Agent skill

Building Threat Intelligence Platform

by mukul975 in mukul975/Anthropic-Cybersecurity-Skills

Design and deploy a Threat Intelligence Platform (TIP) by integrating open-source CTI tools (MISP, OpenCTI, TheHive, Cortex) into a unified system with feed ingestion pipelines, enrichment…

Apache-2.0Auto-check passedSecurity

Install Building Threat Intelligence Platform

skills CLI
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill building-threat-intelligence-platform -a claude-code

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

GitHub CLI
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills building-threat-intelligence-platform --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/building-threat-intelligence-platform .claude/skills/building-threat-intelligence-platform && 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
building-threat-intelligence-platform
GitHub stars
34k
Token cost
~2.5k tokens
SKILL.md length
333 words
Files
8 (incl. scripts, references, assets)
Skills in repo
644
Repo updated
First seen
Licence
Apache-2.0

At a glance

Design and deploy a Threat Intelligence Platform (TIP) by integrating open-source CTI tools (MISP, OpenCTI, TheHive, Cortex) into a unified system with feed ingestion pipelines, enrichment…

  • Works in 4 steps: Deploy Platform with Docker Compose → Configure Feed Ingestion Pipeline → Build Enrichment Pipeline with Cortex → …
  • Standing up a centralized CTI platform to collect
  • SKILL.md covers Overview, When to Use, Prerequisites and Key Concepts, plus 3 more sections
  • Runs Python scripts from its folder; needs APP__ADMIN__PASSWORD and APP__ADMIN__TOKEN

What it does

Building Threat Intelligence Platform is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Design and deploy a Threat Intelligence Platform (TIP) by integrating open-source CTI tools (MISP, OpenCTI, TheHive, Cortex) into a unified system with feed ingestion pipelines, enrichment workflows, STIX/TAXII interoperability, and analyst dashboards. Use when architecting or standing up a centralized CTI platform to collect, analyze, and disseminate threat intelligence across a security team.

Its SKILL.md is about 2.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts, reference files and assets (for example `assets/template.md`, `references/api-reference.md` and `references/standards.md`).

It sits in Security, covering OSINT. 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 centralized CTI platform to collect
  • Disseminate threat intelligence across a security team

Example prompts

  • “/building-threat-intelligence-platform”

Requirements

  • Python 3
  • Docker
  • A credential in APP__ADMIN__TOKEN

Workflow steps

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

  1. Deploy Platform with Docker Compose
  2. Configure Feed Ingestion Pipeline
  3. Build Enrichment Pipeline with Cortex
  4. Implement Analyst Dashboard Metrics

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 2 files in scripts/ (Python), which the agent can run.

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

  • Network

    Links to these hosts (documentation or services it may open):

    • docs.opencti.io
    • misp-project.org
    • thehive-project.org
    • github.com

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

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • APP__ADMIN__PASSWORD
    • APP__ADMIN__TOKEN

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

Context cost

Building Threat Intelligence Platform loads about 2.5k tokens when it runs, and up to ~3.7k if it reads all its reference files. Until then it costs about 109 tokens; SKILL.md has 333 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~109
When it runs · the whole SKILL.md, loaded when a task matches
~2.5k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.7k

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). 333 words, ~2,549 tokens.

Download SKILL.mdSave it as .claude/skills/building-threat-intelligence-platform/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
building-threat-intelligence-platform
description
Design and deploy a Threat Intelligence Platform (TIP) by integrating open-source CTI tools (MISP, OpenCTI, TheHive, Cortex) into a unified system with feed ingestion pipelines, enrichment workflows, STIX/TAXII interoperability, and analyst dashboards. Use when architecting or standing up a centralized CTI platform to collect, analyze, and disseminate threat intelligence across a security team.
domain
cybersecurity
subdomain
threat-intelligence
tags
threat-intelligence, cti, ioc, mitre-attack, stix, platform-building, misp, opencti
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
T1071, T1588.001, T1591

Building Threat Intelligence Platform

Overview

Building a Threat Intelligence Platform (TIP) involves deploying and integrating multiple CTI tools into a unified system for collecting, analyzing, enriching, and disseminating threat intelligence. This skill covers designing TIP architecture using open-source tools (MISP, OpenCTI, TheHive, Cortex), configuring feed ingestion pipelines, establishing enrichment workflows, implementing STIX/TAXII interoperability, and building analyst dashboards for CTI operations.

