Implementing STIX/TAXII Feed Integration
Overview
STIX (Structured Threat Information eXpression) and TAXII (Trusted Automated eXchange of Intelligence Information) are OASIS open standards for representing and transporting cyber threat intelligence. This guide covers implementing a STIX/TAXII 2.1 feed consumer and producer using Python, configuring TAXII server discovery, collection management, polling for new intelligence, parsing STIX 2.1 objects, and integrating feeds into SIEM and TIP platforms.
Prerequisites
- Python 3.9+ with
taxii2-client,stix2,cti-taxii-clientlibraries - Understanding of STIX 2.1 data model (SDOs, SCOs, SROs)
- Understanding of TAXII 2.1 protocol (discovery, API roots, collections)
- Network access to TAXII servers (MITRE ATT&CK TAXII, Anomali STAXX)
- Optional: medallion for running a local TAXII 2.1 server
Key Concepts
TAXII 2.1 Architecture
TAXII defines a RESTful API with three service types:
- Discovery: Returns information about available API roots
- API Root: Contains collections and serves as the main interaction point
- Collection: A logical grouping of STIX objects accessible via GET/POST
STIX 2.1 Object Model
STIX objects are categorized as:
- SDOs (STIX Domain Objects): Indicator, Malware, Threat Actor, Campaign, Attack Pattern, Tool, Infrastructure, Vulnerability, Identity, Location, Note, Opinion, Report, Grouping
- SCOs (STIX Cyber Observables): IPv4-Addr, Domain-Name, URL, File, Email-Addr, Process, Network-Traffic, Artifact
- SROs (STIX Relationship Objects): Relationship, Sighting
- Meta Objects: Marking Definition (TLP), Language Content, Extension Definition
STIX Bundle
A Bundle is a collection of STIX objects transmitted together. Bundles have a unique ID and contain an array of objects. TAXII collections serve bundles in response to GET requests.
Practical Steps
Step 1: TAXII Server Discovery
from taxii2client.v21 import Server, Collection, as_pages
# Connect to MITRE ATT&CK TAXII server
server = Server("https://cti-taxii.mitre.org/taxii2/", user="", password="")
print(f"Title: {server.title}")
print(f"Description: {server.description}")
# List API roots
for api_root in server.api_roots:
print(f"\nAPI Root: {api_root.title}")
print(f" URL: {api_root.url}")
# List collections
for collection in api_root.collections:
print(f" Collection: {collection.title} (ID: {collection.id})")
print(f" Can Read: {collection.can_read}")
print(f" Can Write: {collection.can_write}")
Step 2: Fetch STIX Objects from Collection
from taxii2client.v21 import Collection, as_pages
import json
# Connect to Enterprise ATT&CK collection
ENTERPRISE_ATTACK_ID = "95ecc380-afe9-11e4-9b6c-751b66dd541e"
collection = Collection(
f"https://cti-taxii.mitre.org/stix/collections/{ENTERPRISE_ATTACK_ID}/",
user="",
password="",
)
print(f"Collection: {collection.title}")
# Fetch all objects (paginated)
all_objects = []
for envelope in as_pages(collection.get_objects, per_request=50):
objects = envelope.get("objects", [])
all_objects.extend(objects)
print(f" Fetched {len(objects)} objects (total: {len(all_objects)})")
print(f"\nTotal objects retrieved: {len(all_objects)}")
# Categorize by type
type_counts = {}
for obj in all_objects:
obj_type = obj.get("type", "unknown")
type_counts[obj_type] = type_counts.get(obj_type, 0) + 1
for obj_type, count in sorted(type_counts.items()):
print(f" {obj_type}: {count}")
Step 3: Parse STIX 2.1 Objects with stix2 Library
from stix2 import parse, Filter, MemoryStore
# Load objects into a MemoryStore for querying
store = MemoryStore(stix_data=all_objects)
# Query for all indicators
indicators = store.query([Filter("type", "=", "indicator")])
print(f"Indicators: {len(indicators)}")
for ind in indicators[:5]:
print(f" {ind.name}: {ind.pattern}")
# Query for malware
malware_list = store.query([Filter("type", "=", "malware")])
print(f"\nMalware families: {len(malware_list)}")
# Query for threat actors
actors = store.query([Filter("type", "=", "intrusion-set")])
print(f"Threat actors: {len(actors)}")
# Find relationships for a specific object
def get_related(store, source_id):
relationships = store.query([
Filter("type", "=", "relationship"),
Filter("source_ref", "=", source_id),
])
return relationships
# Example: Get all techniques used by APT28
apt28 = store.query([
Filter("type", "=", "intrusion-set"),
Filter("name", "=", "APT28"),
])
if apt28:
rels = get_related(store, apt28[0].id)
for rel in rels:
target = store.get(rel.target_ref)
if target:
print(f" {rel.relationship_type} -> {target.name} ({target.type})")
Step 4: Implement Custom TAXII Consumer
from taxii2client.v21 import Collection, as_pages
from stix2 import parse, Bundle
from datetime import datetime, timedelta
import json
class TAXIIConsumer:
"""Consume STIX/TAXII 2.1 feeds and extract IOCs."""
