← LeaderboardThe Skill Leaderboard

exploiting-active-directory-with-bloodhound

BloodHound is a graph-based Active Directory reconnaissance tool that uses graph theory to reveal hidden and unintended relationships within AD environments. Red teams use BloodHound to identify attac

Published by mukul975 ↗mukul975/Anthropic-Cybersecurity-Skills

Try your first task

exploiting-active-directory-with-bloodhound

Start a fresh conversation. Replace the highlighted placeholders.

Use exploiting-active-directory-with-bloodhound to analyze the supplied fresh BloodHound graph from an authorized isolated lab for [written owner scope and permitted domain/account coverage], using its recorded owned-principal markings and provenance. Return evidenced shortest paths to Domain Admins/from owned principals; relevant Kerberoastable, AS-REP-roastable, ACL, group, delegation, GPO, unsupported-OS, and DCSync-rights graph findings; coverage limitations; and a prioritized plan for later authorized validation. Do not collect data, alter the graph, execute or plan exploitation steps, or treat graph edges as proven compromise. Provide [graph export or query/screenshot evidence] and [collection date and domain-coverage record].

Required inputs

  • [written owner scope and permitted domain/account coverage]
  • [graph export or query/screenshot evidence]
  • [collection date and domain-coverage record]

User-approved starter prompt based on a pinned source version; check current skill requirements before running. Task evidence ↗

SKILL.md

name: exploiting-active-directory-with-bloodhounddescription: BloodHound is a graph-based Active Directory reconnaissance tool that  uses graph theory to reveal hidden and unintended relationships within AD environments.  Red teams use BloodHound to identify attacdomain: cybersecuritysubdomain: red-teamingtags: - red-team- adversary-simulation- mitre-attack- exploitation- post-exploitation- active-directory- bloodhoundversion: '1.0'author: mahipallicense: Apache-2.0d3fend_techniques: - Restore Access- Password Authentication- Biometric Authentication- Strong Password Policy- Restore User Account Accessnist_csf: - ID.RA-01- GV.OV-02- DE.AE-07mitre_attack: - T1595- T1190- T1059- T1078- T1592

Exploiting Active Directory with BloodHound

Legal Notice: This skill is for authorized security testing and educational purposes only. Unauthorized use against systems you do not own or have written permission to test is illegal and may violate computer fraud laws.

Overview

BloodHound is a graph-based Active Directory reconnaissance tool that uses graph theory to reveal hidden and unintended relationships within AD environments. Red teams use BloodHound to identify attack paths from compromised accounts to high-value targets such as Domain Admins, identifying privilege escalation chains that would be nearly impossible to find manually. SharpHound is the official data collector that gathers AD objects, relationships, ACLs, sessions, and group memberships.

When to Use

  • When performing authorized security testing that involves exploiting active directory with bloodhound
  • When analyzing malware samples or attack artifacts in a controlled environment
  • When conducting red team exercises or penetration testing engagements
  • When building detection capabilities based on offensive technique understanding

Prerequisites

  • Familiarity with red teaming concepts and tools
  • Access to a test or lab environment for safe execution
  • Python 3.8+ with required dependencies installed
  • Appropriate authorization for any testing activities

Objectives

  • Collect Active Directory relationship data using SharpHound or BloodHound.py
  • Visualize attack paths from compromised accounts to Domain Admin
  • Identify misconfigured ACLs, group memberships, and delegation settings
  • Discover shortest attack paths to high-value targets
  • Map Kerberos delegation configurations for abuse
  • Document all identified privilege escalation chains

MITRE ATT&CK Mapping

  • T1087.002 - Account Discovery: Domain Account
  • T1069.002 - Permission Groups Discovery: Domain Groups
  • T1482 - Domain Trust Discovery
  • T1615 - Group Policy Discovery
  • T1018 - Remote System Discovery
  • T1033 - System Owner/User Discovery
  • T1016 - System Network Configuration Discovery

Workflow

Phase 1: Data Collection with SharpHound

  1. Transfer SharpHound collector to compromised host
  2. Execute collection with appropriate method (All, DCOnly, Session, LoggedOn)
  3. Collect from all reachable domains if multi-domain environment
  4. Exfiltrate ZIP data files to analysis workstation
  5. Import data into BloodHound CE or Legacy

Phase 2: Attack Path Analysis

  1. Mark owned principals (compromised accounts)
  2. Query shortest path to Domain Admins
  3. Identify Kerberoastable accounts with admin privileges
  4. Find AS-REP Roastable accounts
  5. Analyze ACL-based attack paths (GenericAll, GenericWrite, WriteDACL, ForceChangePassword)
  6. Review GPO abuse opportunities

Phase 3: Exploitation Planning

  1. Prioritize attack paths by complexity and stealth
  2. Identify required tools for each step in the chain
  3. Plan OPSEC considerations for each technique
  4. Execute identified attack chain
  5. Document evidence at each step

Tools and Resources

ToolPurposePlatform
BloodHound CEGraph visualization and analysisWeb-based
SharpHoundAD data collection (.NET)Windows
BloodHound.pyAD data collection (Python)Linux/Windows
Cypher queriesCustom graph queriesNeo4j/BloodHound
PlumHoundAutomated BloodHound reportingPython
Max (BloodHound)BloodHound automationPython

Key BloodHound Queries

QueryPurpose
Shortest Path to Domain AdminsFind fastest route to DA
Find Kerberoastable Users with Path to DASPN accounts leading to DA
Find AS-REP Roastable UsersAccounts without pre-auth
Shortest Path from Owned PrincipalsPaths from compromised accounts
Find Computers with Unsupported OSLegacy systems for exploitation
Find Users with DCSync RightsAccounts that can replicate AD
Find GPOs that Modify Local Group MembershipGPO-based privilege escalation

Validation Criteria

  • SharpHound data collected from all domains
  • Attack paths identified from owned accounts to DA
  • ACL-based attack paths documented
  • Kerberoastable and AS-REP roastable accounts identified
  • Exploitation plan created with prioritized paths
  • Evidence screenshots captured for report