/autobloody

Tool to automatically exploit Active Directory privilege escalation paths shown by BloodHound

Primary LanguagePythonMIT LicenseMIT

bloodyAD logo autobloody

autobloody is a tool to automatically exploit Active Directory privilege escalation paths shown by BloodHound.

Description

This tool automates the AD privesc between two AD objects, the source (the one we own) and the target (the one we want) if a privesc path exists in BloodHound database. The automation is composed of two steps:

  • Finding the optimal path for privesc using bloodhound data and neo4j queries.
  • Execute the path found using bloodyAD package

Because autobloody relies on bloodyAD, it supports authentication using cleartext passwords, pass-the-hash, pass-the-ticket or certificates and binds to LDAP services of a domain controller to perform AD privesc.

Installation

First if you run it on Linux, you must have libkrb5-dev installed on your OS in order for kerberos to work:

# Debian/Ubuntu/Kali
apt-get install libkrb5-dev

# Centos/RHEL
yum install krb5-devel

# Fedora
dnf install krb5-devel

# Arch Linux
pacman -S krb5

A python package is available:

pip install autobloody

Or you can clone the repo:

git clone --depth 1 https://github.com/CravateRouge/autobloody
pip install .

Dependencies

  • bloodyAD
  • Neo4j python driver
  • Neo4j with the GDS library
  • BloodHound
  • Python 3
  • Gssapi (linux) or Winkerberos (Windows)

How to use it

First data must be imported into BloodHound (e.g using SharpHound or BloodHound.py) and Neo4j must be running.

⚠️ -ds and -dt values are case sensitive

Simple usage:

autobloody -u john.doe -p 'Password123!' --host 192.168.10.2 -dp 'neo4jP@ss' -ds 'JOHN.DOE@BLOODY.LOCAL' -dt 'BLOODY.LOCAL'

Full help:

[bloodyAD]$ ./autobloody.py -h
usage: autobloody.py [-h] [--dburi DBURI] [-du DBUSER] -dp DBPASSWORD -ds DBSOURCE -dt DBTARGET [-d DOMAIN] [-u USERNAME] [-p PASSWORD] [-k] [-c CERTIFICATE] [-s] --host HOST

AD Privesc Automation

options:
  -h, --help            show this help message and exit
  --dburi DBURI         The host neo4j is running on (default is "bolt://localhost:7687")
  -du DBUSER, --dbuser DBUSER
                        Neo4j username to use (default is "neo4j")
  -dp DBPASSWORD, --dbpassword DBPASSWORD
                        Neo4j password to use
  -ds DBSOURCE, --dbsource DBSOURCE
                        Case sensitive label of the source node (name property in bloodhound)
  -dt DBTARGET, --dbtarget DBTARGET
                        Case sensitive label of the target node (name property in bloodhound)
  -d DOMAIN, --domain DOMAIN
                        Domain used for NTLM authentication
  -u USERNAME, --username USERNAME
                        Username used for NTLM authentication
  -p PASSWORD, --password PASSWORD
                        Cleartext password or LMHASH:NTHASH for NTLM authentication
  -k, --kerberos
  -c CERTIFICATE, --certificate CERTIFICATE
                        Certificate authentication, e.g: "path/to/key:path/to/cert"
  -s, --secure          Try to use LDAP over TLS aka LDAPS (default is LDAP)
  --host HOST           Hostname or IP of the DC (ex: my.dc.local or 172.16.1.3)

How it works

First a privesc path is found using the Dijkstra's algorithm implemented into the Neo4j's GDS library. The Dijkstra's algorithm allows to solve the shortest path problem on a weighted graph. By default the edges created by BloodHound don't have weight but a type (e.g MemberOf, WriteOwner). A weight is then added to each edge accordingly to the type of edge and the type of node reached (e.g user,group,domain).

Once a path is generated, autobloody will connect to the DC and execute the path and clean what is reversible (everything except ForcePasswordChange and setOwner).

Limitations

For now, only the following BloodHound edges are currently supported for automatic exploitation:

  • MemberOf
  • ForceChangePassword
  • AddMembers
  • AddSelf
  • DCSync
  • GetChanges/GetChangesAll
  • GenericAll
  • WriteDacl
  • GenericWrite
  • WriteOwner
  • Owns
  • Contains
  • AllExtendedRights

Support

Like this project? Donations are welcome

Need personalized support? send me an email for trainings or custom features.