Performing Threat Intelligence Sharing with MISP

Overview

MISP (Malware Information Sharing Platform) is an open-source threat intelligence platform designed for collecting, storing, distributing, and sharing cybersecurity indicators and threat information. PyMISP is the official Python library for interacting with MISP instances via the REST API, enabling programmatic event creation, attribute management, tag assignment, galaxy cluster attachment, and feed synchronization. This guide covers using PyMISP to create events with structured IOCs (IP addresses, domains, file hashes, URLs), enrich events with MITRE ATT&CK tags, manage sharing groups and distribution levels, search for existing intelligence, and export in STIX 2.1 format for interoperability with other platforms.

Prerequisites

• MISP instance (v2.4+) with API access enabled
• Python 3.9+ with pymisp (pip install pymisp)
• MISP API key (Settings > Auth Keys)
• Understanding of MISP data model (Events, Attributes, Objects, Tags, Galaxies)
• Knowledge of TLP marking and sharing protocols

Steps

1. Install PyMISP: pip install pymisp
2. Initialize ExpandedPyMISP(url, key, ssl=True) connection
3. Create a MISPEvent with info, distribution level, threat level, and analysis status
4. Add attributes via event.add_attribute(type, value) for IPs, domains, hashes
5. Apply TLP tags and MITRE ATT&CK technique tags
6. Publish the event with misp.publish(event)
7. Search existing events with misp.search(controller='events', value=..., type_attribute=...)
8. Enable and configure threat feeds for automatic IOC ingestion
9. Export events in STIX 2.1 format for cross-platform sharing
10. Validate sharing group configuration and sync server settings

Expected Output

A JSON report summarizing events created, attributes added, tags applied, feed sync status, and any correlation hits against existing intelligence, with event IDs and distribution metadata.

Verification Criteria

Confirm successful execution by validating:

• [ ] All prerequisite tools and access requirements are satisfied
• [ ] Each workflow step completed without errors
• [ ] Output matches expected format and contains expected data
• [ ] No security warnings or misconfigurations detected
• [ ] Results are documented and evidence is preserved for audit

Compliance Framework Mapping

This skill supports compliance evidence collection across multiple frameworks:

• SOC 2: CC7.1 (Monitoring), CC7.2 (Anomaly Detection)
• ISO 27001: A.6.1 (Threat Intelligence), A.16.1 (Security Incident Management)
• NIST 800-53: PM-16 (Threat Awareness), RA-3 (Risk Assessment), SI-5 (Security Alerts)
• NIST CSF: ID.RA (Risk Assessment), DE.AE (Anomalies & Events)

Claw GRC Tip: When this skill is executed by a registered agent, compliance evidence is automatically captured and mapped to the relevant controls in your active frameworks.

Deploying This Skill with Claw GRC

Agent Execution

Register this skill with your Claw GRC agent for automated execution:

# Install via CLI
npx claw-grc skills add performing-threat-intelligence-sharing-with-misp

# Or load dynamically via MCP
grc.load_skill("performing-threat-intelligence-sharing-with-misp")

Audit Trail Integration

When executed through Claw GRC, every step of this skill generates tamper-evident audit records:

• SHA-256 chain hashing ensures no step can be modified after execution
• Evidence artifacts (configs, scan results, logs) are automatically attached to relevant controls
• Trust score impact — successful execution increases your agent's trust score

Continuous Compliance

Schedule this skill for recurring execution to maintain continuous compliance posture. Claw GRC monitors for drift and alerts when re-execution is needed.