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building-ioc-enrichment-pipeline-with-opencti

Build an automated IOC enrichment pipeline on OpenCTI (STIX 2.1 native

Install / Use

npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill building-ioc-enrichment-pipeline-with-opencti

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

91/100

Category

Security

Supported Platforms

Universal

Our assessment of building-ioc-enrichment-pipeline-with-opencti

building-ioc-enrichment-pipeline-with-opencti scores 91/100 on our quality scale, 233rd of 544 Security skills we index (top 43%).

Its SKILL.md is 9.7 KB long, well organised into 12 sections with 1 code example: a thorough specification that gives an agent plenty to work with.

With 33,340 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
29/30
Structure
17/20
Description
12/15
Adoption
19/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 25 days ago, so building-ioc-enrichment-pipeline-with-opencti is actively maintained.
  • It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.

AI review by kimi-k2.7-code on 2026-09-26. Automated pattern scan on 2026-09-25. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

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Frequently asked questions

How do I install building-ioc-enrichment-pipeline-with-opencti?
Run npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill building-ioc-enrichment-pipeline-with-opencti. The install tabs above show the steps for each supported agent.
Which AI agents does building-ioc-enrichment-pipeline-with-opencti work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is building-ioc-enrichment-pipeline-with-opencti safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It is Apache-2.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is building-ioc-enrichment-pipeline-with-opencti still maintained?
The repository was last updated 25 days ago, so building-ioc-enrichment-pipeline-with-opencti is actively maintained.

name: building-ioc-enrichment-pipeline-with-opencti description: Build an automated IOC enrichment pipeline on OpenCTI (STIX 2.1 native threat intel platform) using its internal enrichment connectors to pull context from VirusTotal, Shodan, AbuseIPDB, and GreyNoise, correlate indicators with known actors/campaigns, and score them for analyst prioritization. Use when deploying OpenCTI or automating enrichment and confidence scoring of newly ingested indicators. domain: cybersecurity subdomain: threat-intelligence tags:

  • threat-intelligence
  • cti
  • ioc
  • mitre-attack
  • stix
  • opencti
  • enrichment
  • virustotal 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:
  • T1071.001
  • T1583.001
  • T1105
  • T1590.005
  • T1588.001

Building IOC Enrichment Pipeline with OpenCTI

Overview

OpenCTI is an open-source platform for managing cyber threat intelligence knowledge, built on STIX 2.1 as its native data model. This skill covers building an automated IOC enrichment pipeline using OpenCTI's connector ecosystem to enrich indicators with context from VirusTotal, Shodan, AbuseIPDB, GreyNoise, and other sources. The pipeline automatically enriches newly ingested indicators, correlates them with known threat actors and campaigns, and scores them for analyst prioritization.

When to Use

  • When deploying or configuring building ioc enrichment pipeline with opencti 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 OpenCTI deployment
  • Python 3.9+ with pycti library
  • API keys for enrichment services: VirusTotal, Shodan, AbuseIPDB, GreyNoise
  • Understanding of STIX 2.1 data model and relationships
  • ElasticSearch or OpenSearch for OpenCTI backend
  • RabbitMQ or Redis for connector messaging

Key Concepts

OpenCTI Architecture

OpenCTI uses a GraphQL API frontend backed by ElasticSearch for storage and Redis/RabbitMQ for connector communication. Data is natively stored as STIX 2.1 objects with relationships. Connectors are categorized as: External Import (feed ingestion), Internal Import (file parsing), Internal Enrichment (context addition), and Stream (real-time export).

Enrichment Connector Model

Internal enrichment connectors are triggered automatically when new observables are created or manually by analysts. Each connector receives STIX objects, queries external services, and returns STIX 2.1 bundles that augment the original observable with additional context, labels, and relationships.

Confidence Scoring

OpenCTI uses a 0-100 confidence scale for indicators. Enrichment connectors can update confidence scores based on external validation: VirusTotal detection ratios, Shodan exposure data, AbuseIPDB report counts, and GreyNoise classification results.

Workflow

Step 1: Deploy OpenCTI with Docker Compose

# docker-compose.yml (key services)
version: '3'
services:
  opencti:
    image: opencti/platform:6.4.4
    environment:
      - APP__PORT=8080
      - APP__ADMIN__EMAIL=admin@opencti.io
      - APP__ADMIN__PASSWORD=ChangeMeNow
      - APP__ADMIN__TOKEN=your-admin-token-uuid
      - ELASTICSEARCH__URL=http://elasticsearch:9200
      - MINIO__ENDPOINT=minio
      - RABBITMQ__HOSTNAME=rabbitmq
    ports:
      - "8080:8080"
    depends_on:
      - elasticsearch
      - minio
      - rabbitmq
      - redis

  connector-virustotal:
    image: opencti/connector-virustotal:6.4.4
    environment:
      - OPENCTI_URL=http://opencti:8080
      - OPENCTI_TOKEN=your-admin-token-uuid
      - CONNECTOR_ID=connector-virustotal-id
      - CONNECTOR_NAME=VirusTotal
      - CONNECTOR_SCOPE=StixFile,Artifact,IPv4-Addr,Domain-Name,Url
      - CONNECTOR_AUTO=true
      - VIRUSTOTAL_TOKEN=your-vt-api-key
      - VIRUSTOTAL_MAX_TLP=TLP:AMBER