When to Use

  • When deploying or configuring building threat intelligence platform 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

  • Docker and Docker Compose for deploying platform components
  • Python 3.9+ with pymisp, pycti, thehive4py libraries
  • Elasticsearch/OpenSearch cluster for data storage
  • Redis and RabbitMQ for message queuing
  • Understanding of STIX 2.1 data model and TAXII 2.1 transport
  • API keys for enrichment services (VirusTotal, Shodan, AbuseIPDB)

Key Concepts

TIP Architecture Components
  1. Collection Layer: Feed ingestion from OSINT, commercial, and internal sources
  2. Storage Layer: Elasticsearch/OpenSearch for indexed CTI data with STIX 2.1 schema
  3. Analysis Layer: OpenCTI for knowledge graph analysis and MISP for IOC correlation
  4. Enrichment Layer: Cortex analyzers for automated IOC enrichment
  5. Response Layer: TheHive for case management and incident response integration
  6. Sharing Layer: TAXII server for outbound intelligence sharing
Platform Integration Points
  • MISP <-> OpenCTI: Bidirectional sync via OpenCTI MISP connector
  • OpenCTI <-> TheHive: Alert/case creation from high-confidence indicators
  • TheHive <-> Cortex: Automated analysis and enrichment of case observables
  • All <-> SIEM: Real-time IOC push to Splunk/Elastic via API or Kafka

Workflow

Step 1: Deploy Platform with Docker Compose
yaml
version: '3.8'
services:
  # --- Storage Layer ---
  elasticsearch:
    image: docker.elastic.co/elasticsearch/elasticsearch:8.12.0
    environment:
      - discovery.type=single-node
      - xpack.security.enabled=false
      - "ES_JAVA_OPTS=-Xms2g -Xmx2g"
    ports:
      - "9200:9200"
    volumes:
      - es-data:/usr/share/elasticsearch/data

  redis:
    image: redis:7
    ports:
      - "6379:6379"

  rabbitmq:
    image: rabbitmq:3-management
    ports:
      - "5672:5672"
      - "15672:15672"

  minio:
    image: minio/minio
    command: server /data --console-address ":9001"
    ports:
      - "9000:9000"
      - "9001:9001"

  # --- MISP ---
  misp:
    image: ghcr.io/misp/misp-docker/misp-core:latest
    ports:
      - "8443:443"
    environment:
      - MISP_ADMIN_EMAIL=admin@tip.local
      - MISP_BASEURL=https://localhost:8443
    volumes:
      - misp-data:/var/www/MISP/app/files

  # --- OpenCTI ---
  opencti:
    image: opencti/platform:6.4.4
    environment:
      - APP__PORT=8080
      - APP__ADMIN__EMAIL=admin@tip.local
      - APP__ADMIN__PASSWORD=TIPAdminPassword
      - APP__ADMIN__TOKEN=tip-opencti-token-uuid
      - ELASTICSEARCH__URL=http://elasticsearch:9200
      - MINIO__ENDPOINT=minio
      - RABBITMQ__HOSTNAME=rabbitmq
      - REDIS__HOSTNAME=redis
    ports:
      - "8080:8080"
    depends_on:
      - elasticsearch
      - redis
      - rabbitmq
      - minio

  # --- TheHive ---
  thehive:
    image: strangebee/thehive:5.3
    environment:
      - TH_CORTEX_URL=http://cortex:9001
    ports:
      - "9000:9000"
    depends_on:
      - elasticsearch

  # --- Cortex ---
  cortex:
    image: thehiveproject/cortex:3.1.8
    ports:
      - "9001:9001"
    depends_on:
      - elasticsearch

volumes:
  es-data:
  misp-data:
Step 2: Configure Feed Ingestion Pipeline
python
from pymisp import PyMISP
from pycti import OpenCTIApiClient
import json

class TIPFeedManager:
    """Manage threat intelligence feed ingestion across platform components."""

