Kitos
52d230628d
- Add intel_service.py: RSS feed scanner for threat intelligence Searches CISA, NIST NVD, SANS ISC, BleepingComputer, The Hacker News, Krebs on Security for mentions of MITRE technique IDs and names - New intel items stored in intel_items table with URL deduplication - Techniques with new intel flagged with review_required=True - Add POST /system/run-intel-scan endpoint (admin only) - Register weekly intel scan job in APScheduler (every 7 days) - Audit log records each scan execution with summary stats - Update README with new endpoint and project structure
255 lines
7.8 KiB
Python
255 lines
7.8 KiB
Python
"""Automated threat-intelligence scan service.
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Searches public security RSS feeds for mentions of MITRE ATT&CK technique
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IDs and names. New findings are stored as :class:`IntelItem` records and
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the related technique is flagged for review.
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This is an **MVP** implementation — it queries a small set of well-known
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RSS feeds and parses them with the standard-library :mod:`xml.etree`
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parser. No LLMs or paid APIs are used.
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"""
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import logging
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import re
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import xml.etree.ElementTree as ET
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from datetime import datetime
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import requests as _requests
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from sqlalchemy.orm import Session
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from app.models.intel import IntelItem
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from app.models.technique import Technique
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from app.services.audit_service import log_action
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logger = logging.getLogger(__name__)
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# ---------------------------------------------------------------------------
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# Public security RSS feeds
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# ---------------------------------------------------------------------------
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RSS_FEEDS: list[dict[str, str]] = [
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{
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"name": "CISA Alerts",
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"url": "https://www.cisa.gov/cybersecurity-advisories/all.xml",
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},
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{
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"name": "NIST NVD CVE",
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"url": "https://nvd.nist.gov/feeds/xml/cve/misc/nvd-rss.xml",
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},
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{
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"name": "SANS ISC",
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"url": "https://isc.sans.edu/rssfeed.xml",
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},
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{
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"name": "BleepingComputer",
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"url": "https://www.bleepingcomputer.com/feed/",
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},
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{
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"name": "The Hacker News",
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"url": "https://feeds.feedburner.com/TheHackersNews",
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},
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{
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"name": "Krebs on Security",
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"url": "https://krebsonsecurity.com/feed/",
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},
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]
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# Timeout for each feed request (seconds)
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_FEED_TIMEOUT = 15
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# Maximum number of techniques to scan (to keep MVP fast)
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_MAX_TECHNIQUES = 50
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# ---------------------------------------------------------------------------
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# Internal helpers
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# ---------------------------------------------------------------------------
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def _fetch_feed(url: str) -> list[dict[str, str]]:
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"""Download and parse an RSS/Atom feed, returning a list of entries.
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Each entry is a dict with keys ``title``, ``link``, and ``description``.
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Returns an empty list on any error so the scan can continue.
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"""
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try:
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resp = _requests.get(url, timeout=_FEED_TIMEOUT, headers={
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"User-Agent": "AegisPlatform/1.0 IntelScan",
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})
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resp.raise_for_status()
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except Exception as exc:
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logger.warning("Failed to fetch feed %s: %s", url, exc)
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return []
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try:
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root = ET.fromstring(resp.content)
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except ET.ParseError as exc:
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logger.warning("Failed to parse feed %s: %s", url, exc)
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return []
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entries: list[dict[str, str]] = []
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# RSS 2.0 format: <channel><item>...
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for item in root.iter("item"):
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title_el = item.find("title")
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link_el = item.find("link")
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desc_el = item.find("description")
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entries.append({
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"title": title_el.text.strip() if title_el is not None and title_el.text else "",
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"link": link_el.text.strip() if link_el is not None and link_el.text else "",
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"description": desc_el.text.strip() if desc_el is not None and desc_el.text else "",
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})
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# Atom format: <feed><entry>...
