Building Threat Intelligence Feed Integration

Building Threat Intelligence Feed Integration

When to Use

Use this skill when:

• SOC teams need automated ingestion of threat intelligence feeds into SIEM platforms
• Multiple TI sources require normalization into a common format (STIX 2.1)
• Detection systems need real-time IOC matching against network and endpoint telemetry
• TI feed quality assessment and deduplication processes need to be established

Do not use for manual IOC lookup — use dedicated enrichment tools (VirusTotal, AbuseIPDB) for ad-hoc queries.

Common Misconfigurations & Verification

• STIX pattern parsing breaks on split("'")[1]: the push-to-SIEM code extracts the IOC with indicator.pattern.split("'")[1], which silently grabs the wrong token for hash patterns ([file:hashes.'SHA-256' = '...'] has an extra quoted segment) or any pattern with quoting variation. Verify each pattern_type=stix indicator round-trips to the value you expect before bulk-pushing, or you poison the feed with SHA-256 literals instead of hashes.
• type field forces wrong attribute: the MISP push hardcodes ip-dst if "ipv4" in pattern else domain, so URLs and hashes get mislabeled as domains and never match. Map each STIX object type explicitly.
• No expiration = false positives forever: without enforcing the IOC TTL policy (IP 30d, domain 90d, hash 1y), expired/sinkholed IPs and CDN ranges keep matching. The Output Format note "CDN IPs removed from feed" is the tell — pre-filter known-good ranges (cloud egress, CDN, your own infra) before ingest, not after analysts chase the FP.
• Dedup hash hides multi-source confidence: sha256("{type}:{value}") dedup drops the second source, so you lose corroboration scoring — keep multi-source attribution rather than first-wins.
• Verification: push a controlled canary IOC end-to-end and confirm it lands in Splunk ip_intel/MISP with correct type and weight; check the feed-health match-rate search (Step 6) actually joins — a feed showing 0 matches over weeks usually means a field/format mismatch, not a quiet network.

Prerequisites

• MISP instance or Threat Intelligence Platform (TIP) for feed aggregation
• STIX/TAXII client library (taxii2-client, stix2 Python packages)
• SIEM platform (Splunk ES, Elastic Security, or Sentinel) with TI framework configured
• API keys for commercial and open-source feeds (AlienVault OTX, Abuse.ch, CISA AIS)
• Python 3.8+ for feed processing automation

Workflow

Step 1: Identify and Catalog Intelligence Sources

Map available feeds by type, format, and update frequency:

Step 2: Ingest STIX/TAXII Feeds

Connect to a TAXII 2.1 server and download indicators:

from taxii2client.v21 import Server, Collection
from stix2 import parse

# Connect to TAXII server (example: CISA AIS)
server = Server(
    "https://taxii.cisa.gov/taxii2/",
    user="your_username",
    password="your_password"
)

# List available collections
for api_root in server.api_roots:
    print(f"API Root: {api_root.title}")
    for collection in api_root.collections:
        print(f"  Collection: {collection.title} (ID: {collection.id})")

# Fetch indicators from a collection
collection = Collection(
    "https://taxii.cisa.gov/taxii2/collections/COLLECTION_ID/",
    user="your_username",
    password="your_password"
)

# Get indicators added in last 24 hours
from datetime import datetime, timedelta
added_after = (datetime.utcnow() - timedelta(days=1)).strftime("%Y-%m-%dT%H:%M:%S.000Z")

response = collection.get_objects(added_after=added_after, type=["indicator"])
for obj in response.get("objects", []):
    indicator = parse(obj)
    print(f"Type: {indicator.type}")
    print(f"Pattern: {indicator.pattern}")
    print(f"Valid Until: {indicator.valid_until}")
    print(f"Confidence: {indicator.confidence}")
    print("---")

Step 3: Ingest Open-Source Feeds

Abuse.ch URLhaus Feed:

import requests
import csv
from io import StringIO

# Download URLhaus recent URLs
response = requests.get("https://urlhaus.abuse.ch/downloads/csv_recent/")
reader = csv.reader(StringIO(response.text), delimiter=',')

indicators = []
for row in reader:
    if row[0].startswith("#"):
        continue
    indicators.append({
        "id": row[0],
        "dateadded": row[1],
        "url": row[2],
        "url_status": row[3],
        "threat": row[5],
        "tags": row[6]
    })

print(f"Ingested {len(indicators)} URLs from URLhaus")

# Filter for active threats only
active = [i for i in indicators if i["url_status"] == "online"]
print(f"Active threats: {len(active)}")

AlienVault OTX Pulse Feed:

from OTXv2 import OTXv2, IndicatorTypes

otx = OTXv2("YOUR_OTX_API_KEY")

# Get subscribed pulses (last 24 hours)
pulses = otx.getall(modified_since="2024-03-14T00:00:00")

for pulse in pulses:
    print(f"Pulse: {pulse['name']}")
    print(f"Tags: {pulse['tags']}")
    for indicator in pulse["indicators"]:
        print(f"  IOC: {indicator['indicator']} ({indicator['type']})")

Abuse.ch Feodo Tracker (C2 IPs):

response = requests.get("https://feodotracker.abuse.ch/downloads/ipblocklist_recommended.json")
c2_data = response.json()

for entry in c2_data:
    print(f"IP: {entry['ip_address']}:{entry['port']}")
    print(f"Malware: {entry['malware']}")
    print(f"First Seen: {entry['first_seen']}")
    print(f"Last Online: {entry['last_online']}")

