DACLhound

DACLhound collects Active Directory security descriptors over LDAP and turns the results into a graph you can inspect in a browser. The collector uses bloodyAD as a Python library; it does not run the bloodyAD command. Impacket's Python library handles password-based Kerberos TGT requests, passing the ticket in memory to bloodyAD.

It is primarily intended for Hack The Box (HTB) and similar hands-on labs, and works best with lab-sized or otherwise moderate Active Directory environments. It is not designed or performance-tested for very large enterprise domains.

Unlike BloodHound CE's modeled graph edges, DACLhound preserves the collected DACL details and exposes individual Write-Property rights by attribute (for example, WriteLogonHours or WriteUserAccountControl, etc.). This helps inspect the specific property and ACE behind a relationship.

Development status

DACLhound is still under active development. I plan to update it daily as I continue testing it, fixing bugs, and improving the results. You may encounter issues, and feedback or bug reports are welcome.

Demo

https://github.com/user-attachments/assets/62a531d9-c3f0-47d3-aab0-d7fef8db28d1

The demo walks through collecting a domain and opening the graph viewer. It also shows selecting an object to focus on its permission paths, hiding objects, and setting start and end nodes to reveal a path.

Install

Python 3.10 or newer is required.

pipx install DACLhound

Upgrade later with:

pipx upgrade DACLhound

Collect a graph

DACLhound.py collect --host $FQDN -d $DOMAIN -u 'user' -p 'password' --dc-ip $IP --output $DOMAIN.json

The collector is read-only. By default it collects users, groups, computers, OUs, containers, GPOs, the domain, and ADCS data. Use --types to limit directory object types:

DACLhound.py collect --host $FQDN -d $DOMAIN -u 'user' -p 'password' --types users,groups --output users-and-groups.json

Use --no-adcs to skip ADCS collection. The normalized graph is written to --output. Add --raw-output to keep the bloodyAD response as well.

Authentication

NTLM password

DACLhound.py collect --host $FQDN -d $DOMAIN -u 'user' -p 'password' --dc-ip $IP -o $DOMAIN.json

NTLM pass-the-hash

Use LMHASH:NTHASH; if you only have the NT hash, leave the LM field empty:

DACLhound.py collect --host $FQDN -d $DOMAIN -u 'user' -hashes ':<NTHASH>' --dc-ip $IP -o $DOMAIN.json

Kerberos

Kerberos supports a password, pass-the-hash, or an existing ccache. When using a ccache, -u is optional; the identity is taken from the ticket. -no-pass is an explicit flag for ccache authentication.

Password:

DACLhound.py collect --host $FQDN -d $DOMAIN -u 'user' -p '<password>' -k --dc-ip $IP -o $DOMAIN.json

Pass-the-hash (NT hash used as the Kerberos RC4 key):

DACLhound.py collect --host $FQDN -d $DOMAIN -u 'user' -hashes '<LMHASH>:<NTHASH>' -k --dc-ip $IP -o $DOMAIN.json

If only the NT hash is available, use -hashes '<NTHASH>'.

Existing ccache:

# Use the current KRB5CCNAME
DACLhound.py collect --host $FQDN -d $DOMAIN -k -no-pass --dc-ip $IP -o DOMAIN.json

# Or provide a ccache file directly
DACLhound.py collect --host $FQDN -d $DOMAIN -k user.ccache -no-pass --dc-ip $IP -o $DOMAIN.json

An AES key enables Kerberos automatically: use -aesKey '<AESKEY>' (with -u). Add -s to use LDAPS.

Open the graph

Run the viewer in the foreground and stop it with Ctrl+C:

DACLhound.py graph --input $DOMAIN.json

Or run it in the background:

DACLhound.py graph start
DACLhound.py graph start --input $DOMAIN.json
DACLhound.py graph status
DACLhound.py graph stop

The server listens on 127.0.0.1:8765 by default. Uploaded JSON files stay in memory while the server is running and are discarded when it stops. Use --bind and --port to change the listener. Run DACLhound.py collect --help or DACLhound.py graph --help for all options.

License

MIT. See LICENSE.