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ns = {"atom": "http://www.w3.org/2005/Atom"}
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for entry in root.iter("{http://www.w3.org/2005/Atom}entry"):
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title_el = entry.find("atom:title", ns)
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link_el = entry.find("atom:link", ns)
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summary_el = entry.find("atom:summary", ns)
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link_href = ""
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if link_el is not None:
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link_href = link_el.get("href", "")
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entries.append({
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"title": title_el.text.strip() if title_el is not None and title_el.text else "",
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"link": link_href.strip(),
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"description": summary_el.text.strip() if summary_el is not None and summary_el.text else "",
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})
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return entries
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def _build_patterns(technique: Technique) -> list[re.Pattern]:
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"""Build regex patterns to search feed content for a given technique."""
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patterns: list[re.Pattern] = []
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mitre_id = re.escape(technique.mitre_id)
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patterns.append(re.compile(mitre_id, re.IGNORECASE))
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# Technique name — match if the full name appears
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if technique.name and len(technique.name) > 4:
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name_escaped = re.escape(technique.name)
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patterns.append(re.compile(name_escaped, re.IGNORECASE))
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return patterns
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def _entry_matches(entry: dict[str, str], patterns: list[re.Pattern]) -> bool:
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"""Return True if any pattern matches the entry's title or description."""
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text = f"{entry.get('title', '')} {entry.get('description', '')}"
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return any(p.search(text) for p in patterns)
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# ---------------------------------------------------------------------------
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# Public API
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# ---------------------------------------------------------------------------
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def scan_intel(db: Session) -> dict:
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"""Run the intel scan across RSS feeds for known techniques.
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Parameters
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----------
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db : Session
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Active SQLAlchemy database session.
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Returns
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-------
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dict
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Summary with keys ``new_items``, ``duplicates_skipped``,
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``techniques_flagged``, ``feeds_checked``.
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"""
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logger.info("Intel scan starting...")
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# 1. Load techniques (limit for MVP speed)
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techniques = (
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db.query(Technique)
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.order_by(Technique.mitre_id)
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.limit(_MAX_TECHNIQUES)
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.all()
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)
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logger.info("Scanning %d techniques against %d feeds", len(techniques), len(RSS_FEEDS))
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# 2. Pre-load all existing intel URLs for dedup
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existing_urls: set[str] = {
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row[0] for row in db.query(IntelItem.url).all()
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}
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# 3. Fetch all feeds once
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all_entries: list[tuple[str, dict[str, str]]] = [] # (feed_name, entry)
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feeds_ok = 0
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for feed in RSS_FEEDS:
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entries = _fetch_feed(feed["url"])
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if entries:
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feeds_ok += 1
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for entry in entries:
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all_entries.append((feed["name"], entry))
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logger.info("Fetched %d entries from %d/%d feeds", len(all_entries), feeds_ok, len(RSS_FEEDS))
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# 4. Match entries to techniques
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new_items = 0
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duplicates_skipped = 0
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techniques_flagged: set[str] = set()
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for technique in techniques:
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patterns = _build_patterns(technique)
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for feed_name, entry in all_entries:
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if not _entry_matches(entry, patterns):
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continue
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url = entry.get("link", "").strip()
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if not url:
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continue
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# Dedup
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if url in existing_urls:
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duplicates_skipped += 1
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continue
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# Create IntelItem
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intel_item = IntelItem(
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technique_id=technique.id,
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url=url,
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title=entry.get("title", "")[:500],
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source=feed_name,
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detected_at=datetime.utcnow(),
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reviewed=False,
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)
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db.add(intel_item)
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existing_urls.add(url)
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new_items += 1
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# Flag technique for review
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if not technique.review_required:
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technique.review_required = True
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techniques_flagged.add(technique.mitre_id)
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# 5. Single commit
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db.commit()
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summary = {
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"new_items": new_items,
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"duplicates_skipped": duplicates_skipped,
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"techniques_flagged": len(techniques_flagged),
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"feeds_checked": feeds_ok,
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}
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logger.info(
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"Intel scan complete — new=%d, duplicates_skipped=%d, "
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"techniques_flagged=%d, feeds_checked=%d",
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new_items, duplicates_skipped, len(techniques_flagged), feeds_ok,
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)
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# 6. Audit log
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log_action(
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db,
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user_id=None,
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action="intel_scan",
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entity_type="intel_item",
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entity_id=None,
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details=summary,
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)
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return summary
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