implementing-stix-taxii-feed-integration

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

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$npx skills install mukul975/Anthropic-Cybersecurity-Skills/implementing-stix-taxii-feed-integration
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summary

STIX (Structured Threat Information eXpression) and TAXII (Trusted Automated eXchange of Intelligence Information) are OASIS open standards for representing and transporting cyber threat intelligence.

skill.md
name
implementing-stix-taxii-feed-integration
description
STIX (Structured Threat Information eXpression) and TAXII (Trusted Automated eXchange of Intelligence Information) are OASIS open standards for representing and transporting cyber threat intelligence.
domain
cybersecurity
subdomain
threat-intelligence
tags
- threat-intelligence - cti - ioc - mitre-attack - stix - taxii - feed-integration - oasis
version
'1.0'
author
mahipal
license
Apache-2.0
nist_csf
- ID.RA-01 - ID.RA-05 - DE.CM-01 - DE.AE-02

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 skill 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.

When to Use

  • When deploying or configuring implementing stix taxii feed integration 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 taxii2-client, stix2, cti-taxii-client libraries
  • 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.

Workflow

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

References

how to use implementing-stix-taxii-feed-integration

How to use implementing-stix-taxii-feed-integration on Cursor

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1

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-stix-taxii-feed-integration
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-stix-taxii-feed-integration

The skills CLI fetches implementing-stix-taxii-feed-integration 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-stix-taxii-feed-integration

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

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

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
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ 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
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

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Ratings

4.658 reviews
  • Aditi Harris· Dec 24, 2024

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

  • Omar Brown· Dec 24, 2024

    implementing-stix-taxii-feed-integration is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Sofia Brown· Dec 16, 2024

    Useful defaults in implementing-stix-taxii-feed-integration — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Amelia Harris· Dec 8, 2024

    We added implementing-stix-taxii-feed-integration from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Diego Li· Dec 4, 2024

    I recommend implementing-stix-taxii-feed-integration for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Camila White· Nov 27, 2024

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

  • Aanya Huang· Nov 15, 2024

    Registry listing for implementing-stix-taxii-feed-integration matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Naina Desai· Nov 15, 2024

    implementing-stix-taxii-feed-integration reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Diego Jain· Nov 7, 2024

    Useful defaults in implementing-stix-taxii-feed-integration — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Diego Khan· Oct 26, 2024

    I recommend implementing-stix-taxii-feed-integration for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

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