  connector-shodan:
    image: opencti/connector-shodan:6.4.4
    environment:
      - OPENCTI_URL=http://opencti:8080
      - OPENCTI_TOKEN=your-admin-token-uuid
      - CONNECTOR_ID=connector-shodan-id
      - CONNECTOR_NAME=Shodan
      - CONNECTOR_SCOPE=IPv4-Addr
      - CONNECTOR_AUTO=true
      - SHODAN_TOKEN=your-shodan-api-key
      - SHODAN_MAX_TLP=TLP:AMBER

  connector-abuseipdb:
    image: opencti/connector-abuseipdb:6.4.4
    environment:
      - OPENCTI_URL=http://opencti:8080
      - OPENCTI_TOKEN=your-admin-token-uuid
      - CONNECTOR_ID=connector-abuseipdb-id
      - CONNECTOR_NAME=AbuseIPDB
      - CONNECTOR_SCOPE=IPv4-Addr
      - CONNECTOR_AUTO=true
      - ABUSEIPDB_API_KEY=your-abuseipdb-key

Step 2: Build Custom Enrichment Connector

import os
from pycti import OpenCTIConnectorHelper, get_config_variable
from stix2 import (
    Bundle, Indicator, Note, Relationship,
    IPv4Address, DomainName
)
import requests


class CustomEnrichmentConnector:
    def __init__(self):
        config = {
            "opencti": {
                "url": os.environ.get("OPENCTI_URL"),
                "token": os.environ.get("OPENCTI_TOKEN"),
            },
            "connector": {
                "id": os.environ.get("CONNECTOR_ID"),
                "name": "CustomEnrichment",
                "scope": "IPv4-Addr,Domain-Name,Url",
                "auto": True,
                "type": "INTERNAL_ENRICHMENT",
            },
        }
        self.helper = OpenCTIConnectorHelper(config)
        self.helper.listen(self._process_message)

    def _process_message(self, data):
        entity_id = data["entity_id"]
        stix_object = self.helper.api.stix_cyber_observable.read(id=entity_id)

        if not stix_object:
            return "Observable not found"

        observable_type = stix_object["entity_type"]
        observable_value = stix_object.get("value", "")

        enrichment_results = []

        if observable_type == "IPv4-Addr":
            enrichment_results = self._enrich_ip(observable_value, entity_id)
        elif observable_type == "Domain-Name":
            enrichment_results = self._enrich_domain(observable_value, entity_id)

        if enrichment_results:
            bundle = Bundle(objects=enrichment_results, allow_custom=True)
            self.helper.send_stix2_bundle(bundle.serialize())

        return "Enrichment completed"

    def _enrich_ip(self, ip_address, entity_id):
        """Enrich IP address with GreyNoise, AbuseIPDB context."""
        objects = []

        # GreyNoise Community API
        try:
            gn_response = requests.get(
                f"https://api.greynoise.io/v3/community/{ip_address}",
                headers={"key": os.environ.get("GREYNOISE_API_KEY")},
                timeout=30,
            )
            if gn_response.status_code == 200:
                gn_data = gn_response.json()
                classification = gn_data.get("classification", "unknown")
                noise = gn_data.get("noise", False)
                riot = gn_data.get("riot", False)

                note_content = (
                    f"## GreyNoise Enrichment\n"
                    f"- Classification: {classification}\n"
                    f"- Internet Noise: {noise}\n"
                    f"- RIOT (Benign Service): {riot}\n"
                    f"- Name: {gn_data.get('name', 'N/A')}\n"
                    f"- Last Seen: {gn_data.get('last_seen', 'N/A')}"
                )

                note = Note(
                    content=note_content,
                    object_refs=[entity_id],
                    abstract=f"GreyNoise: {classification}",
                    allow_custom=True,
                )
                objects.append(note)

                # Add labels based on classification
                if classification == "malicious":
                    self.helper.api.stix_cyber_observable.add_label(
                        id=entity_id, label_name="greynoise:malicious"
                    )
                elif riot:
                    self.helper.api.stix_cyber_observable.add_label(
                        id=entity_id, label_name="greynoise:benign-service"
                    )

        except Exception as e:
            self.helper.log_error(f"GreyNoise enrichment failed: {e}")

        return objects

    def _enrich_domain(self, domain, entity_id):
        """Enrich domain with WHOIS and DNS context."""
        objects = []

        try:
            # Use SecurityTrails API for domain enrichment
            st_response = requests.get(
                f"https://api.securitytrails.com/v1/domain/{domain}",
                headers={"APIKEY": os.environ.get("SECURITYTRAILS_API_KEY")},
                timeout=30,
            )
            if st_response.status_code == 200:
                st_data = st_response.json()
                current_dns = st_data.get("current_dns", {})

                a_records = [
                    r.get("ip") for r in current_dns.get("a", {}).get("values", [])
                ]

                note_content = (
                    f"## SecurityTrails Enrichment\n"
                    f"- A Records: {', '.join(a_records)}\n"
                    f"- Alexa Rank: {st_data.get('alexa_rank', 'N/A')}\n"
                    f"- Hostname: {st_data.get('hostname', 'N/A')}"
                )

                note = Note(
                    content=note_content,
                    object_refs=[entity_id],
                    abstract=f"SecurityTrails: {domain}",
                    allow_custom=True,
                )
                objects.append(note)

        except Exception as e:
            self.helper.log_error(f"SecurityTrails enrichment failed: {e}")

        return objects


if __name__ == "__main__":
    connector = CustomEnrichmentConnector()

Related Skills

View on GitHub
GitHub Stars33.3k
CategorySecurity
Updated25d ago
Forks4.0k

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions