collecting-indicators-of-compromise

collecting-indicators-of-compromise is a skill for Claude Code, Codex from adriannoes/awesome-agentic-ai. It costs 88 tokens per session (2,784 once invoked), scanned A, original, MIT.

A guide for collecting indicators of compromise (IOCs), which are technical clues such as suspicious IP addresses, domains, files, or email artifacts linked to an attack. It organizes and shares these clues using threat-intelligence systems and the STIX/TAXII formats.

In plain words
What is it for?
Use it to gather IOCs from SIEM logs, endpoint data, memory, disks, network captures, and email. It helps enrich, score, manage, and share those indicators with security tools, partners, or law enforcement.
Why use it?
Incident evidence is easier to search, block, and share when attack clues are recorded in a consistent structure. This helps turn investigation findings into detections and intelligence for future incidents.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to gather IOCs from SIEM logs, endpoint data, memory, disks, network captures, and email. It helps enrich, score, manage, and share those indicators with security tools, partners, or law enforcement.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/adriannoes/awesome-agentic-ai/collecting-indicators-of-compromise
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 adriannoes/awesome-agentic-ai --skill collecting-indicators-of-compromise
Clone the repo
git clone --depth 1 https://github.com/adriannoes/awesome-agentic-ai

Made for: Claude Code, Codex.

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-indicators-of-compromise

README.md
[![agentmods](https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/collecting-indicators-of-compromise/github.svg)](https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/collecting-indicators-of-compromise)
Your own site
<a href="https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/collecting-indicators-of-compromise"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/collecting-indicators-of-compromise/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-indicators-of-compromise

Your own site · 80×15
<a href="https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/collecting-indicators-of-compromise"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/collecting-indicators-of-compromise.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 88 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,784 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 pass 7 Sept 2026
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 $0.00088 $0.02784
Opus 5 $0.00044 $0.01392
Sonnet 5 $0.00018 $0.00557
Haiku 4.5 $0.00009 $0.00278

Measured 12d ago against content hash c6b4fefdd2bd, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

collecting-indicators-of-compromise 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 12d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/agent.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

3 near-identical copies found in the catalogue:

cursor-claude-codex/skills/anthropic-cybersecurity-skills/skills/collecting-indicators-of-compromise/SKILL.md · 273 lines

How it starts

The opening of the file, as written. The whole thing — 273 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Collecting Indicators of Compromise

When to Use

  • During active incident response to identify and block adversary infrastructure
  • Post-incident to document all observed adversary artifacts for future detection
  • When sharing threat intelligence with ISACs, sector partners, or law enforcement
  • When building detection rules in SIEM, EDR, or network security tools
  • When enriching IOCs with threat intelligence context for risk scoring

Do not use for behavioral TTP analysis without accompanying technical indicators; use MITRE ATT&CK mapping for behavioral characterization.

Prerequisites

  • Access to incident evidence sources: SIEM logs, EDR telemetry, memory dumps, disk images, network captures
  • Threat intelligence platform (MISP, OpenCTI, ThreatConnect) for IOC management and sharing
  • IOC enrichment tools: VirusTotal, OTX (AlienVault Open Threat Exchange), Shodan, DomainTools
  • STIX 2.1 knowledge for structured IOC representation
  • Sharing agreements with relevant ISACs (FS-ISAC, H-ISAC, IT-ISAC) or sector partners

Workflow

Step 1: Identify IOC Categories

Collect indicators across all categories from incident evidence:

Network Indicators:

  • IP addresses (C2 servers, staging servers, exfiltration destinations)
  • Domain names (C2 domains, phishing domains, DGA domains)
  • URLs (malware download, C2 check-in, exfiltration endpoints)
  • JA3/JA3S hashes (TLS client/server fingerprints)
  • User-Agent strings (custom or unusual HTTP headers)
  • DNS query patterns (tunneling signatures, DGA patterns)

Host Indicators:

  • File hashes (MD5, SHA-1, SHA-256 of malware, tools, scripts)
  • File paths (known malware installation directories)
  • Registry keys (persistence mechanisms, configuration storage)
  • Scheduled tasks and service names (persistence)
  • Mutex/event names (malware instance synchronization)
  • Named pipes (C2 communication channels, e.g., Cobalt Strike)

Email Indicators:

  • Sender addresses and domains (spoofed or attacker-controlled)
  • Subject lines and body content patterns
  • Attachment names and hashes
  • Embedded URLs
  • Email header anomalies (SPF/DKIM/DMARC failures)

Read the full file on GitHub · 273 lines

Files

What ships with it

3 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. 12d ago First seen · 273 lines · 88 tokens per session scan A c6b4fefdd2bd

Subscribe to this mod's changes

collecting-indicators-of-compromise is a skill published in the GitHub repository adriannoes/awesome-agentic-ai (57 stars, last pushed 14d ago), licensed MIT. It adds 88 tokens to every session and 2,784 once invoked, about $0.0004 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 2026-08-30.

Related

Other skills, from other repositories

collecting-indicators-of-compromise

Systematically collects, categorizes, and distributes indicators of compromise (IOCs) during and after security incidents to enable detection, blocking, and threat intelligence sharing. Covers network, host, email, and behavioral indicators using STIX/TAXII formats and threat intelligence platforms. Activates for…

26zl/cybersec-toolkit · 88 tokens

collecting-indicators-of-compromise

Systematically collects, categorizes, and distributes indicators of compromise (IOCs) during and after security incidents to enable detection, blocking, and threat intelligence sharing. Covers network, host, email, and behavioral indicators using STIX/TAXII formats and threat intelligence platforms. Activates for…

autohandai/community-skills · 88 tokens

collecting-indicators-of-compromise

Systematically collects, categorizes, and distributes indicators of compromise (IOCs) during and after security incidents to enable detection, blocking, and threat intelligence sharing. Covers network, host, email, and behavioral indicators using STIX/TAXII formats and threat intelligence platforms. Activates for…

Youngmaidainon/Agent-Level-Up · 88 tokens

collecting-indicators-of-compromise

Systematically collects, categorizes, and distributes indicators of compromise (IOCs) during and after security incidents to enable detection, blocking, and threat intelligence sharing. Covers network, host, email, and behavioral indicators using STIX/TAXII formats and threat intelligence platforms. Activates for…

RobotFlow-Labs/skills-repo · 88 tokens

importing-a-codebase

Use when the repo holds real source code but no specs: the existing-codebase branch of setting-up-a-project, normally reached via that dispatcher, directly only when the situation is unmistakable. Not for empty workspaces (starting-a-new-project) or feature work in a specced project (brainstorming).

JetBrains/thinkrail · 69 tokens

starting-a-new-project

Use when the workspace is empty — no code yet — and the user brings a raw idea: the brand-new branch of setting-up-a-project, normally reached via that dispatcher, directly only when the situation is unmistakable. Not for features in an existing project — use brainstorming instead.

JetBrains/thinkrail · 61 tokens