Autonomous pentesting against Active Directory, without the black box #31
Dark-Moon-X
announced in
Announcements
Replies: 0 comments
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Uh oh!
There was an error while loading. Please reload this page.
Active Directory is where most internal compromises happen and where most AI tools give up. Darkmoon runs the AD attack path autonomously and shows every step.
Why AD is hard for AI. AD attack paths are stateful and multi step. A single prompt cannot hold the whole graph. You need an agent loop that enumerates, reasons and pivots while keeping state.
Playbooks as the state engine. In Darkmoon the AD methodology is a Markdown playbook you can read and fork. The agent follows it, the proxy keeps the state, and every tool call is explicit.
From foothold to domain. The agent enumerates with BloodHound style logic, identifies attack paths, and executes them with real tools, attaching the output of each step.
Auditable by design. Because the method is a file and the execution is logged, a reviewer can follow exactly how the domain fell.
Run it on GOAD and read the generated attack path end to end.
Docs: https://docs.dark-moon.org/ | Demo: https://youtu.be/1bFRVuMkZzY
What would you want to see next, and where do you think this approach breaks? Feedback welcome.
All reactions