    def __init__(self, misp_url, misp_key, opencti_url, opencti_token):
        self.misp = PyMISP(misp_url, misp_key, ssl=False)
        self.opencti = OpenCTIApiClient(opencti_url, opencti_token)

    def configure_osint_feeds(self):
        """Enable default OSINT feeds in MISP."""
        osint_feeds = [
            {"name": "CIRCL OSINT", "id": 1},
            {"name": "Botvrij.eu", "id": 2},
            {"name": "abuse.ch URLhaus", "id": 5},
            {"name": "abuse.ch Feodo Tracker", "id": 6},
        ]
        for feed in osint_feeds:
            try:
                self.misp.enable_feed(feed["id"])
                self.misp.fetch_feed(feed["id"])
                print(f"[+] Enabled feed: {feed['name']}")
            except Exception as e:
                print(f"[-] Failed: {feed['name']}: {e}")

    def configure_opencti_connectors(self):
        """List and verify OpenCTI connector status."""
        connectors = self.opencti.connector.list()
        for conn in connectors:
            print(
                f"  Connector: {conn['name']} - "
                f"Active: {conn['active']} - "
                f"Type: {conn['connector_type']}"
            )

    def sync_misp_to_opencti(self):
        """Verify MISP-OpenCTI sync is operational."""
        # OpenCTI MISP connector handles this automatically
        # Check connector status
        connectors = self.opencti.connector.list()
        misp_connector = [
            c for c in connectors if "misp" in c["name"].lower()
        ]
        if misp_connector:
            print(f"[+] MISP connector active: {misp_connector[0]['active']}")
        else:
            print("[-] MISP connector not found - configure in Docker Compose")
Step 3: Build Enrichment Pipeline with Cortex
python
import requests

class CortexEnrichment:
    """Integrate Cortex analyzers for automated enrichment."""

    def __init__(self, cortex_url, cortex_key):
        self.url = cortex_url
        self.headers = {"Authorization": f"Bearer {cortex_key}"}

    def list_analyzers(self):
        """List available Cortex analyzers."""
        resp = requests.get(
            f"{self.url}/api/analyzer",
            headers=self.headers,
            timeout=30,
        )
        if resp.status_code == 200:
            analyzers = resp.json()
            for a in analyzers:
                print(f"  {a['name']}: {a.get('description', '')[:60]}")
            return analyzers
        return []

    def analyze_observable(self, observable_type, observable_value, analyzer_id):
        """Submit an observable for analysis."""
        job = {
            "data": observable_value,
            "dataType": observable_type,
            "tlp": 2,
            "message": "TIP automated enrichment",
        }
        resp = requests.post(
            f"{self.url}/api/analyzer/{analyzer_id}/run",
            json=job,
            headers=self.headers,
            timeout=30,
        )
        if resp.status_code == 200:
            return resp.json()
        return None

    def get_job_report(self, job_id):
        """Get the report for a completed analysis job."""
        resp = requests.get(
            f"{self.url}/api/job/{job_id}/report",
            headers=self.headers,
            timeout=60,
        )
        if resp.status_code == 200:
            return resp.json()
        return None
Step 4: Implement Analyst Dashboard Metrics
python
class TIPMetrics:
    """Collect platform metrics for analyst dashboards."""

    def __init__(self, misp, opencti):
        self.misp = misp
        self.opencti = opencti

    def get_platform_stats(self):
        """Collect statistics across all platform components."""
        stats = {}

        # MISP stats
        misp_stats = self.misp.get_server_statistics()
        stats["misp"] = {
            "total_events": misp_stats.get("event_count", 0),
            "total_attributes": misp_stats.get("attribute_count", 0),
            "active_feeds": len([
                f for f in self.misp.feeds()
                if f.get("Feed", {}).get("enabled")
            ]),
        }

