
Implementing TAXII Server
FreeSet up a TAXII 2.1 server for threat intelligence sharing.
Free · Opens the source repo
What Implementing TAXII Server does
The Implementing TAXII Server with OpenTAXII skill provides a comprehensive guide for deploying a TAXII 2.1 server using Docker. This skill is designed for cybersecurity professionals who need to share and consume threat intelligence in a standardized format. By leveraging OpenTAXII, users can publish and manage STIX 2.1 bundles across various collections, facilitating automated indicator exchange between organizations. This capability is essential for improving threat detection and response times in security operations.
With this skill, you will learn to deploy the server, configure collections for threat intelligence feeds, and integrate the setup with SIEM/SOAR platforms. The skill covers the necessary prerequisites, including Python libraries and Docker configuration, ensuring that users are well-prepared to implement a TAXII server in their environments. The workflow includes detailed steps for server deployment, collection configuration, and publishing STIX objects, making it a practical resource for both new and experienced cybersecurity engineers.
This skill is particularly useful when establishing security controls aligned with compliance requirements or when building security architectures that require effective threat intelligence sharing. It enables organizations to automate the ingestion of STIX indicators into their existing security infrastructure, enhancing their overall threat intelligence capabilities. By following the provided scripts and guidelines, users can efficiently set up a TAXII server tailored to their specific needs.
When to use it
Use this skill when you need to establish a TAXII server for sharing cyber threat intelligence within your organization or with partners.
When not to use it
This skill may not be suitable for environments that do not require threat intelligence sharing or for users unfamiliar with Docker and Python.
What you can build with it
Deploying a TAXII Server
Set up a TAXII 2.1 server using Docker to facilitate threat intelligence sharing.
Integrating with SIEM/SOAR
Automate the ingestion of STIX indicators into your existing security infrastructure.
Configuring Threat Intelligence Collections
Create and manage collections for various types of threat intelligence data.
How to install Implementing TAXII Server
View source1. Install with the skills CLI
npx skills add mukul975/anthropic-cybersecurity-skills/implementing-taxii-server-with-opentaxii --agent claude-code2. Or install it manually
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Inside SKILL.md
Written by mukul975Implementing TAXII Server with OpenTAXII
Overview
TAXII (Trusted Automated eXchange of Intelligence Information) is an OASIS standard protocol for exchanging cyber threat intelligence over HTTPS. OpenTAXII is an open-source TAXII server implementation by EclecticIQ that supports TAXII 1.x, while the OASIS cti-taxii-server provides a TAXII 2.1 reference implementation. This skill covers deploying a TAXII server, configuring collections for threat intelligence feeds, publishing STIX 2.1 bundles, and integrating with SIEM/SOAR platforms for automated indicator ingestion.
When to Use
- When deploying or configuring implementing taxii server with opentaxii 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
- Python 3.9+ with
medallion,stix2,taxii2-client,opentaxii,cabbylibraries - Docker and Docker Compose for containerized deployment
- Understanding of STIX 2.1 objects (Indicator, Malware, Attack Pattern, Relationship)
- Familiarity with REST APIs and HTTPS configuration
- TLS certificates for production deployment
Key Concepts
TAXII 2.1 Architecture
TAXII 2.1 defines three services: Discovery (find available API roots), API Root (entry point for collections), and Collections (repositories of CTI objects). Collections support two access models: the Collection endpoint allows consumers to poll for objects, and the Status endpoint tracks the result of add operations. TAXII uses HTTP content negotiation with application/taxii+json;version=2.1.
Sharing Models
TAXII supports hub-and-spoke (central server distributes to consumers), peer-to-peer (bidirectional sharing between partners), and source-subscriber (producer publishes, consumers subscribe) models. Each collection can have read-only, write-only, or read-write access controls.
STIX 2.1 Content
TAXII transports STIX 2.1 bundles containing Structured Threat Information objects: Indicators (detection patterns), Observed Data, Malware, Attack Patterns, Threat Actors, Intrusion Sets, Campaigns, Relationships, and Sightings. Each object has a unique STIX ID, creation/modification timestamps, and optional TLP marking definitions.
