Skip to content
Skillpedia
Misc35k · #6003

operationalizing-misp-threat-feeds

Helps your agent use threat information to create detection rules. It's useful for improving security and automating attack identification.

What it does

This tool helps set up a platform called MISP to collect cybersecurity threat information. It filters the information to remove useless data and turns it into detection rules to protect systems.

When to use it

  • ✓When you want to use threat intelligence to create security alerts.
  • ✓To organize and filter sources of cybersecurity threat data.
  • ✓To automate the creation of detection rules from threat data.

Example of what to ask your AI

“Set up MISP to collect threat feeds, filter out false positives, and generate Suricata detection rules.”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/mukul975/Anthropic-Cybersecurity-Skills/blob/main/skills/operationalizing-misp-threat-feeds/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/mukul975/Anthropic-Cybersecurity-Skills/blob/main/skills/operationalizing-misp-threat-feeds/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

The tool connects to MISP, selects reliable sources of threat information, applies filters to remove irrelevant data, and uses this information to generate rules that help detect malicious activity.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill operationalizing-misp-threat-feeds

Or download just the file:

curl -L https://raw.githubusercontent.com/mukul975/Anthropic-Cybersecurity-Skills/main/skills/operationalizing-misp-threat-feeds/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

Operationalizing MISP Threat Feeds

Note: This skill covers a defensive threat-intelligence platform. Handle ingested intelligence according to its Traffic Light Protocol (TLP) marking and your sharing agreements. Treat ingested IOCs as potentially sensitive.

Overview

MISP (Malware Information Sharing Platform) is the de-facto open-source threat-intelligence platform for storing, correlating, and sharing structured indicators (IOCs), events, galaxies (threat-actor/technique knowledge), and objects. Running a MISP instance is only the first step; the value comes from operationalizing it — curating high-quality feeds, suppressing false positives with warninglists, and pushing the resulting IOCs into detection tooling so intelligence actually drives blocking and alerting.

A feed in MISP is a remote source (another MISP, a CSV/freetext list, or a structured collection) that you enable and optionally cache. Caching pulls the feed's IOCs into the instance's Redis-backed cache so values can be correlated and looked up in real time (e.g., a SIEM asking "have you seen this domain?") without importing every event. Curation matters: enabling every public feed produces noise and false positives, so you select reputable feeds (CIRCL OSINT, abuse.ch, Feodo Tracker, etc.), apply warninglists (known-good ranges like RFC1918, Alexa/Tranco top sites, public DNS resolvers) to flag non-actionable indicators, and use taxonomies/tags (TLP, confidence) to scope what gets exported.

The detection-engineering payoff comes from MISP's export formats and PyMISP. MISP can render matching attributes directly as Suricata and Snort rules via the REST API, and PyMISP lets you script extraction of fresh IOCs to generate Sigma rules and Wazuh CDB lists / rules on a schedule. This skill walks the full lifecycle: feed enablement and caching, warninglist-based FP reduction, PyMISP-driven search, and automated generation of Suricata, Sigma, and Wazuh detections.

When to Use

  • Standing up or maturing a MISP instance into a feed that drives detection, not just a repository.
  • Curating and caching public/commercial threat feeds with quality controls.
  • Reducing IOC false positives with warninglists before they reach the SIEM/IDS.
  • Automating generation of Suricata/Sigma/Wazuh detections from MISP attributes.
  • Integrating MISP with a SOC so DNS/IP/hash lookups can be enriched against current intel.

Prerequisites

  • A running MISP instance (the maintained container images are the fastest path):
    git clone https://github.com/MISP/misp-docker.git
    cd misp-docker && cp template.env .env
    docker compose up -d
    # Web UI on https://localhost; default admin: admin@admin.test / admin
    
  • A MISP Auth Key (UI: Administration -> List Auth Keys -> Add).
  • PyMISP:
    pip install pymisp
    
  • Target detection tooling reachable: Suricata, a Sigma toolchain (pip install sigma-cli), and/or Wazuh manager.

Objectives

  • Enable and cache curated threat feeds in MISP.
  • Apply warninglists to suppress known-good / non-actionable indicators.
  • Authenticate and query MISP with PyMISP to pull fresh, scoped IOCs.
  • Export matching attributes as Suricata/Snort rules via the REST API.
  • Generate Sigma rules and Wazuh CDB lists from MISP attributes on a schedule.
  • Validate that generated detections load and fire in the target tooling.

MITRE ATT&CK Mapping

Technique ID Technique Name Relevance
T1589 Gather Victim Identity Information Feeds capture adversary reconnaissance indicators; operationalizing them detects/contextualizes such activity.
T1071.001 Application Layer Protocol: Web Protocols C2 domain/URL IOCs from feeds become Suricata/Sigma detections for malicious HTTP(S).
T1071.004 Application Layer Protocol: DNS Malicious-domain IOCs feed DNS-based detection (Wazuh/Suricata).
T1105 Ingress Tool Transfer File-hash IOCs from feeds detect known malicious payload delivery.

Workflow

1. Add and enable a feed

Register a reputable source and turn it on.

# add_feed.py (PyMISP) — register the CIRCL OSINT feed
from pymisp import PyMISP, MISPFeed
misp = PyMISP("https://localhost", "YOUR_AUTH_KEY", ssl=False)
feed = MISPFeed()
feed.name = "CIRCL OSINT Feed"
feed.provider = "CIRCL"
feed.url = "https://www.circl.lu/doc/misp/feed-osint"
feed.source_format = "misp"
feed.input_source = "network"

…
FAQ

What is MISP?

MISP is a platform for sharing and organizing cybersecurity threat information, like malicious IP addresses or suspicious files.

What are 'threat feeds'?

These are data sources that provide updated information about cyber threats, such as lists of malicious websites or dangerous IP addresses.

What are 'false positives'?

These are security alerts that indicate a threat but are not actually dangerous. The tool helps reduce these useless alerts.

Details

Original description by the author

Stand up MISP, enable and cache curated threat feeds (CIRCL, abuse.ch, Feodo Tracker), apply warninglists to suppress false positives, query indicators with PyMISP, and export attributes as auto-generated Suricata/Sigma/Wazuh detection rules. Use when maturing a MISP instance to actively drive detection, curating threat feeds with quality controls, or automating IOC-to-detection pipelines for the

repo: mukul975/Anthropic-Cybersecurity-Skills

Popularity

GitHub stars
35k
Ranking position
#6003
License
Apache-2.0
Updated
8/31/2026

Is this skill useful?

0

Sign in to vote.

Comments

  • …

More skills from this repository

Similar skills