implementing-taxii-server-with-opentaxii

mukul975/Anthropic-Cybersecurity-Skills · updated May 25, 2026

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$npx skills install mukul975/Anthropic-Cybersecurity-Skills/implementing-taxii-server-with-opentaxii
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summary

Deploy and configure an OpenTAXII server to share and consume STIX-formatted cyber threat intelligence using the TAXII 2.1 protocol for automated indicator exchange between organizations.

skill.md
name
implementing-taxii-server-with-opentaxii
description
Deploy and configure an OpenTAXII server to share and consume STIX-formatted cyber threat intelligence using the TAXII 2.1 protocol for automated indicator exchange between organizations.
domain
cybersecurity
subdomain
threat-intelligence
tags
- taxii - stix - opentaxii - threat-sharing - cti - indicator-exchange - taxii-server - automation
version
'1.0'
author
mahipal
license
Apache-2.0
nist_csf
- ID.RA-01 - ID.RA-05 - DE.CM-01 - DE.AE-02

Implementing 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, cabby libraries
  • 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": "[email protected]",
        "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

how to use implementing-taxii-server-with-opentaxii

How to use implementing-taxii-server-with-opentaxii on Cursor

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Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add implementing-taxii-server-with-opentaxii
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills install mukul975/Anthropic-Cybersecurity-Skills/implementing-taxii-server-with-opentaxii

The skills CLI fetches implementing-taxii-server-with-opentaxii from GitHub repository mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.

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Select Cursor when prompted

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Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/implementing-taxii-server-with-opentaxii

Reload or restart Cursor to activate implementing-taxii-server-with-opentaxii. Access the skill through slash commands (e.g., /implementing-taxii-server-with-opentaxii) or your agent's skill management interface.

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Implementation Guide

Prerequisites

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Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
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  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

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Best Practices

✓ Do

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  • +Document successful prompt patterns

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  • Be specific about desired format and style
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✓ Use When

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✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
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  4. 4Build expertise through regular use and experimentation

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Ratings

4.770 reviews
  • Advait Martinez· Dec 28, 2024

    implementing-taxii-server-with-opentaxii is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Carlos Jackson· Dec 24, 2024

    implementing-taxii-server-with-opentaxii has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Sofia Shah· Dec 24, 2024

    implementing-taxii-server-with-opentaxii fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Noah Ndlovu· Dec 20, 2024

    Keeps context tight: implementing-taxii-server-with-opentaxii is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Noah Singh· Dec 16, 2024

    implementing-taxii-server-with-opentaxii reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Noah Gonzalez· Dec 12, 2024

    We added implementing-taxii-server-with-opentaxii from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Ganesh Mohane· Dec 4, 2024

    Keeps context tight: implementing-taxii-server-with-opentaxii is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Sakshi Patil· Nov 23, 2024

    implementing-taxii-server-with-opentaxii has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Carlos Patel· Nov 19, 2024

    implementing-taxii-server-with-opentaxii fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Advait Anderson· Nov 19, 2024

    Solid pick for teams standardizing on skills: implementing-taxii-server-with-opentaxii is focused, and the summary matches what you get after install.

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