash_str:
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return False
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hash_str = hash_str.strip().lower()
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if hash_type == "md5":
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return len(hash_str) == 32 and all(c in '0123456789abcdef' for c in hash_str)
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elif hash_type == "sha1":
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return len(hash_str) == 40 and all(c in '0123456789abcdef' for c in hash_str)
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elif hash_type == "sha256":
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return len(hash_str) == 64 and all(c in '0123456789abcdef' for c in hash_str)
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hash_lengths = {"md5": 32, "sha1": 40, "sha256": 64}
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expected_length = hash_lengths.get(hash_type)
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return False
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if not expected_length:
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return False
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return (len(hash_str) == expected_length and
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all(c in '0123456789abcdef' for c in hash_str))
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def query_misp_single(self, value, attr):
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"""Query MISP for a single value - ENHANCED for cross-org visibility."""
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results = []
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def _make_misp_request(self, payload: Dict[str, Any], retry_count: int = 0) -> List[Dict]:
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"""Make MISP API request with retry logic."""
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try:
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response = requests.post(
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f"{self.misp_url}/attributes/restSearch/",
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json=payload,
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headers={"Authorization": self.misp_api_key},
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verify=False,
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timeout=self.request_timeout,
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)
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if response.status_code == 200:
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data = response.json()
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return data.get("response", {}).get("Attribute", [])
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elif response.status_code == 429: # Rate limited
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wait_time = min(2 ** retry_count, 60) # Exponential backoff, max 60s
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logger.warning(f"Rate limited, waiting {wait_time}s before retry")
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time.sleep(wait_time)
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raise requests.exceptions.RequestException("Rate limited")
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else:
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logger.warning(f"MISP API returned status {response.status_code}")
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return []
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except (requests.exceptions.Timeout, requests.exceptions.ConnectionError) as e:
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if retry_count < self.max_retries:
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wait_time = min(2 ** retry_count * 5, 120) # Exponential backoff
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logger.warning(f"Request failed (attempt {retry_count + 1}), retrying in {wait_time}s: {e}")
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time.sleep(wait_time)
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return self._make_misp_request(payload, retry_count + 1)
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else:
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logger.error(f"Request failed after {self.max_retries} retries: {e}")
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self.stats['errors'] += 1
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return []
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except Exception as e:
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logger.error(f"Unexpected error in MISP request: {e}")
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self.stats['errors'] += 1
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return []
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def query_misp_batch(self, indicators: List[str], attr: str) -> Dict[str, List[Dict]]:
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"""Query MISP for multiple indicators efficiently."""
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results = defaultdict(list)
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# Query both ip-src and ip-dst for IPs, include cross-org events
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# Determine search types based on attribute
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if attr == "ip":
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search_types = ["ip-src", "ip-dst"]
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else:
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search_types = [attr]
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for search_type in search_types:
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try:
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# Include events from other organizations
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# Batch indicators to reduce API calls
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for i in range(0, len(indicators), self.api_batch_size):
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batch = indicators[i:i + self.api_batch_size]
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# Build payload with distribution settings
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distribution_levels = [0] # Own org
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if self.include_community:
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distribution_levels.extend([1, 2]) # Community and connected orgs
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payload = {
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"returnFormat": "json",
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"value": value,
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"returnFormat": "json",
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"value": batch,
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"type": search_type,
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# Include events from all organizations with proper distribution
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"enforceWarninglist": False, # Don't filter known-good IPs
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"includeDecayScore": False, # Skip decay scores for speed
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"includeFullModel": False, # Skip full model for speed
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"decayingModel": [], # No decaying model filters
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"excludeDecayed": False, # Include older indicators
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# Distribution levels: 0=Own org, 1=Community, 2=Connected, 3=All, 5=Inherit
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"distribution": [0, 1]
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"enforceWarninglist": False,
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"includeDecayScore": False,
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"includeFullModel": False,
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"excludeDecayed": False,
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"distribution": distribution_levels,
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"limit": 10000, # High limit for large datasets
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}
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response = requests.post(
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f"{self.misp_url}/attributes/restSearch/",
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json=payload,
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headers={"Authorization": self.misp_api_key},
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verify=False,
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timeout=30,
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)
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if response.status_code == 200:
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data = response.json()
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attributes = data.get("response", {}).get("Attribute", [])
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results.extend(attributes)
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except Exception:
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continue
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self.stats['api_calls_made'] += 1
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logger.info(f"Querying MISP for {len(batch)} {search_type} indicators (call #{self.stats['api_calls_made']})")
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return results
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batch_results = self._make_misp_request(payload)
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# Group results by indicator value
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for result in batch_results:
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indicator_value = result.get("value", "").strip()
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if indicator_value in batch:
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results[indicator_value].append(result)
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# Rate limiting courtesy pause
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time.sleep(0.5)
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return dict(results)
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def mark_event(self, event, result, attr):
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"""Add MISP intelligence to event - FIXED to prevent duplicates."""