        # OpenCTI stats via GraphQL
        stats["opencti"] = {
            "total_indicators": self.opencti.indicator.list(
                first=0, withPagination=True
            ).get("pagination", {}).get("globalCount", 0),
            "total_reports": self.opencti.report.list(
                first=0, withPagination=True
            ).get("pagination", {}).get("globalCount", 0),
        }

        return stats

Validation Criteria

  • All platform components (MISP, OpenCTI, TheHive, Cortex) deployed and accessible
  • MISP-OpenCTI bidirectional sync operational
  • At least 3 OSINT feeds ingesting data
  • Cortex analyzers configured and returning enrichment results
  • Platform metrics dashboard showing real-time statistics
  • STIX/TAXII export functional for intelligence sharing

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 7 other files (scripts, references, assets) in skills/building-threat-intelligence-platform of mukul975/Anthropic-Cybersecurity-Skills.

  • SKILL.md
  • LICENSE
  • assets/template.md
  • references/api-reference.md
  • references/standards.md
  • references/workflows.md
  • scripts/agent.py
  • scripts/process.py

Open the folder on GitHubat commit 54a7988

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Code Audit3stoneBrother/code-audit8921 repos~2.7kAutomated safety check: PassNone
Codeqlelastic/kibana21k—~1.7kAutomated safety check: PassCustom licence
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Works with

Categories

Questions about Building Threat Intelligence Platform

What does Building Threat Intelligence Platform do?

Design and deploy a Threat Intelligence Platform (TIP) by integrating open-source CTI tools (MISP, OpenCTI, TheHive, Cortex) into a unified system with feed ingestion pipelines, enrichment…. Building Threat Intelligence Platform is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Design and deploy a Threat Intelligence Platform (TIP) by integrating open-source CTI tools (MISP, OpenCTI, TheHive, Cortex) into a unified system with feed ingestion pipelines, enrichment workflows, STIX/TAXII interoperability, and analyst dashboards.

When should I use Building Threat Intelligence Platform?

Building Threat Intelligence Platform fits situations like: standing up a centralized CTI platform to collect; disseminate threat intelligence across a security team.

How do I install Building Threat Intelligence Platform in Claude Code?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill building-threat-intelligence-platform -a claude-code`. Or copy the skill folder (skills/building-threat-intelligence-platform in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/building-threat-intelligence-platform in your project. Claude Code loads it when a task matches its description.

How do I install Building Threat Intelligence Platform in Codex?

Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill building-threat-intelligence-platform -a codex`. Or copy the skill folder (skills/building-threat-intelligence-platform in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/building-threat-intelligence-platform in your project. Codex loads it when a task matches its description.

Can I use Building Threat Intelligence Platform 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 building-threat-intelligence-platform -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/building-threat-intelligence-platform, .gemini/skills/building-threat-intelligence-platform, .github/skills/building-threat-intelligence-platform and .opencode/skills/building-threat-intelligence-platform in your project.

What does Building Threat Intelligence Platform need to run?

Going by SKILL.md and its folder, Building Threat Intelligence Platform needs Python for the scripts in its folder and credentials named APP__ADMIN__PASSWORD and APP__ADMIN__TOKEN. Our summary lists: Python 3; Docker; A credential in APP__ADMIN__TOKEN.

Does Building Threat Intelligence Platform access the network?

SKILL.md names 4 domains. As links in the text: docs.opencti.io, misp-project.org, thehive-project.org and github.com. This is read from the text; nothing was executed.

Is Building Threat Intelligence Platform 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 Building Threat Intelligence Platform use?

Building Threat Intelligence Platform 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 Building Threat Intelligence Platform use?

About 2.5k tokens (SKILL.md is roughly 10k 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 Building Threat Intelligence Platform?

Skills that share tags, products or a category with Building Threat Intelligence Platform: Sherlock (Tommy-yw/RunbookHermes, 546 stars), Code Audit (3stoneBrother/code-audit, 892 stars), Codeql (elastic/kibana, 21k stars) and Osint (smixs/osint-skill, 141 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Building Threat Intelligence Platform?

mukul975 (a GitHub user) maintains it in mukul975/Anthropic-Cybersecurity-Skills, which has 33,993 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.