I've been working on an open-source project for automating parts of Active Directory security assessments.

AdPentestAI-Python v1.0.0

GitHub:
https://github.com/netanelcyber/AdPentestAI-Python

The problem I wanted to solve is fairly simple: during an AD assessment, a lot of time is spent moving between different discovery and enumeration tools, collecting output, correlating results, and turning everything into a consistent report.

The framework is designed as an orchestration layer around that workflow:

DNS / DC Discovery ↓ LDAP / RootDSE ↓ SMB / RPC ↓ Kerberos ↓ AD Enumeration ↓ Security Assessment ↓ Correlation ↓ JSON Report 

Current capabilities

• Automated Domain Controller discovery
• DNS SRV discovery
• LDAP RootDSE discovery
• Port/service fingerprinting
• Active Directory enumeration
• Users / Groups / Computers discovery
• SMB / RPC enumeration
• Kerberos-oriented assessment workflows
• Integration with security assessment tools
• Parallel execution of independent checks
• Structured JSON output
• Dry-run mode
• Explicit scope confirmation
• Process timeouts and execution controls

One of the design goals is to keep the framework from becoming a "run everything against the target" script.

The intended execution model is:

dry-run ↓ scope validation ↓ explicit authorization ↓ assessment ↓ structured results 

The project is intended for authorized penetration tests, labs, research and security assessments.

What I'm looking for

I'd particularly like feedback from people who have actually performed AD pentests.

What would you change in the architecture?

Some questions I'm currently thinking about:

1. Which AD assessment steps are still too manual?
2. Which tools/integrations would you add?
3. How should findings from different tools be normalized?
4. What should a useful machine-readable pentest result contain?
5. Where should automation stop and require human approval?
6. Would ATT&CK mapping add useful value here?
7. Would you prefer a CLI-first architecture, API, or both?

I'm especially interested in criticism of the architecture and workflow rather than just feature requests.

Repository:
https://github.com/netanelcyber/AdPentestAI-Python