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def extract_indicators_from_event(self, event: Any, attr: str, timesketch_attr: str) -> List[str]:
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"""Extract indicators from a single event."""
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loc = event.source.get(timesketch_attr)
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if not loc:
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return []
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indicators = []
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loc_str = str(loc)
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if attr == "ip" and timesketch_attr == "message":
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# Extract IPs from nginx access log messages
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ip_matches = self.ip_pattern.findall(loc_str)
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indicators = [ip for ip in ip_matches if self._is_valid_ip(ip)]
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elif attr == "ip" and timesketch_attr in ["source_ip", "src_ip", "client_ip"]:
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if self._is_valid_ip(loc_str):
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indicators = [loc_str]
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elif attr in ["md5", "sha1", "sha256"]:
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if self._is_valid_hash(loc_str, attr):
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indicators = [loc_str]
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elif attr == "filename":
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filename = ntpath.basename(loc_str)
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if filename and len(filename) > 3: # Meaningful filename
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indicators = [filename]
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return indicators
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def mark_event_with_intel(self, event: Any, misp_results: List[Dict], attr: str) -> None:
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"""Mark event with MISP intelligence."""
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try:
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# Check if event already marked
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event_id = event.source.get('_id', '')
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if event_id in self.marked_events:
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return
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self.marked_events.add(event_id)
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# Show organization info for cross-org awareness
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# Build comprehensive message
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if attr == "ip":
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msg = "MISP: Malicious IP detected - "
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msg = "MISP: Malicious IP detected"
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else:
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msg = "MISP: Known indicator - "
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msg = f"MISP: Known {attr.upper()} indicator"
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# Collect unique events and organizations
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# Collect event and organization info
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events_info = {}
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orgs_info = set()
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threat_levels = set()
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for misp_attr in result:
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for misp_attr in misp_results:
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event_info = misp_attr.get("Event", {})
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event_id = event_info.get("id", "")
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event_id_misp = event_info.get("id", "")
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event_desc = event_info.get("info", "Unknown")
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org_name = event_info.get("Orgc", {}).get("name", "Unknown Org")
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org_name = event_info.get("Orgc", {}).get("name", "Unknown")
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threat_level = event_info.get("threat_level_id", "")
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events_info[event_id] = f'"{event_desc}"'
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events_info[event_id_misp] = event_desc[:50] # Truncate long descriptions
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orgs_info.add(org_name)
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if threat_level:
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threat_levels.add(threat_level)
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# Build message with org info
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event_descriptions = list(events_info.values())[:2] # First 2 events
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msg += " | ".join(event_descriptions)
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# Enhanced message with threat context
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event_descriptions = list(events_info.values())[:2]
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if event_descriptions:
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msg += f" | Events: {' | '.join(event_descriptions)}"
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if len(result) > 2:
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msg += f" | +{len(result)-2} more"
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if len(misp_results) > 2:
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msg += f" | +{len(misp_results)-2} more indicators"
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# Add organization information
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# Organization information
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if len(orgs_info) > 1:
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msg += f" | Orgs: {', '.join(list(orgs_info)[:3])}"
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elif orgs_info:
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org_name = list(orgs_info)[0]
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if org_name != "Unknown Org":
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msg += f" | Org: {org_name}"
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msg += f" | Sources: {', '.join(list(orgs_info)[:3])}"
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elif orgs_info and list(orgs_info)[0] != "Unknown":
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msg += f" | Source: {list(orgs_info)[0]}"
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# Threat level context
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if threat_levels:
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highest_threat = min(threat_levels) # Lower number = higher threat
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threat_map = {"1": "HIGH", "2": "MEDIUM", "3": "LOW", "4": "UNDEFINED"}
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msg += f" | Threat: {threat_map.get(str(highest_threat), 'UNKNOWN')}"
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# Add tags and comment
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tags = [f"MISP-{attr}", "threat-intel"]
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if self.include_community and len(orgs_info) > 1:
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tags.append("cross-org-intel")
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event.add_comment(msg)
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event.add_tags([f"MISP-{attr}", "threat-intel", "cross-org-intel"])
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event.add_tags(tags)
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event.commit()
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self.stats['events_marked'] += 1
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except Exception as e:
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logger.error(f"Error marking event: {e}")
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logger.error(f"Error marking event {event_id}: {e}")
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self.stats['errors'] += 1
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def query_misp(self, query, attr, timesketch_attr):
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"""Extract indicators and query MISP."""