Step 4: Normalize and Deduplicate

Convert all feeds to STIX 2.1 format for standardization:

from stix2 import Indicator, Bundle
import hashlib

def create_stix_indicator(ioc_value, ioc_type, source, confidence=50):
    """Convert raw IOC to STIX 2.1 indicator"""
    pattern_map = {
        "ipv4": f"[ipv4-addr:value = '{ioc_value}']",
        "domain": f"[domain-name:value = '{ioc_value}']",
        "url": f"[url:value = '{ioc_value}']",
        "sha256": f"[file:hashes.'SHA-256' = '{ioc_value}']",
        "md5": f"[file:hashes.MD5 = '{ioc_value}']",
    }

    return Indicator(
        name=f"{ioc_type}: {ioc_value}",
        pattern=pattern_map[ioc_type],
        pattern_type="stix",
        valid_from="2024-03-15T00:00:00Z",
        confidence=confidence,
        labels=[source],
        custom_properties={"x_source_feed": source}
    )

# Deduplicate across sources
seen_iocs = set()
unique_indicators = []

for ioc in all_collected_iocs:
    ioc_hash = hashlib.sha256(f"{ioc['type']}:{ioc['value']}".encode()).hexdigest()
    if ioc_hash not in seen_iocs:
        seen_iocs.add(ioc_hash)
        unique_indicators.append(
            create_stix_indicator(ioc["value"], ioc["type"], ioc["source"])
        )

bundle = Bundle(objects=unique_indicators)
print(f"Unique indicators: {len(unique_indicators)}")

Step 5: Push to SIEM Threat Intelligence Framework

Push to Splunk ES Threat Intelligence:

import requests

splunk_url = "https://splunk.company.com:8089"
headers = {"Authorization": f"Bearer {splunk_token}"}

for indicator in unique_indicators:
    # Extract IOC value from STIX pattern
    ioc_value = indicator.pattern.split("'")[1]

    # Upload to Splunk ES threat intel collection
    data = {
        "ip": ioc_value,
        "description": indicator.name,
        "weight": indicator.confidence // 10,
        "threat_key": indicator.id,
        "source_feed": indicator.get("x_source_feed", "unknown")
    }

    requests.post(
        f"{splunk_url}/services/data/threat_intel/item/ip_intel",
        headers=headers, data=data,
        verify=not os.environ.get("SKIP_TLS_VERIFY", "").lower() == "true",  # Set SKIP_TLS_VERIFY=true for self-signed certs in lab environments
    )

Push to MISP for centralized management:

from pymisp import PyMISP, MISPEvent, MISPAttribute

misp = PyMISP("https://misp.company.com", "YOUR_MISP_API_KEY")

# Create event for feed batch
event = MISPEvent()
event.info = f"TI Feed Import - {datetime.now().strftime('%Y-%m-%d')}"
event.threat_level_id = 2  # Medium
event.analysis = 2  # Completed

# Add indicators as attributes
for ioc in unique_indicators:
    attr = MISPAttribute()
    attr.type = "ip-dst" if "ipv4" in ioc.pattern else "domain"
    attr.value = ioc.pattern.split("'")[1]
    attr.to_ids = True
    attr.comment = f"Source: {ioc.get('x_source_feed', 'mixed')}"
    event.add_attribute(**attr)

result = misp.add_event(event)
print(f"MISP Event created: {result['Event']['id']}")

Step 6: Monitor Feed Health and Quality

Track feed effectiveness metrics:

index=threat_intel sourcetype="threat_intel_manager"
| stats count AS total_iocs,
        dc(threat_key) AS unique_iocs,
        dc(source_feed) AS feed_count
  by source_feed
| join source_feed [
    search index=notable source="Threat Intelligence"
    | stats count AS matches by source_feed
  ]
| eval match_rate = round(matches / unique_iocs * 100, 2)
| sort - match_rate
| table source_feed, unique_iocs, matches, match_rate

Key Concepts

Tools & Systems

• MISP: Open-source threat intelligence platform for feed aggregation, correlation, and sharing
• AlienVault OTX: Free threat intelligence sharing platform with community pulse feeds
• Abuse.ch: Suite of free threat feeds (URLhaus, MalwareBazaar, Feodo Tracker, ThreatFox)
• OpenCTI: Open-source cyber threat intelligence platform supporting STIX 2.1 native storage
• TAXII2 Client: Python library for connecting to STIX/TAXII 2.1 servers for automated indicator retrieval

Common Scenarios

• New Feed Onboarding: Evaluate feed quality, map fields to STIX, configure automated ingestion pipeline
• Multi-SIEM Distribution: Push normalized IOCs from MISP to Splunk, Elastic, and Sentinel simultaneously
• False Positive Reduction: Score IOCs by source count and age, expire stale indicators automatically
• Feed Quality Audit: Compare detection match rates across feeds to identify highest-value sources
• Incident IOC Sharing: Package investigation IOCs as STIX bundle and share with ISACs via TAXII

Output Format

THREAT INTEL FEED STATUS — Daily Report
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Date:         2024-03-15
Total IOCs:   45,892 active indicators

Feed Health:
  Feed                  IOCs    Matches  Match Rate  Status
  Abuse.ch URLhaus      12,340  47       0.38%       HEALTHY
  AlienVault OTX        18,567  23       0.12%       HEALTHY
  Abuse.ch Feodo        1,203   12       1.00%       HEALTHY
  CISA AIS              8,945   8        0.09%       HEALTHY
  CrowdStrike Intel     4,837   31       0.64%       HEALTHY

Actions Today:
  New IOCs ingested:    1,247
  IOCs expired:         892
  Duplicates removed:   156
  SIEM matches:         121 notable events generated
  False positives:      3 (CDN IPs removed from feed)