collecting-threat-intelligence-with-misp

collecting-threat-intelligence-with-misp is a skill for Claude Code from 26zl/cybersec-toolkit. It costs 48 tokens per session (1,562 once invoked), scanned A, original, MIT.

A guide to using MISP, an open-source platform for collecting, storing, comparing, and sharing threat intelligence. Threat intelligence includes information about malicious activity, such as suspicious domains, IP addresses, and file hashes.

In plain words
What is it for?
Use it to deploy MISP, configure feeds, collect indicators through its Python API, and build automated threat-intelligence workflows.
Why use it?
It helps security teams organize information from many feeds and connect related indicators instead of managing them in disconnected files.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

Part of the cybersec-toolkit plugin — 197 skills, 2 hooks, 1 MCP server shipped together

Good fit Use it to deploy MISP, configure feeds, collect indicators through its Python API, and build automated threat-intelligence workflows.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/26zl/cybersec-toolkit/collecting-threat-intelligence-with-misp
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add 26zl/cybersec-toolkit --skill collecting-threat-intelligence-with-misp
Clone the repo
git clone --depth 1 https://github.com/26zl/cybersec-toolkit

Made for: Claude Code.

Or install cybersec-toolkit, the plugin that ships this one along with the rest of its 197 skills, 2 hooks, 1 MCP server.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for collecting-threat-intelligence-with-misp

README.md
[![agentmods](https://agentmods.dev/badge/skills/26zl/cybersec-toolkit/collecting-threat-intelligence-with-misp/github.svg)](https://agentmods.dev/skills/26zl/cybersec-toolkit/collecting-threat-intelligence-with-misp)
Your own site
<a href="https://agentmods.dev/skills/26zl/cybersec-toolkit/collecting-threat-intelligence-with-misp"><img src="https://agentmods.dev/badge/skills/26zl/cybersec-toolkit/collecting-threat-intelligence-with-misp/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for collecting-threat-intelligence-with-misp

Your own site · 80×15
<a href="https://agentmods.dev/skills/26zl/cybersec-toolkit/collecting-threat-intelligence-with-misp"><img src="https://agentmods.dev/badge/skills/26zl/cybersec-toolkit/collecting-threat-intelligence-with-misp.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 48 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,562 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 2 findings, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Privilege Escalation · line 78
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
  • high Privilege Escalation · line 79
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00048 $0.01562
Opus 5 $0.00024 $0.00781
Sonnet 5 $0.00010 $0.00312
Haiku 4.5 $0.00005 $0.00156

Measured 8d ago against content hash 7513612da762, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

collecting-threat-intelligence-with-misp scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/agent.py, scripts/process.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

.claude/skills/collecting-threat-intelligence-with-misp/SKILL.md · 194 lines

How it starts

The opening of the file, as written. The whole thing — 194 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Collecting Threat Intelligence with MISP

Overview

MISP (Malware Information Sharing Platform) is an open-source threat intelligence platform for gathering, sharing, storing, and correlating Indicators of Compromise (IOCs) of targeted attacks, threat intelligence, financial fraud information, vulnerability information, or counter-terrorism information. This skill covers deploying MISP, configuring threat feeds, using the PyMISP API for programmatic access, and building automated collection pipelines that aggregate IOCs from multiple community and commercial sources.

When to Use

  • When managing security operations that require collecting threat intelligence with misp
  • When improving security program maturity and operational processes
  • When establishing standardized procedures for security team workflows
  • When integrating threat intelligence or vulnerability data into operations

Prerequisites

  • Python 3.9+ with pymisp library installed
  • Docker and Docker Compose for MISP deployment
  • Understanding of STIX 2.1 and TAXII 2.1 protocols
  • Familiarity with IOC types: hashes, IP addresses, domains, URLs, email addresses
  • Network access to MISP community feeds (circl.lu, botvrij.eu)

Key Concepts

MISP Architecture

MISP operates on an event-based model where threat intelligence is organized into events containing attributes (IOCs), objects (structured groupings of attributes), galaxies (threat actor/malware clusters linked to MITRE ATT&CK), and tags for classification. Synchronization between MISP instances uses a pull/push model over HTTPS with API key authentication.

Feed Types

  • MISP Feeds: Native JSON/CSV feeds from MISP community (CIRCL OSINT, botvrij.eu)
  • Freetext Feeds: Unstructured text feeds parsed for IOCs (abuse.ch, Feodo Tracker)
  • TAXII Feeds: STIX/TAXII 2.1 compatible feeds from commercial and government sources
  • CSV Feeds: Structured CSV feeds with configurable column mapping

PyMISP API

PyMISP is the official Python library to access MISP platforms via their REST API. It supports fetching events, adding/updating events and attributes, uploading samples, and searching across the entire MISP dataset. Authentication uses an API key passed in the Authorization header.

Read the full file on GitHub · 194 lines

Files

What ships with it

7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 194 lines · 48 tokens per session scan A 7513612da762

Subscribe to this mod's changes

collecting-threat-intelligence-with-misp is a skill published in the GitHub repository 26zl/cybersec-toolkit (54 stars, last pushed today), licensed MIT. It adds 48 tokens to every session and 1,562 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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