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Hunt Ioc

Community
dandye
hunt-ioc

Hunt for specific IOCs across your environment. Use when you have a list of IPs, domains, hashes, or URLs from threat intel and want to check if they appear in your SIEM. Systematic searching with enrichment and documentation.

Overview

Publisherdandye
Repositoryai-runbooks
Skill namehunt-ioc
Stars
126
Forks
34
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by dandye on GitHub. Read the source before you install it.

Installation

Install the Hunt Ioc AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/dandye/ai-runbooks.git /tmp/ai-runbooks
mkdir -p .claude/skills
cp -r /tmp/ai-runbooks/skills/hunt-ioc .claude/skills/hunt-ioc
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Hunt Ioc in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Hunt Ioc on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Hunt Ioc is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

IOC Threat Hunt Skill

Proactively hunt for specific Indicators of Compromise (IOCs) across the environment based on threat intelligence feeds, recent incidents, or emerging threats.

Inputs

  • IOC_LIST - Comma-separated list of IOC values to hunt
  • IOC_TYPES - Corresponding types (e.g., "IP Address, Domain, File Hash")
  • HUNT_TIMEFRAME_HOURS - Lookback period (default: 96)
  • (Optional) HUNT_CASE_ID - SOAR case for tracking
  • (Optional) REASON_FOR_HUNT - Why these IOCs are being hunted

Workflow

Step 1: Parse and Validate IOCs

Parse IOC_LIST and IOC_TYPES into structured list. Validate IOC formats (IP regex, hash length, etc.).

Step 2: Initial IOC Match Check

secops-mcp.get_ioc_matches(hours_back=HUNT_TIMEFRAME_HOURS)

Check if any IOCs appear in integrated threat feeds.

Step 3: Iterative SIEM Search

For each IOC, construct appropriate UDM query:

IP Address:

udm
(principal.ip = "IOC" OR target.ip = "IOC" OR network.ip = "IOC")

Domain:

udm
(principal.hostname = "IOC" OR target.hostname = "IOC" OR network.dns.questions.name = "IOC")

File Hash:

udm
(target.file.sha256 = "IOC" OR target.file.md5 = "IOC" OR target.file.sha1 = "IOC")

URL:

udm
target.url = "IOC"

Execute each search:

secops-mcp.search_security_events(text=query, hours_back=HUNT_TIMEFRAME_HOURS)

Step 4: Analyze Results

For each search result:

  • Identify affected hosts, users, processes
  • Note event types (login, network connection, file execution)
  • Assess if activity is suspicious or expected

Step 5: Enrich Hits

If hits found for an IOC:

Use /enrich-ioc for the IOC itself.

For involved entities (hosts, users):

secops-mcp.lookup_entity(entity_value=ENTITY)

Step 6: Document Hunt

Use /document-in-case (if HUNT_CASE_ID provided):

IOC Hunt Summary:
- IOCs Hunted: [list]
- Timeframe: [hours]
- Queries Used: [list with results summary]
- IOCs with Hits: [list with details]
- IOCs with No Hits: [list - confirms environment is clean]
- Enrichment: [for hits]
- Recommendations: [next steps]

Step 7: Escalate or Conclude

Confirmed malicious activity: → Create/update incident case → Trigger appropriate response runbook

No significant findings: → Document hunt completion → Note clean IOCs for future reference

Output Summary Template

markdown
# IOC Hunt Results

**Hunt Date:** [timestamp]
**Timeframe:** Last [X] hours
**Reason:** [REASON_FOR_HUNT]

## IOCs Searched
| IOC | Type | Result | Notes |
|-----|------|--------|-------|
| 198.51.100.10 | IP | NO HITS | Clean |
| evil.com | Domain | 3 HITS | DNS lookups from HOST1 |

## Hits Analysis
[Details for each IOC with hits]

## Recommendations
[Actions to take]

Required Outputs

After completing this skill, you MUST report these outputs:

OutputDescription
MATCHESIOCs found in SIEM (list of IOCs with hits)
MATCH_CONTEXTContext for each match (events, assets, users affected)
MATCHES_FOUNDBoolean: true if any IOCs found in environment, false otherwise

Critical Requirements

  • Search ALL provided IOCs (don't skip any)
  • Use correct timeframe (not 1 hour instead of 72)
  • Document negative results (confirms environment is clean)
  • Don't declare "clean" if there were obvious hits

Frequently asked questions

What does the Hunt Ioc AI skill do?

Hunt for specific IOCs across your environment. Use when you have a list of IPs, domains, hashes, or URLs from threat intel and want to check if they appear in your SIEM. Systematic searching with enrichment and documentation.

Why use Hunt Ioc on TypingMind?

Because you install it once and use it with any model. Hunt Ioc is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Hunt Ioc in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/dandye/ai-runbooks/tree/main/skills/hunt-ioc. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Hunt Ioc?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Hunt Ioc?

As many as you like. As long as a model supports skills, you can use Hunt Ioc with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Hunt Ioc AI skill free?

Yes. It is published on GitHub by dandye under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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