Workflow
Step 1: Deploy TAXII 2.1 Server with Medallion
# Install medallion (OASIS reference implementation)
# pip install medallion
# medallion_config.json
import json
config = {
"backend": {
"module_class": "MemoryBackend",
"filename": "taxii_data.json"
},
"users": {
"admin": "admin_password_change_me",
"analyst": "analyst_password_change_me",
"readonly": "readonly_password_change_me"
},
"taxii": {
"max_content_length": 10485760
}
}
# Create initial data store
taxii_data = {
"discovery": {
"title": "Threat Intelligence TAXII Server",
"description": "TAXII 2.1 server for sharing CTI indicators",
"contact": "soc@organization.com",
"default": "https://taxii.organization.com/api/",
"api_roots": ["https://taxii.organization.com/api/"]
},
"api_roots": {
"api": {
"title": "Threat Intelligence API Root",
"description": "Primary API root for threat intelligence sharing",
"versions": ["application/taxii+json;version=2.1"],
"max_content_length": 10485760,
"collections": {
"malware-iocs": {
"id": "91a7b528-80eb-42ed-a74d-c6fbd5a26116",
"title": "Malware IOCs",
"description": "Indicators of compromise from malware analysis",
"can_read": True,
"can_write": True,
"media_types": ["application/stix+json;version=2.1"]
},
"apt-intelligence": {
"id": "52892447-4d7e-4f70-b94a-5460e242dd23",
"title": "APT Intelligence",
"description": "Advanced persistent threat group intelligence",
"can_read": True,
"can_write": True,
"media_types": ["application/stix+json;version=2.1"]
},
"phishing-indicators": {
"id": "64993447-4d7e-4f70-b94a-5460e242ee34",
"title": "Phishing Indicators",
"description": "Phishing URLs, domains, and email indicators",
"can_read": True,
"can_write": True,
"media_types": ["application/stix+json;version=2.1"]
}
}
}
}
}
with open("medallion_config.json", "w") as f:
json.dump(config, f, indent=2)
with open("taxii_data.json", "w") as f:
json.dump(taxii_data, f, indent=2)
print("[+] TAXII server configuration created")
Step 2: Docker Deployment
# docker-compose.yml
version: '3.8'
services:
taxii-server:
image: python:3.11-slim
container_name: taxii-server
working_dir: /app
volumes:
- ./medallion_config.json:/app/medallion_config.json
- ./taxii_data.json:/app/taxii_data.json
- ./certs:/app/certs
ports:
- "6100:6100"
command: >
bash -c "pip install medallion &&
medallion --host 0.0.0.0 --port 6100
--config /app/medallion_config.json"
restart: unless-stopped
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:6100/taxii2/"]
interval: 30s
timeout: 10s
retries: 3
Step 3: Publish STIX 2.1 Objects to Collections
from stix2 import Indicator, Malware, Relationship, Bundle, TLP_WHITE
from taxii2client.v21 import Server, Collection, as_pages
import json
from datetime import datetime
class TAXIIPublisher:
def __init__(self, server_url, username, password):
self.server = Server(
server_url,
user=username,
password=password,
)
def list_collections(self):
"""List all available collections."""
api_root = self.server.api_roots[0]
for collection in api_root.collections:
print(f" [{collection.id}] {collection.title} "
f"(read={collection.can_read}, write={collection.can_write})")
return api_root.collections
def publish_indicators(self, collection_id, indicators):
"""Publish STIX indicators to a TAXII collection."""
api_root = self.server.api_roots[0]
collection = Collection(
f"{api_root.url}collections/{collection_id}/",
user=self.server._user,
password=self.server._password,
)
bundle = Bundle(objects=indicators)
response = collection.add_objects(bundle.serialize())
print(f"[+] Published {len(indicators)} objects to {collection_id}")
print(f" Status: {response.status}")
return response
def create_malware_indicators(self):
"""Create sample STIX malware indicators."""