def __init__(self, collection_url, user="", password=""):
self.collection = Collection(collection_url, user=user, password=password)
self.last_poll = None
def poll_new_objects(self, added_after=None):
"""Poll for objects added after a specific timestamp."""
if added_after is None:
added_after = (
self.last_poll or
(datetime.utcnow() - timedelta(days=1)).strftime(
"%Y-%m-%dT%H:%M:%S.000Z"
)
)
all_objects = []
kwargs = {"added_after": added_after}
for envelope in as_pages(
self.collection.get_objects, per_request=100, **kwargs
):
objects = envelope.get("objects", [])
all_objects.extend(objects)
self.last_poll = datetime.utcnow().strftime("%Y-%m-%dT%H:%M:%S.000Z")
return all_objects
def extract_indicators(self, objects):
"""Extract actionable indicators from STIX objects."""
indicators = []
for obj in objects:
if obj.get("type") == "indicator":
indicators.append({
"id": obj.get("id"),
"name": obj.get("name", ""),
"pattern": obj.get("pattern", ""),
"pattern_type": obj.get("pattern_type", ""),
"valid_from": obj.get("valid_from", ""),
"valid_until": obj.get("valid_until", ""),
"indicator_types": obj.get("indicator_types", []),
"confidence": obj.get("confidence", 0),
"labels": obj.get("labels", []),
})
return indicators
def extract_observables(self, objects):
"""Extract STIX Cyber Observables."""
observables = []
observable_types = {
"ipv4-addr", "ipv6-addr", "domain-name", "url",
"file", "email-addr", "network-traffic",
}
for obj in objects:
if obj.get("type") in observable_types:
observables.append({
"type": obj["type"],
"value": obj.get("value", ""),
"id": obj.get("id"),
})
return observables
# Usage
consumer = TAXIIConsumer(
f"https://cti-taxii.mitre.org/stix/collections/{ENTERPRISE_ATTACK_ID}/"
)
new_objects = consumer.poll_new_objects()
indicators = consumer.extract_indicators(new_objects)
print(f"New indicators: {len(indicators)}")
Step 5: Set Up Local TAXII Server with Medallion
# medallion configuration (medallion.conf)
TAXII_CONFIG = {
"backend": {
"module_class": "MemoryBackend",
},
"users": {
"admin": "admin_password",
"readonly": "readonly_password",
},
"taxii": {
"max_content_length": 10485760,
},
}
# Run medallion server:
# pip install medallion
# python -m medallion --config medallion.conf --port 5000
# Add objects to local TAXII server
import requests
def push_to_taxii(server_url, collection_id, stix_bundle, user, password):
"""Push STIX bundle to a TAXII 2.1 collection."""
url = f"{server_url}/collections/{collection_id}/objects/"
headers = {
"Content-Type": "application/stix+json;version=2.1",
"Accept": "application/taxii+json;version=2.1",
}
response = requests.post(
url,
json=stix_bundle,
headers=headers,
auth=(user, password),
timeout=30,
)
return response.json()
Validation Criteria
- TAXII server discovery returns valid API roots and collections
- STIX objects fetched and parsed correctly from TAXII collections
- Indicators extracted with valid STIX patterns
- Pagination handled correctly for large collections
- Consumer tracks polling state for incremental updates
- Local TAXII server accepts and serves STIX bundles
Compliance Framework Mapping
This skill supports compliance evidence collection across multiple frameworks:
- SOC 2: CC7.1 (Monitoring), CC7.2 (Anomaly Detection)
- ISO 27001: A.6.1 (Threat Intelligence), A.16.1 (Security Incident Management)
- NIST 800-53: PM-16 (Threat Awareness), RA-3 (Risk Assessment), SI-5 (Security Alerts)
- NIST CSF: ID.RA (Risk Assessment), DE.AE (Anomalies & Events)
Claw GRC Tip: When this skill is executed by a registered agent, compliance evidence is automatically captured and mapped to the relevant controls in your active frameworks.
Deploying This Skill with Claw GRC
Agent Execution
Register this skill with your Claw GRC agent for automated execution:
# Install via CLI
npx claw-grc skills add implementing-stix-taxii-feed-integration
# Or load dynamically via MCP
grc.load_skill("implementing-stix-taxii-feed-integration")
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- SHA-256 chain hashing ensures no step can be modified after execution
- Evidence artifacts (configs, scan results, logs) are automatically attached to relevant controls
- Trust score impact — successful execution increases your agent's trust score
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