Processing STIX/TAXII Feeds

When to Use

Use this skill when:

• Onboarding a new TAXII 2.1 collection from a government feed (CISA AIS, FS-ISAC) or commercial provider
• Validating that ingested STIX bundles conform to the OASIS STIX 2.1 specification before import
• Building automated pipelines that parse STIX relationship objects to reconstruct campaign context

Do not use this skill for proprietary vendor feed formats (Recorded Future JSON, CrowdStrike IOC lists) that require vendor-specific parsers rather than STIX processing.

Prerequisites

• Python 3.9+ with

  stix2

  library (pip install stix2) and

  taxii2-client

  library
• Network access to TAXII 2.1 server endpoint with valid credentials
• Target TIP or SIEM with import API (MISP, OpenCTI, or Splunk ES)

Workflow

Step 1: Discover TAXII Server Collections

from taxii2client.v21 import Server, as_pages

server = Server("https://cti.example.com/taxii/",
                user="apiuser", password="apikey")
api_root = server.api_roots[0]
for collection in api_root.collections:
    print(collection.id, collection.title, collection.can_read)

Select collections relevant to your threat profile. CISA AIS provides collections segmented by sector (financial, energy, healthcare).

Step 2: Fetch STIX Bundles with Pagination

from taxii2client.v21 import Collection
from datetime import datetime, timedelta, timezone

collection = Collection(
    "https://cti.example.com/taxii/api1/collections/<id>/objects/",
    user="apiuser", password="apikey")

# Fetch only objects added in the last 24 hours
added_after = datetime.now(timezone.utc) - timedelta(hours=24)
for bundle_page in as_pages(collection.get_objects,
                             added_after=added_after, per_request=100):
    process_bundle(bundle_page)

Step 3: Parse and Validate STIX Objects

import stix2

def process_bundle(bundle_dict):
    bundle = stix2.parse(bundle_dict, allow_custom=True)
    for obj in bundle.objects:
        if obj.type == "indicator":
            validate_indicator(obj)
        elif obj.type == "threat-actor":
            upsert_threat_actor(obj)
        elif obj.type == "relationship":
            link_objects(obj)

def validate_indicator(indicator):
    required = ["id", "type", "spec_version", "created",
                "modified", "pattern", "pattern_type", "valid_from"]
    for field in required:
        if not hasattr(indicator, field):
            raise ValueError(f"Missing required field: {field}")
    # Check confidence range
    if hasattr(indicator, "confidence"):
        assert 0 <= indicator.confidence <= 100

Step 4: Route Objects to Consuming Platforms

Map STIX object types to destination systems:

• indicator

  objects → SIEM lookup tables and firewall blocklists

• malware

  objects → EDR threat intelligence library

• threat-actor

  /

  campaign

  objects → TIP for analyst context

• course-of-action

  objects → Security team wiki or SOAR playbook triggers

Use TLP marking definitions to enforce sharing restrictions:

for marking in obj.get("object_marking_refs", []):
    if "tlp-red" in marking:
        route_to_restricted_platform_only(obj)

Step 5: Publish Back to TAXII (Bi-directional Sharing)

# Add validated local intelligence back to shared collection
new_indicator = stix2.Indicator(
    name="Malicious C2 Domain",
    pattern="[domain-name:value = 'evil-c2.example.com']",
    pattern_type="stix",
    valid_from="2025-01-15T00:00:00Z",
    confidence=80,
    labels=["malicious-activity"],
    object_marking_refs=["marking-definition--34098fce-860f-479c-ae..."]  # TLP:GREEN
)
collection.add_objects(stix2.Bundle(new_indicator))

Key Concepts

[network-traffic:dst_port = 443 AND ipv4-addr:value = '10.0.0.1']

Tools & Systems

• stix2 (Python): Official OASIS Python library for creating, parsing, and validating STIX 2.0/2.1 objects
• taxii2-client (Python): Client library for TAXII 2.0/2.1 server discovery, collection enumeration, and object retrieval
• MISP: Open-source TIP with native TAXII 2.1 server and client; MISP-TAXII-Server plugin for publishing MISP events
• OpenCTI: CTI platform with built-in TAXII 2.1 connector; supports STIX 2.1 import/export natively
• Cabby: Legacy Python TAXII 1.x client for older government feeds still on TAXII 1.1

Common Pitfalls

• Ignoring

  spec_version

  field: STIX 2.0 and 2.1 have incompatible schemas (2.1 adds

  confidence

  ,

  object_marking_refs

  at bundle level). Always check

  spec_version

  before parsing.
• No pagination handling: TAXII servers cap responses at 100–1000 objects per request. Missing pagination (via

  next

  link header) causes silent data loss.
• Clock skew on

  added_after

  : Server and client time misalignment causes missed objects at interval boundaries. Use UTC exclusively and add 5-minute overlap windows.
• Storing raw STIX blobs without indexing: Storing bundles as opaque JSON prevents querying by indicator type or campaign. Parse into relational or graph database.
• Sharing TLP:RED content inadvertently: Automated pipelines must filter marking definitions before routing to any shared platform or SIEM with broad analyst access.