Agent skill

Implementing Taxii Server With Opentaxii

by mukul975 in mukul975/Anthropic-Cybersecurity-Skills

Deploy and configure a TAXII 2.1 server (Medallion) with Docker, publish and consume STIX 2.1 bundles across collections, and integrate the feed with SIEM/SOAR platforms for automated indicator…

Apache-2.0Auto-check passedSecurity

Install Implementing Taxii Server With Opentaxii

skills CLI
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-taxii-server-with-opentaxii -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills implementing-taxii-server-with-opentaxii --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/implementing-taxii-server-with-opentaxii .claude/skills/implementing-taxii-server-with-opentaxii && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
implementing-taxii-server-with-opentaxii
GitHub stars
34k
Token cost
~3.6k tokens
SKILL.md length
382 words
Files
4 (incl. scripts, references)
Skills in repo
644
Repo updated
First seen
Licence
Apache-2.0

At a glance

Deploy and configure a TAXII 2.1 server (Medallion) with Docker, publish and consume STIX 2.1 bundles across collections, and integrate the feed with SIEM/SOAR platforms for automated indicator…

  • Works in 5 steps: Deploy TAXII 2.1 Server with Medallion → Docker Deployment → Publish STIX 2.1 Objects to Collections → …
  • Standing up a TAXII server to share threat intel
  • SKILL.md covers Overview, When to Use, Prerequisites and Key Concepts, plus 3 more sections
  • Runs Python scripts from its folder; reaches taxii.organization.com

What it does

Implementing Taxii Server With Opentaxii is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Deploy and configure a TAXII 2.1 server (Medallion) with Docker, publish and consume STIX 2.1 bundles across collections, and integrate the feed with SIEM/SOAR platforms for automated indicator exchange between organizations. Use when standing up a TAXII server to share threat intel, configuring collections for CTI feeds, or automating STIX indicator ingestion into a SIEM/SOAR.

Its SKILL.md is about 3.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `references/api-reference.md` and `scripts/agent.py`).

It sits in Security, covering Security operations and Containers. It works with Docker. The repository describes itself as: 817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io…. The licence is Apache-2.0.

When your agent uses it

  • Standing up a TAXII server to share threat intel
  • Configuring collections for CTI feeds
  • Automating STIX indicator ingestion into a SIEM/SOAR

Example prompts

  • “/implementing-taxii-server-with-opentaxii”

Requirements

  • Python 3
  • Docker

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Deploy TAXII 2.1 Server with Medallion
  2. Docker Deployment
  3. Publish STIX 2.1 Objects to Collections
  4. Consume Intelligence from TAXII Collections
  5. Integrate with SIEM/SOAR

What it can do on your machine

Read from SKILL.md and the folder at commit 54a7988. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • taxii.organization.com

    Also links to:

    • github.com
    • docs.oasis-open.org
    • oasis-open.github.io
    • eclecticiq.com
    • kravensecurity.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Implementing Taxii Server With Opentaxii loads about 3.6k tokens when it runs, and up to ~4.6k if it reads all its reference files. Until then it costs about 105 tokens; SKILL.md has 382 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~105
When it runs · the whole SKILL.md, loaded when a task matches
~3.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from mukul975/Anthropic-Cybersecurity-Skills at commit 54a7988, republished under its Apache-2.0 licence (© mukul975). 382 words, ~3,558 tokens.

Download SKILL.mdSave it as .claude/skills/implementing-taxii-server-with-opentaxii/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
implementing-taxii-server-with-opentaxii
description
Deploy and configure a TAXII 2.1 server (Medallion) with Docker, publish and consume STIX 2.1 bundles across collections, and integrate the feed with SIEM/SOAR platforms for automated indicator exchange between organizations. Use when standing up a TAXII server to share threat intel, configuring collections for CTI feeds, or automating STIX indicator ingestion into a SIEM/SOAR.
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
mitre_attack
T1591, T1592, T1593, T1589

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.

Show full SKILL.md (138 more words)Show less
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
python
# 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
yaml
# 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
python
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
python
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
python
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

© mukul975, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts, references) in skills/implementing-taxii-server-with-opentaxii of mukul975/Anthropic-Cybersecurity-Skills.

  • SKILL.md
  • LICENSE
  • references/api-reference.md
  • scripts/agent.py

Open the folder on GitHubat commit 54a7988

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Works with

Questions about Implementing Taxii Server With Opentaxii

What does Implementing Taxii Server With Opentaxii do?

Deploy and configure a TAXII 2.1 server (Medallion) with Docker, publish and consume STIX 2.1 bundles across collections, and integrate the feed with SIEM/SOAR platforms for automated indicator…. Implementing Taxii Server With Opentaxii is an agent skill from mukul975/Anthropic-Cybersecurity-Skills.1 bundles across collections, and integrate the feed with SIEM/SOAR platforms for automated indicator exchange between organizations.

When should I use Implementing Taxii Server With Opentaxii?

Implementing Taxii Server With Opentaxii fits situations like: standing up a TAXII server to share threat intel; configuring collections for CTI feeds; automating STIX indicator ingestion into a SIEM/SOAR.

How do I install Implementing Taxii Server With Opentaxii in Claude Code?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-taxii-server-with-opentaxii -a claude-code`. Or copy the skill folder (skills/implementing-taxii-server-with-opentaxii in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/implementing-taxii-server-with-opentaxii in your project. Claude Code loads it when a task matches its description.

How do I install Implementing Taxii Server With Opentaxii in Codex?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-taxii-server-with-opentaxii -a codex`. Or copy the skill folder (skills/implementing-taxii-server-with-opentaxii in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/implementing-taxii-server-with-opentaxii in your project. Codex loads it when a task matches its description.

Can I use Implementing Taxii Server With Opentaxii in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-taxii-server-with-opentaxii -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/implementing-taxii-server-with-opentaxii, .gemini/skills/implementing-taxii-server-with-opentaxii, .github/skills/implementing-taxii-server-with-opentaxii and .opencode/skills/implementing-taxii-server-with-opentaxii in your project.

What does Implementing Taxii Server With Opentaxii need to run?

Going by SKILL.md and its folder, Implementing Taxii Server With Opentaxii needs Python for the scripts in its folder. Our summary lists: Python 3; Docker.

Does Implementing Taxii Server With Opentaxii access the network?

SKILL.md names 6 domains. In commands or code: taxii.organization.com; the agent is likely to contact it when it follows the instructions. As links in the text: github.com, docs.oasis-open.org, oasis-open.github.io, eclecticiq.com and kravensecurity.com. This is read from the text; nothing was executed.

Is Implementing Taxii Server With Opentaxii safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Implementing Taxii Server With Opentaxii use?

Implementing Taxii Server With Opentaxii is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Implementing Taxii Server With Opentaxii use?

About 3.6k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.1k tokens, read only when the agent opens those files.

What are the alternatives to Implementing Taxii Server With Opentaxii?

Skills that share tags, products or a category with Implementing Taxii Server With Opentaxii: Cyberowlai (karimhabush/cyberowl, 263 stars), DefectDojo Vulnerability Management (AgentSecOps/SecOpsAgentKit, 220 stars), Runtime Provisioner (nealbridges/VulnHunter, 678 stars) and Warp Vulnerability Triage (warpdotdev/warp, 65k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Implementing Taxii Server With Opentaxii?

mukul975 (a GitHub user) maintains it in mukul975/Anthropic-Cybersecurity-Skills, which has 34,116 GitHub stars. The repository holds 644 skills in this directory. The repository was last updated on August 31, 2026.

Source: mukul975/Anthropic-Cybersecurity-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.