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events = self.event_stream(query_string=query, return_fields=[timesketch_attr, '_id'])
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query_list = []
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events_list = []
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processed = 0
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# Extract indicators from events
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for event in events:
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processed += 1
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if processed > 5000:
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break
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loc = event.source.get(timesketch_attr)
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if not loc:
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continue
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events_list.append(event)
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indicators = []
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# Extract based on attribute type
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if attr == "ip" and timesketch_attr == "message":
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ip_matches = self.ip_pattern.findall(str(loc))
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indicators = [ip for ip in ip_matches if self._is_valid_ip(ip)]
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elif attr == "ip" and timesketch_attr in ["source_ip", "src_ip", "client_ip"]:
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if self._is_valid_ip(str(loc)):
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indicators = [str(loc)]
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elif attr in ["md5", "sha1", "sha256"]:
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if self._is_valid_hash(str(loc), attr):
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indicators = [str(loc)]
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elif attr == "filename":
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filename = ntpath.basename(str(loc))
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if filename and len(filename) > 1:
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indicators = [filename]
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# Add valid indicators to query list
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for indicator in indicators:
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if indicator not in query_list:
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query_list.append(indicator)
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self.result_dict[f"{attr}:{indicator}"] = []
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logger.info(f"Extracted {len(query_list)} {attr} indicators from {processed} events")
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if not query_list:
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def process_events_chunk(self, events_chunk: List[Any], attr: str, timesketch_attr: str) -> None:
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"""Process a chunk of events efficiently."""
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# Extract all indicators from the chunk
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chunk_indicators = []
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event_to_indicators = {}
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for event in events_chunk:
|
||||
indicators = self.extract_indicators_from_event(event, attr, timesketch_attr)
|
||||
if indicators:
|
||||
event_id = event.source.get('_id', '')
|
||||
event_to_indicators[event_id] = (event, indicators)
|
||||
chunk_indicators.extend(indicators)
|
||||
|
||||
# Remove duplicates while preserving order
|
||||
unique_indicators = list(dict.fromkeys(chunk_indicators))
|
||||
new_indicators = [ind for ind in unique_indicators if ind not in self.processed_indicators]
|
||||
|
||||
if not new_indicators:
|
||||
return
|
||||
|
||||
# Query MISP for each indicator
|
||||
for indicator in query_list:
|
||||
result = self.query_misp_single(indicator, attr)
|
||||
if result:
|
||||
self.result_dict[f"{attr}:{indicator}"] = result
|
||||
# Log organization diversity
|
||||
orgs = set()
|
||||
for r in result:
|
||||
org = r.get("Event", {}).get("Orgc", {}).get("name", "Unknown")
|
||||
orgs.add(org)
|
||||
logger.info(f"MISP hit: {indicator} ({len(result)} indicators from {len(orgs)} orgs)")
|
||||
|
||||
# Mark matching events
|
||||
for event in events_list:
|
||||
loc = event.source.get(timesketch_attr)
|
||||
if not loc:
|
||||
continue
|
||||
|
||||
# Check if event already processed
|
||||
event_id = event.source.get('_id', '')
|
||||
|
||||
logger.info(f"Processing {len(new_indicators)} new indicators from chunk of {len(events_chunk)} events")
|
||||
|
||||
# Query MISP for new indicators
|
||||
misp_results = self.query_misp_batch(new_indicators, attr)
|
||||
|
||||
# Update processed indicators and result cache
|
||||
self.processed_indicators.update(new_indicators)
|
||||
for indicator, results in misp_results.items():
|
||||
if results:
|
||||
self.result_dict[f"{attr}:{indicator}"] = results
|
||||
|
||||
# Mark events that have matching indicators
|
||||
for event_id, (event, indicators) in event_to_indicators.items():
|
||||
if event_id in self.marked_events:
|
||||
continue
|
||||
|
||||
# Re-extract indicators from this event
|
||||
event_indicators = []
|
||||
|
||||
if attr == "ip" and timesketch_attr == "message":
|
||||
ip_matches = self.ip_pattern.findall(str(loc))
|
||||
event_indicators = [ip for ip in ip_matches if self._is_valid_ip(ip)]
|
||||
elif attr == "ip" and timesketch_attr in ["source_ip", "src_ip", "client_ip"]:
|
||||
if self._is_valid_ip(str(loc)):
|
||||
event_indicators = [str(loc)]
|
||||
elif attr in ["md5", "sha1", "sha256"]:
|
||||
if self._is_valid_hash(str(loc), attr):
|
||||
event_indicators = [str(loc)]
|
||||
elif attr == "filename":
|
||||
filename = ntpath.basename(str(loc))
|
||||
if filename:
|
||||
event_indicators = [filename]
|
||||
|
||||
# Check if any indicator has MISP match
|
||||
for indicator in event_indicators:
|
||||
|
||||
matching_results = []
|
||||
for indicator in indicators:
|
||||
key = f"{attr}:{indicator}"
|
||||
if key in self.result_dict and self.result_dict[key]:
|
||||
self.total_event_counter += 1
|
||||
self.mark_event(event, self.result_dict[key], attr)
|
||||
break # Only mark once per event
|
||||
if key in self.result_dict:
|
||||
matching_results.extend(self.result_dict[key])
|
||||
|
||||
if matching_results:
|
||||
self.mark_event_with_intel(event, matching_results, attr)
|
||||
|
||||
# Create view if we found matches
|
||||
if self.total_event_counter > 0:
|
||||
def query_misp(self, query: str, attr: str, timesketch_attr: str) -> None:
|
||||
"""Main processing function with chunked approach for large datasets."""
|
||||
logger.info(f"Starting MISP analysis for {attr} in {timesketch_attr}")
|
||||
logger.info(f"Community querying: {'enabled' if self.include_community else 'disabled'}")
|
||||
|
||||
# Process events in chunks to manage memory
|
||||
events_stream = self.event_stream(
|
||||
query_string=query,
|
||||
return_fields=[timesketch_attr, '_id', 'timestamp']
|
||||
)
|
||||
|
||||
current_chunk = []
|
||||
|
||||
try:
|
||||
for event in events_stream:
|
||||
current_chunk.append(event)
|
||||
self.stats['events_processed'] += 1
|
||||
|
||||
# Process chunk when it reaches the specified size
|
||||
if len(current_chunk) >= self.chunk_size:
|
||||
self.process_events_chunk(current_chunk, attr, timesketch_attr)
|
||||
current_chunk = []
|
||||
|
||||
# Progress logging
|
||||
if self.stats['events_processed'] % 10000 == 0:
|
||||
logger.info(f"Progress: {self.stats['events_processed']} events processed, "
|
||||
f"{self.stats['events_marked']} marked, "
|
||||
f"{self.stats['api_calls_made']} API calls made")
|
||||
|
||||
# Process remaining events in the last chunk
|
||||
if current_chunk:
|
||||
self.process_events_chunk(current_chunk, attr, timesketch_attr)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error during event processing: {e}")
|
||||
self.stats['errors'] += 1
|
||||
|
||||
# Create comprehensive view if we found matches
|
||||
if self.stats['events_marked'] > 0:
|
||||
view_name = f"MISP Threat Intel - {attr.upper()}"
|
||||
if self.include_community:
|
||||
view_name += " (Cross-Org)"
|
||||
|
||||
self.sketch.add_view(
|
||||
view_name="MISP Cross-Org Threat Intel",
|
||||
view_name=view_name,
|
||||
analyzer_name=self.NAME,
|
||||
query_string='tag:"MISP-*" OR tag:"threat-intel" OR tag:"cross-org-intel"',
|
||||
query_string=f'tag:"MISP-{attr}" OR tag:"threat-intel"',
|
||||
)
|
||||
|
||||
def run(self):
|
||||
"""Entry point for the analyzer."""
|
||||
def run(self) -> str:
|
||||
"""Entry point for the analyzer with comprehensive error handling."""
|
||||
if not self.misp_url or not self.misp_api_key:
|
||||
return "No MISP configuration found"
|
||||
return "Error: No MISP configuration found"
|
||||
|
||||
start_time = time.time()
|
||||
|
||||
try:
|
||||
logger.info(f"Starting MISP analyzer with config: "
|
||||
f"batch_size={self.batch_size}, "
|
||||
f"api_batch_size={self.api_batch_size}, "
|
||||
f"chunk_size={self.chunk_size}, "
|
||||
f"include_community={self.include_community}")
|
||||
|
||||
self.query_misp(self._query_string, self._attr, self._timesketch_attr)
|
||||
return f"[{self._timesketch_attr}] MISP Match: {self.total_event_counter}"
|
||||
|
||||
elapsed_time = time.time() - start_time
|
||||
|
||||
# Comprehensive results summary
|
||||
result_msg = (f"[{self._timesketch_attr}] MISP Analysis Complete: "
|
||||
f"{self.stats['events_marked']}/{self.stats['events_processed']} events marked | "
|
||||
f"{self.stats['api_calls_made']} API calls | "
|
||||
f"{len(self.processed_indicators)} indicators processed | "
|
||||
f"{elapsed_time:.1f}s")
|
||||
|
||||
if self.stats['errors'] > 0:
|
||||
result_msg += f" | {self.stats['errors']} errors"
|
||||
|
||||
logger.info(result_msg)
|
||||
return result_msg
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"MISP analyzer error: {e}")
|
||||
logger.error(f"MISP analyzer critical error: {e}")
|
||||
return f"[{self._timesketch_attr}] MISP Error: {str(e)}"
|
||||
|
||||
|
||||
|
||||
Reference in New Issue
Block a user