bloodhound-query

bloodhound-query is a skill for Claude Code, Codex from MingyiSecLab/Mingyi-Atlas. It costs 32 tokens per session (1,073 once invoked), scanned A, a copy of bloodhound-query, Apache-2.0.

A BloodHound workflow for collecting and querying Active Directory data. BloodHound maps users, computers, groups, and permissions to show possible access paths.

In plain words
What is it for?
It covers collecting directory data, importing it into a knowledge graph, and running queries for owned accounts, administrator paths, roastable users, and replication rights.
Why use it?
It turns directory information into searchable relationships, making it easier to find shortest routes to administrator access and accounts with risky settings.

Skill for Claude CodeCodex

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

Good fit It covers collecting directory data, importing it into a knowledge graph, and running queries for owned accounts, administrator paths, roastable users, and replication rights.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/mingyiseclab/mingyi-atlas/bloodhound-query
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 MingyiSecLab/Mingyi-Atlas --skill bloodhound-query
Clone the repo
git clone --depth 1 https://github.com/MingyiSecLab/Mingyi-Atlas

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 bloodhound-query

README.md
[![agentmods](https://agentmods.dev/badge/skills/mingyiseclab/mingyi-atlas/bloodhound-query/github.svg)](https://agentmods.dev/skills/mingyiseclab/mingyi-atlas/bloodhound-query)
Your own site
<a href="https://agentmods.dev/skills/mingyiseclab/mingyi-atlas/bloodhound-query"><img src="https://agentmods.dev/badge/skills/mingyiseclab/mingyi-atlas/bloodhound-query/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 bloodhound-query

Your own site · 80×15
<a href="https://agentmods.dev/skills/mingyiseclab/mingyi-atlas/bloodhound-query"><img src="https://agentmods.dev/badge/skills/mingyiseclab/mingyi-atlas/bloodhound-query.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 32 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,073 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.
Origin 94% copy Near-identical to another mod 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 $0.00032 $0.01073
Opus 5 $0.00016 $0.00536
Sonnet 5 $0.00006 $0.00215
Haiku 4.5 $0.00003 $0.00107

Measured 11d ago against content hash b58b1ab6a670, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

bloodhound-query 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 11d ago.

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

This is a copy

94% identical to bloodhound-query — 6 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.

src/skills/standard/ad/bloodhound-query/SKILL.md · 83 lines

How it starts

The opening of the file, as written. The whole thing — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.

BloodHound Query Playbook

1. Collect

# Python collector (works from Linux attacker box)
bloodhound-python -u USER -p 'PASS' -d DOMAIN -c all --zip --dns-tcp \
  -ns DC_IP -o /workspace/bh.zip

# Or SharpHound from a Windows beachhead
# Invoke-BloodHound -CollectionMethod All -ZipFileName bh.zip

If bloodhound-python errors on TLS, add -gc gc.domain.local for the global catalog FQDN.

2. Ingest into Atlas KG

bh_ingest_zip("/workspace/bh.zip")

This populates User / Computer / Group / GPO / OU nodes with attribute properties (hasspn, dontreqpreauth, enabled, admincount, sidhistory).

3. Canonical Cypher queries

Run via bh_cypher("<query>") or post-process kg_query(kind=...):

Goal Cypher
Owned principals MATCH (u) WHERE u.owned=true RETURN u.name
Shortest path to DA MATCH p=shortestPath((u {owned:true})-[*1..]->(g:Group {name:'DOMAIN ADMINS@DOM'})) RETURN p
Kerberoastable users MATCH (u:User {hasspn:true, enabled:true}) RETURN u.name,u.spns
AS-REP roastable MATCH (u:User {dontreqpreauth:true, enabled:true}) RETURN u.name
DCSync candidates `MATCH (n)-[:GetChanges
Unconstrained delegation MATCH (c:Computer {unconstraineddelegation:true}) RETURN c.name
RBCD targets MATCH (n)-[:AddAllowedToAct]->(c:Computer) RETURN n.name,c.name
GenericAll on user MATCH (n)-[:GenericAll]->(u:User) WHERE NOT n=u RETURN n.name,u.name
ACL path to high-value `MATCH p=shortestPath((u {owned:true})-[:GenericAll
Sessions on DC MATCH (u:User)-[:HasSession]->(c:Computer) WHERE c.name CONTAINS 'DC' RETURN u.name,c.name
Computers w/ admin from owned MATCH (u {owned:true})-[:AdminTo*1..2]->(c:Computer) RETURN c.name
GPO abuse MATCH (n)-[:GpLink]->(:OU)-[:Contains*1..]->(c:Computer) WHERE n.name CONTAINS 'unsafe' RETURN n.name,c.name

4. Auto-prioritize attack paths

After ingest:

plan_attack_chains(promote=True)

This walks the graph from owned → high-value and surfaces:

  • Tier-0 reachability (DA / EA / krbtgt)
  • Tier-1 reachability (server admins, backup ops)
  • Lateral hops (admin → admin via AdminTo)

Read the full file on GitHub · 83 lines

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. 11d ago First seen · 83 lines · 32 tokens per session scan A b58b1ab6a670

Subscribe to this mod's changes

bloodhound-query is a skill published in the GitHub repository MingyiSecLab/Mingyi-Atlas (11 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 32 tokens to every session and 1,073 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to bloodhound-query, differing in 6 lines, and is treated as a copy.