Building Threat Intelligence Platform
Overview
Building a Threat Intelligence Platform (TIP) involves deploying and integrating multiple CTI tools into a unified system for collecting, analyzing, enriching, and disseminating threat intelligence. This skill covers designing TIP architecture using open-source tools (MISP, OpenCTI, TheHive, Cortex), configuring feed ingestion pipelines, establishing enrichment workflows, implementing STIX/TAXII interoperability, and building analyst dashboards for CTI operations.
When to Use
Trigger phrases:
"building threat intelligence platform"
"Building a Threat Intelligence Platform (TIP) involves deploying and integrating"
When deploying or configuring building threat intelligence platform capabilities in your environment
When establishing security controls aligned to compliance requirements
When building or improving security architecture for this domain
When conducting security assessments that require this implementation
Prerequisites
- Docker and Docker Compose for deploying platform components
- Python 3.9+ with
pymisp,pycti,thehive4pylibraries - Elasticsearch/OpenSearch cluster for data storage
- Redis and RabbitMQ for message queuing
- Understanding of STIX 2.1 data model and TAXII 2.1 transport
- API keys for enrichment services (VirusTotal, Shodan, AbuseIPDB)
Key Concepts
This section covers key concepts for building threat intelligence platform.
- Ensure all prerequisites are met before proceeding
- Follow the documented workflow steps in sequence
- Record results and any anomalies encountered during this phase
TIP Architecture Components
- Collection Layer: Feed ingestion from OSINT, commercial, and internal sources
- Storage Layer: Elasticsearch/OpenSearch for indexed CTI data with STIX 2.1 schema
- Analysis Layer: OpenCTI for knowledge graph analysis and MISP for IOC correlation
- Enrichment Layer: Cortex analyzers for automated IOC enrichment
- Response Layer: TheHive for case management and incident response integration
- Sharing Layer: TAXII server for outbound intelligence sharing
Platform Integration Points
- MISP <-> OpenCTI: Bidirectional sync via OpenCTI MISP connector
- OpenCTI <-> TheHive: Alert/case creation from high-confidence indicators
- TheHive <-> Cortex: Automated analysis and enrichment of case observables
- All <-> SIEM: Real-time IOC push to Splunk/Elastic via API or Kafka
Workflow
- Scope the task — define objectives, boundaries, and success criteria
- Gather information — collect all necessary data and context before proceeding
- Execute the core workflow — follow the domain-specific steps methodically
- Validate results — verify outputs against expected outcomes or baselines
- Document findings — record results, anomalies, and recommendations
Step 1: Deploy Platform with Docker Compose
version: '3.8'
services:
# --- Storage Layer ---
elasticsearch:
image: docker.elastic.co/elasticsearch/elasticsearch:8.12.0
environment:
- discovery.type=single-node
- xpack.security.enabled=false
- "ES_JAVA_OPTS=-Xms2g -Xmx2g"
ports:
- "9200:9200"
volumes:
- es-data:/usr/share/elasticsearch/data
redis:
image: redis:7
ports:
- "6379:6379"
rabbitmq:
image: rabbitmq:3-management
ports:
- "5672:5672"
- "15672:15672"
minio:
image: minio/minio
command: server /data --console-address ":9001"
ports:
- "9000:9000"
- "9001:9001"
# --- MISP ---
misp:
image: ghcr.io/misp/misp-docker/misp-core:latest
ports:
- "8443:443"
environment:
- MISP_ADMIN_EMAIL=admin@tip.local
- MISP_BASEURL=https://localhost:8443
volumes:
- misp-data:/var/www/MISP/app/files
# --- OpenCTI ---
opencti:
image: opencti/platform:6.4.4
environment:
- APP__PORT=8080
- APP__ADMIN__EMAIL=admin@tip.local
- APP__ADMIN__PASSWORD=TIPAdminPassword
- APP__ADMIN__TOKEN=tip-opencti-token-uuid
- ELASTICSEARCH__URL=http://elasticsearch:9200
- MINIO__ENDPOINT=minio
- RABBITMQ__HOSTNAME=rabbitmq
- REDIS__HOSTNAME=redis
ports:
- "8080:8080"
depends_on:
- elasticsearch
- redis
- rabbitmq
- minio
# --- TheHive ---
thehive:
image: strangebee/thehive:5.3
environment:
- TH_CORTEX_URL=http://cortex:9001
ports:
- "9000:9000"
depends_on:
- elasticsearch
# --- Cortex ---
cortex:
image: thehiveproject/cortex:3.1.8
ports:
- "9001:9001"
depends_on:
- elasticsearch
volumes:
es-data:
misp-data:
Step 2: Configure Feed Ingestion Pipeline
from pymisp import PyMISP
from pycti import OpenCTIApiClient
import json
class TIPFeedManager:
"""Manage threat intelligence feed ingestion across platform components."""
def __init__(self, misp_url, misp_key, opencti_url, opencti_token):
self.misp = PyMISP(misp_url, misp_key, ssl=False)
self.opencti = OpenCTIApiClient(opencti_url, opencti_token)
def configure_osint_feeds(self):
"""Enable default OSINT feeds in MISP."""