malware = Malware(
name="SUNBURST",
description="Backdoor used in SolarWinds supply chain attack (2020). "
"Trojanized SolarWinds.Orion.Core.BusinessLayer.dll module.",
malware_types=["backdoor", "trojan"],
is_family=True,
object_marking_refs=[TLP_WHITE],
)
indicator_hash = Indicator(
name="SUNBURST SHA-256 Hash",
description="SHA-256 hash of trojanized SolarWinds Orion DLL",
pattern="[file:hashes.'SHA-256' = "
"'32519b85c0b422e4656de6e6c41878e95fd95026267daab4215ee59c107d6c77']",
pattern_type="stix",
valid_from=datetime(2020, 12, 13),
indicator_types=["malicious-activity"],
object_marking_refs=[TLP_WHITE],
)
indicator_domain = Indicator(
name="SUNBURST C2 Domain Pattern",
description="DGA domain pattern used by SUNBURST for C2",
pattern="[domain-name:value MATCHES "
"'^[a-z0-9]{4,}\\.appsync-api\\..*\\.avsvmcloud\\.com$']",
pattern_type="stix",
valid_from=datetime(2020, 12, 13),
indicator_types=["malicious-activity"],
object_marking_refs=[TLP_WHITE],
)
rel = Relationship(
relationship_type="indicates",
source_ref=indicator_hash.id,
target_ref=malware.id,
)
return [malware, indicator_hash, indicator_domain, rel]
publisher = TAXIIPublisher(
"https://taxii.organization.com/taxii2/",
"admin", "admin_password_change_me"
)
collections = publisher.list_collections()
indicators = publisher.create_malware_indicators()
publisher.publish_indicators("91a7b528-80eb-42ed-a74d-c6fbd5a26116", indicators)
Step 4: Consume Intelligence from TAXII Collections
from taxii2client.v21 import Server, Collection, as_pages
import json
class TAXIIConsumer:
def __init__(self, server_url, username, password):
self.server = Server(server_url, user=username, password=password)
def poll_collection(self, collection_id, added_after=None):
"""Poll a collection for new STIX objects."""
api_root = self.server.api_roots[0]
collection = Collection(
f"{api_root.url}collections/{collection_id}/",
user=self.server._user,
password=self.server._password,
)
kwargs = {}
if added_after:
kwargs["added_after"] = added_after
all_objects = []
for bundle in as_pages(collection.get_objects, per_request=50, **kwargs):
objects = json.loads(bundle).get("objects", [])
all_objects.extend(objects)
indicators = [o for o in all_objects if o.get("type") == "indicator"]
malware = [o for o in all_objects if o.get("type") == "malware"]
relationships = [o for o in all_objects if o.get("type") == "relationship"]
print(f"[+] Polled {len(all_objects)} objects: "
f"{len(indicators)} indicators, {len(malware)} malware, "
f"{len(relationships)} relationships")
return all_objects
def extract_iocs_for_siem(self, stix_objects):
"""Extract IOCs from STIX objects for SIEM ingestion."""
iocs = []
for obj in stix_objects:
if obj.get("type") == "indicator":
pattern = obj.get("pattern", "")
iocs.append({
"id": obj.get("id"),
"name": obj.get("name", ""),
"pattern": pattern,
"valid_from": obj.get("valid_from", ""),
"indicator_types": obj.get("indicator_types", []),
"confidence": obj.get("confidence", 0),
})
return iocs
consumer = TAXIIConsumer(
"https://taxii.organization.com/taxii2/",
"analyst", "analyst_password_change_me"
)
objects = consumer.poll_collection("91a7b528-80eb-42ed-a74d-c6fbd5a26116")
iocs = consumer.extract_iocs_for_siem(objects)
Step 5: Integrate with SIEM/SOAR
import requests
def push_to_splunk(iocs, splunk_url, hec_token):
"""Push extracted IOCs to Splunk via HEC."""
headers = {"Authorization": f"Splunk {hec_token}"}
for ioc in iocs:
event = {
"event": ioc,
"sourcetype": "stix:indicator",
"source": "taxii-server",
"index": "threat_intel",
}
resp = requests.post(
f"{splunk_url}/services/collector/event",
headers=headers,
json=event,
verify=not os.environ.get("SKIP_TLS_VERIFY", "").lower() == "true", # Set SKIP_TLS_VERIFY=true for self-signed certs in lab environments
)
if resp.status_code != 200:
print(f"[-] Splunk HEC error: {resp.text}")
print(f"[+] Pushed {len(iocs)} IOCs to Splunk")
def push_to_elasticsearch(iocs, es_url, index="threat-intel"):
"""Push IOCs to Elasticsearch."""
for ioc in iocs:
resp = requests.post(
f"{es_url}/{index}/_doc",
json=ioc,
headers={"Content-Type": "application/json"},
)
if resp.status_code not in (200, 201):
print(f"[-] ES error: {resp.text}")
print(f"[+] Indexed {len(iocs)} IOCs in Elasticsearch")
Validation Criteria
- TAXII 2.1 server deployed and accessible via HTTPS
- Collections created with appropriate read/write permissions
- STIX 2.1 bundles published successfully to collections
- Consumer can poll and retrieve objects with filtering
- IOCs extracted and forwarded to SIEM platform
- Authentication and authorization enforced correctly
References
Frequently asked questions about Implementing TAXII Server
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