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.
npx skills add andycungkrinx91/konoha --skill collecting-threat-intelligence-with-mispgit clone --depth 1 https://github.com/andycungkrinx91/konohaWrote 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.
[](https://agentmods.dev/skills/andycungkrinx91/konoha/collecting-threat-intelligence-with-misp)<a href="https://agentmods.dev/skills/andycungkrinx91/konoha/collecting-threat-intelligence-with-misp"><img src="https://agentmods.dev/badge/skills/andycungkrinx91/konoha/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.
<a href="https://agentmods.dev/skills/andycungkrinx91/konoha/collecting-threat-intelligence-with-misp"><img src="https://agentmods.dev/badge/skills/andycungkrinx91/konoha/collecting-threat-intelligence-with-misp.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00048 | $0.01562 |
| Opus 5.5 | $0.00019 | $0.00625 |
| Sonnet 5.5 | $0.00010 | $0.00312 |
| Haiku 4.5 | $0.00005 | $0.00156 |
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 today.
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.
This is a copy
100% identical to collecting-threat-intelligence-with-misp — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
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
pymisplibrary 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.
What ships with it
6 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.
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.
- today First seen · 194 lines · 48 tokens per session scan A 7513612da762
collecting-threat-intelligence-with-misp is a skill published in the GitHub repository andycungkrinx91/konoha (12 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 5.5. A static security scan graded it A with 0 findings. It is 100% identical to collecting-threat-intelligence-with-misp, differing in 0 lines, and is treated as a copy.
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