collecting-indicators-of-compromise
by mukul975collecting-indicators-of-compromise skill for extracting, enriching, scoring, and exporting IOCs from incident evidence. Use it for Security Audit workflows, threat intel sharing, and STIX 2.1 output when you need a practical collecting-indicators-of-compromise guide instead of a generic incident-response prompt.
This skill scores 83/100, which makes it a solid listing candidate for directory users. It provides a concrete IOC collection workflow with clear triggers, executable CLI examples, enrichment steps, and STIX 2.1 export, so an agent can do materially more than a generic prompt with less guesswork.
- Clear activation language for IOC collection, extraction, sharing, enrichment, and STIX export
- Operational workflow is backed by a real Python script plus API reference with CLI examples and key functions
- Good install-decision value: scope, prerequisites, constraints, and external enrichment sources are documented
- Requires external APIs and inputs (for example VirusTotal, MalwareBazaar, AbuseIPDB), so it is not fully self-contained
- The excerpted documentation hints at a richer workflow, but some edge-case handling and end-to-end examples are not fully visible in the repository evidence
Overview of collecting-indicators-of-compromise skill
The collecting-indicators-of-compromise skill helps you extract, organize, enrich, and export indicators of compromise from incident evidence. It is best for security analysts, incident responders, and threat intel teams who need a repeatable way to turn messy evidence into usable IOCs for blocking, detection, and sharing.
What makes the collecting-indicators-of-compromise skill useful is that it is not just a generic prompt about incident response. It is oriented around practical IOC handling: regex-based extraction, enrichment with threat intel sources, confidence scoring, and STIX 2.1 export. That makes it a strong fit for collecting-indicators-of-compromise for Security Audit workflows where you need traceable artifacts, not just a narrative summary.
Best fit for IOC-heavy workflows
Use this skill when your source material includes logs, reports, tickets, email, host artifacts, or analyst notes and you want to pull out IPs, domains, URLs, hashes, and related enrichment context. It is especially relevant when you need to normalize findings into a shareable format for downstream tools like SIEM, EDR, MISP, or OpenCTI.
What it is not for
This is not the right tool for pure behavioral analysis without technical indicators. If your task is mostly TTP mapping, phishing triage without artifacts, or general incident writeups, a broader prompt will often be better than this collecting-indicators-of-compromise skill.
Key differentiators
The main value is the workflow: extract first, enrich second, score third, export last. That sequence reduces the common failure mode of sharing raw indicators without context. It also helps you decide whether an IOC is actionable enough to block or only suitable for watchlisting.
How to Use collecting-indicators-of-compromise skill
Install and first files to read
Install the collecting-indicators-of-compromise skill with:
npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill collecting-indicators-of-compromise
After install, read SKILL.md first, then references/api-reference.md, then scripts/agent.py. Those three files tell you the intended input shape, supported enrichment path, and export behavior faster than browsing the full repo. If you only skim one support file, make it the API reference because it shows the real CLI and function flow.
How to frame a good request
The collecting-indicators-of-compromise usage pattern works best when you provide source material plus the desired output format. A weak request is: “Find IOCs.” A stronger request is: “Extract IPv4s, domains, SHA-256s, and URLs from this incident report, enrich anything reputation-related with VirusTotal, and return a STIX-ready IOC list with confidence notes.”
Good input usually includes:
- the raw text, log excerpt, or file contents
- the source type and date range
- whether enrichment is allowed
- the target output, such as JSON, STIX bundle, or analyst table
- any false-positive context, like internal domains or expected scanners
Practical workflow that matches the skill
A reliable collecting-indicators-of-compromise guide is:
- extract indicators from the source material
- deduplicate obvious repeats
- enrich only the indicators that matter most
- score confidence based on evidence quality
- export in the format your workflow actually consumes
That order matters. If you enrich too early, you waste time on duplicate or low-value artifacts. If you export too soon, you lose analyst context that helps downstream teams trust the IOC.
Tips that improve output quality
State whether you want only observable indicators or also surrounding context. If you are doing a Security Audit, say whether the goal is detection engineering, threat sharing, or containment. Also specify exclusions up front, such as internal IP ranges, sandbox URLs, or known corporate domains, so the output does not get polluted with expected noise.
collecting-indicators-of-compromise skill FAQ
Is this better than a generic prompt?
Usually yes, if your task is specifically IOC collection. The collecting-indicators-of-compromise skill bakes in a workflow for extraction, enrichment, and STIX-oriented handling, which is more reliable than asking a model to “find indicators” from scratch.
What does the skill actually support?
The repository evidence points to extraction of common IOC types such as IPv4s, domains, hashes, and URLs, plus enrichment paths that use threat intelligence services and STIX 2.1 export. If you need email header parsing, registry artifact analysis, or deep malware reversing, this skill is not the whole answer.
Is collecting-indicators-of-compromise beginner-friendly?
Yes, if you already know you need indicators from incident material. The skill is easier to use than a blank prompt because it gives you a structured path. The main beginner risk is under-specifying the source data, which leads to incomplete or noisy results.
When should I not use it?
Do not use collecting-indicators-of-compromise when you only need a narrative incident summary, high-level ATT&CK mapping, or broad threat hunting ideas without concrete observables. In those cases, you will get better results from a different cybersecurity skill or a purpose-built prompt.
How to Improve collecting-indicators-of-compromise skill
Give the extraction target, not just the artifact
The best way to improve collecting-indicators-of-compromise usage is to tell it what counts as an IOC in your context. For example: “Extract only external IPs, domains, file hashes, and URLs; ignore RFC1918 addresses and vendor telemetry URLs.” That small constraint prevents noisy output and makes the result more actionable.
Add enrichment priorities
If you need enrichment, specify which indicators matter most. For example, ask to enrich only high-risk IPs and file hashes, not every domain mention. This keeps the collecting-indicators-of-compromise skill focused and avoids wasting time on low-value reputation checks.
Ask for the format you will reuse
Tell the skill whether you want a deduplicated table, STIX bundle, or analyst notes. If your next step is a SIEM rule or ticket update, ask for fields like indicator, type, source context, confidence, and recommended action. That makes the output easier to operationalize after the first pass.
Iterate by tightening false-positive rules
If the first output includes internal assets, benign CDN hosts, or scanner traffic, refine the prompt with exclusion lists and source context. The fastest way to improve a collecting-indicators-of-compromise guide outcome is to tell it what not to treat as suspicious, then rerun on the same evidence.