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Bloodhound Analysis

Organization
SpecterOps
bloodhound-analysis

Use as the default router for generic BloodHound asks: check the BloodHound connection, verify MCP health, analyze BloodHound data, find or explain a path, inspect shortest paths, find a path to Domain Admin or Tier Zero, show exposure, run a BloodHound query, or triage graph results when the domain is not yet clear. Use BloodHound MCP for authorized BloodHound CE graph analysis, path triage, object lookup, data-quality checks, AD/ADCS/Azure/OpenGraph exposure mapping, and report-ready remediation output. Do not use for unrelated network recon or for domain-specific work that is clearly AzureHound, OpenHound, OpenGraph schema design, or explicit Cypher authoring/review.

Overview

PublisherSpecterOps
Repositoryskills
Skill namebloodhound-analysis
Stars
706
Forks
80
Bundled files
4
LicenseMIT
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.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Bloodhound Analysis 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.
    https://github.com/SpecterOps/skills/tree/main/plugins/bloodhound/skills/bloodhound-analysis
  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/SpecterOps/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/plugins/bloodhound/skills/bloodhound-analysis .claude/skills/bloodhound-analysis
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Bloodhound Analysis 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 Bloodhound Analysis 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 Bloodhound Analysis 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.

BloodHound Analysis

When to use

Use this skill as the MCP-aware router for authorized BloodHound analysis. It is optimized for repeatable graph workflows: dataset checks, object lookup, path analysis, query design, ADCS/Azure/OpenGraph code-review, and report-ready output.

Direct triggers

Use this skill when the task mentions any of the following:

  • check the BloodHound connection
  • verify BloodHound MCP
  • is BloodHound up
  • analyze BloodHound data
  • find a path
  • shortest path
  • path to Domain Admin
  • path to DA
  • path to Tier Zero
  • show BloodHound exposure
  • inspect this BloodHound result
  • run a BloodHound query

Route to instead

  • Use $bloodhound-ad-analysis when the user clearly means AD/ADCS pathing such as DCSync, ESC paths, Domain Admins, trusts, sessions, or GPO/ACL abuse.
  • Use $bloodhound-query when the user explicitly wants Cypher written, reviewed, optimized, explained, or adapted from saved queries.
  • Use $azurehound-analysis, $openhound-github, $openhound-jamf, or $openhound-okta when the graph domain is explicit.
  • Use $bloodhound-opengraph when the task is about custom node schemas, ingestors, or graph-model extension work.

Required context

  • Confirm the assessment or lab is authorized and in scope.
  • Confirm bloodhound_mcp is configured and visible in /mcp before relying on live MCP tools.
  • If MCP is unavailable, produce a query/workflow plan instead of claiming live graph facts. The repo includes optional MCP packaging for target environments, but repository work should not install or sync it into the current Codex config unless explicitly requested.
  • Route domain-specific query work to $bloodhound-query, $bloodhound-ad-analysis, $azurehound-analysis, $openhound-github, $openhound-jamf, or $openhound-okta as appropriate.

Default workflow

  1. Check data quality first
    • Start with data_quality(info_type="stats") or data_quality(info_type="platform_list").
    • Call out collection gaps before drawing conclusions.
  2. Find the right graph objects
    • Use domain_info(info_type="list") and domain_info(info_type="search", query=...).
    • Capture object IDs/names for every critical claim.
  3. Use the right composite tool before custom Cypher
    • Prefer user_info, group_info, computer_info, ou_info, gpo_info, graph_analysis, and adcs_info for common questions.
    • Use cypher_query(info_type="run", query=...) only when the composite tools cannot answer cleanly.
  4. Load references before writing attack queries
    • For custom query work, read ../../references/docs/bloodhound-query-methodology.md.
    • For attack scenarios, use the relevant domain index in ../../references/query-indexes/ and adapt a known-good snapshot pattern.
    • For OpenGraph collector, SCIM, or hybrid identity work, also read ../../references/docs/collector-source-index.md, ../../references/docs/scim-methodology.md, ../../references/docs/opengraph-extension-management.md, and ../../references/examples/ as relevant.
    • If MCP exposes live BloodHound resources such as bloodhound://cypher/reference, use them as live supplements, not replacements for the repo-packaged guidance.
  5. Produce assessment-ready output
    • Separate confirmed graph facts from inferred risk.
    • Include affected entities, edge sequence, confidence, data-quality caveats, and remediation.

Safety and quality rules

  • Do not perform write actions such as custom node changes, asset group changes, saved query edits, or file uploads without explicit user confirmation.
  • Use pagination (limit, skip) for broad queries.
  • Never label a user, computer, or path as low risk without checking memberships, enabled/admincount status, and relevant edge context.
  • Use uppercase names with domain suffixes when filtering BloodHound names, and lowercase property names such as hasspn, enabled, and admincount.
  • Prefer remediation-focused wording over exploitation instructions unless the user explicitly asks for operator guidance in an authorized assessment.

References

  • Read references/bloodhound-mcp-tools.md for the expected MCP tool and resource surface.
  • Read ../../references/docs/source-index.md for official docs, collector references, examples, and vendored query indexes.
  • Use $bloodhound-query for cross-domain query authoring/review.
  • Use $bloodhound-ad-analysis, $azurehound-analysis, $openhound-github, $openhound-jamf, or $openhound-okta for domain-specific saved-query adaptation.
  • Use $bloodhound-opengraph for custom node schema, OpenGraph modeling, and ingestor extension work.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Bloodhound Analysis AI skill do?

Use as the default router for generic BloodHound asks: check the BloodHound connection, verify MCP health, analyze BloodHound data, find or explain a path, inspect shortest paths, find a path to Domain Admin or Tier Zero, show exposure, run a BloodHound query, or triage graph results when the domain is not yet clear. Use BloodHound MCP for authorized BloodHound CE graph analysis, path triage, object lookup, data-quality checks, AD/ADCS/Azure/OpenGraph exposure mapping, and report-ready remediation output. Do not use for unrelated network recon or for domain-specific work that is clearly Azu...

Why use Bloodhound Analysis on TypingMind?

Because you install it once and use it with any model. Bloodhound Analysis 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 Bloodhound Analysis in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/SpecterOps/skills/tree/main/plugins/bloodhound/skills/bloodhound-analysis. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Bloodhound Analysis?

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 Bloodhound Analysis?

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

Is the Bloodhound Analysis AI skill free?

Yes. It is published on GitHub by SpecterOps under the MIT 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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