Performing Threat Intelligence Sharing With Misp

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 skill 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.

When to Use

Trigger phrases:

• "performing threat intelligence sharing with misp"

• "Use PyMISP to create, enrich, and share threat intelligence events on a MISP pla"

• When conducting security assessments that involve performing threat intelligence sharing with misp

• When following incident response procedures for related security events

• When performing scheduled security testing or auditing activities

• When validating security controls through hands-on testing

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

# Example: IOC detection
import re

IOC_PATTERNS = {
    "ip": r"\b(?:\d{1,3}\.){3}\d{1,3}\b",
    "domain": r"\b[a-z0-9-]+\.[a-z]{2,}\b",
    "hash_md5": r"\b[a-f0-9]{32}\b",
    "hash_sha256": r"\b[a-f0-9]{64}\b",
}

def extract_iocs(text: str) -> dict:
    return {k: re.findall(v, text) for k, v in IOC_PATTERNS.items()}

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.

When NOT to Use

• You don't have explicit written authorization to test
• Task is about defense/detection, not offense (use detection skills)
• You need to implement security controls (use implementing-* skills)
• Task requires compliance auditing (use auditing-* skills)
• You're investigating an incident (use incident response skills)
• Target is out of scope for your engagement
• Task is about vulnerability scanning only (use scanning tools)

Red Flags

• Performing actions without explicit written authorization from the asset owner
• Testing against production systems without a defined scope and rules of engagement
• Acting on threat intelligence without validating source reliability
• Sharing classified or sensitive indicators without proper handling procedures
• Alerting threat actors to detection capabilities through visible response actions

Process

1. Design — Define interface, identify patterns, plan implementation
2. Implement — Write code following existing conventions, add tests
3. Verify — Run tests, check integration, validate behavior

Verification

• All steps executed successfully against a test environment before production use
• Output documented with screenshots or logs demonstrating expected behavior
• Results validated against known-good baselines or reference implementations
• Documentation complete enough for another analyst to reproduce findings

Anti-Rationalization Table