osint_feeds = [
{"name": "CIRCL OSINT", "id": 1},
{"name": "Botvrij.eu", "id": 2},
{"name": "abuse.ch URLhaus", "id": 5},
{"name": "abuse.ch Feodo Tracker", "id": 6},
]
for feed in osint_feeds:
try:
self.misp.enable_feed(feed["id"])
self.misp.fetch_feed(feed["id"])
print(f"[+] Enabled feed: {feed['name']}")
except Exception as e:
print(f"[-] Failed: {feed['name']}: {e}")
def configure_opencti_connectors(self):
"""List and verify OpenCTI connector status."""
connectors = self.opencti.connector.list()
for conn in connectors:
print(
f" Connector: {conn['name']} - "
f"Active: {conn['active']} - "
f"Type: {conn['connector_type']}"
)
def sync_misp_to_opencti(self):
"""Verify MISP-OpenCTI sync is operational."""
# OpenCTI MISP connector handles this automatically
# Check connector status
connectors = self.opencti.connector.list()
misp_connector = [
c for c in connectors if "misp" in c["name"].lower()
]
if misp_connector:
print(f"[+] MISP connector active: {misp_connector[0]['active']}")
else:
print("[-] MISP connector not found - configure in Docker Compose")
Step 3: Build Enrichment Pipeline with Cortex
import requests
class CortexEnrichment:
"""Integrate Cortex analyzers for automated enrichment."""
def __init__(self, cortex_url, cortex_key):
self.url = cortex_url
self.headers = {"Authorization": f"Bearer {cortex_key}"}
def list_analyzers(self):
"""List available Cortex analyzers."""
resp = requests.get(
f"{self.url}/api/analyzer",
headers=self.headers,
timeout=30,
)
if resp.status_code == 200:
analyzers = resp.json()
for a in analyzers:
print(f" {a['name']}: {a.get('description', '')[:60]}")
return analyzers
return []
def analyze_observable(self, observable_type, observable_value, analyzer_id):
"""Submit an observable for analysis."""
job = {
"data": observable_value,
"dataType": observable_type,
"tlp": 2,
"message": "TIP automated enrichment",
}
resp = requests.post(
f"{self.url}/api/analyzer/{analyzer_id}/run",
json=job,
headers=self.headers,
timeout=30,
)
if resp.status_code == 200:
return resp.json()
return None
def get_job_report(self, job_id):
"""Get the report for a completed analysis job."""
resp = requests.get(
f"{self.url}/api/job/{job_id}/report",
headers=self.headers,
timeout=60,
)
if resp.status_code == 200:
return resp.json()
return None
Step 4: Implement Analyst Dashboard Metrics
class TIPMetrics:
"""Collect platform metrics for analyst dashboards."""
def __init__(self, misp, opencti):
self.misp = misp
self.opencti = opencti
def get_platform_stats(self):
"""Collect statistics across all platform components."""
stats = {}
# MISP stats
misp_stats = self.misp.get_server_statistics()
stats["misp"] = {
"total_events": misp_stats.get("event_count", 0),
"total_attributes": misp_stats.get("attribute_count", 0),
"active_feeds": len([
f for f in self.misp.feeds()
if f.get("Feed", {}).get("enabled")
]),
}
# OpenCTI stats via GraphQL
stats["opencti"] = {
"total_indicators": self.opencti.indicator.list(
first=0, withPagination=True
).get("pagination", {}).get("globalCount", 0),
"total_reports": self.opencti.report.list(
first=0, withPagination=True
).get("pagination", {}).get("globalCount", 0),
}
return stats
Validation Criteria
- All platform components (MISP, OpenCTI, TheHive, Cortex) deployed and accessible
- MISP-OpenCTI bidirectional sync operational
- At least 3 OSINT feeds ingesting data
- Cortex analyzers configured and returning enrichment results
- Platform metrics dashboard showing real-time statistics
- STIX/TAXII export functional for intelligence sharing
When NOT to Use
- You need to test what you built (use performing-* skills)
- Task is about configuring existing systems (use configuring-* skills)
- You need to analyze the output (use analyzing-* skills)
- Task is about implementing vendor solutions (use implementing-* skills)
- You don't have infrastructure access
- Task requires compliance validation (use auditing-* skills)
Red Flags
- Performing actions without explicit written authorization from the asset owner
- Testing against production systems without a defined scope and rules of engagement
- Acting on threat intelligence without validating source reliability
- Sharing classified or sensitive indicators without proper handling procedures
- Alerting threat actors to detection capabilities through visible response actions
Verification
- All steps executed successfully against a test environment before production use
- Output documented with screenshots or logs demonstrating expected behavior
- Results validated against known-good baselines or reference implementations
- Documentation complete enough for another analyst to reproduce findings
References
Process
- Analyze the task requirements
- Apply domain expertise
- Verify output quality
Anti-Rationalization Table
| Rationalization | Reality |
|---|---|
| "We are too small to be targeted" | Automated attacks target everyone. Size does not matter. |
| "Security slows us down" | A breach slows you down 100x more. Build security in from the start. |
| "We will fix it after launch" | Vulnerabilities in production are exploited within hours. Fix before deploy. |