Back to Research
Red Team

Setting up an Active Directory Pentest Lab in Seconds with AI (Cursor)

Mevlüt YıldırımAuthor
April 1, 2026
4 min read

Setting up an Active Directory Pentest Lab in Seconds with AI (Cursor)

Setting up an Active Directory (AD) lab for practicing modern Red Team engagement scenarios—Kerberoasting, AS-REP Roasting, BloodHound mapping, or Golden Ticket attacks—traditionally requires monstrous virtual machines, hours of reading Windows Server documentation, and mind-numbing PowerShell scripts to simulate vulnerable users.

But it's 2026. Setting up a lab manually is a waste of an ethical hacker's time.

With the rise of intelligent IDEs like Cursor AI (powered by Claude 3.5 Sonnet / GPT-4o) and Infrastructure as Code (IaC) tools like Terraform and Ansible, creating a network of vulnerable Domain Controllers and compromised client workstations is now as simple as writing a single, well-architected prompt.

In this guide, we dive into building an automated, ephemeral AD range using AI.

1. Why Automation Over Manual VMs?

If you are a CISO or a Red Team Lead, you want your junior analysts to spend their 8-hour shifts exploiting Domain Admins, not fighting with VirtualBox bridging issues. Building labs manually has zero return on investment.

By utilizing Terraform and Ansible alongside Cursor AI:

  • Reproducibility: You can destroy the lab when the pentest scenario ends and recreate it perfectly the next day without paying for idle AWS EC2 instances.
  • Complexity at Scale: Want to simulate a Forest Trust vulnerability between two distinct domains? An LLM can generate the 200-line Ansible playbook to establish the trust instantly.
  • Cost Efficiency: You can spin the entire AD forest up on a cloud provider like Azure or AWS, run your BloodHound collectors, verify the attack paths, and tear it down for pennies.

2. Using Cursor AI to Architect the Lab

Cursor AI operates beautifully when you provide it with rigid constraints and specific technological requirements. To construct your AD lab, open Cursor and use the following system prompt to command the AI:

The Master Prompt

"Act as an Offensive Security Infrastructure Engineer. I need to deploy a vulnerable Active Directory lab in AWS using Terraform and configure the misconfigurations using Ansible. Ensure the environment consists of 1 Windows Server 2022 (Domain Controller) and 1 Windows 10 (Workstation). Create the Terraform (main.tf) to provision the EC2 instances in a private subnet. Then, write an Ansible playbook that configures the Domain Controller (marvel.local), creates 5 users, and intentionally leaves 2 users vulnerable to Kerberoasting (by assigning SPNs) and 1 user vulnerable to AS-REP Roasting (by disabling Kerberos Pre-Authentication)."

AI's Output and Magic

Cursor will immediately generate the main.tf to spin up the Windows EC2 instances. More importantly, it will generate the complex winrm Ansible configurations required to remotely push the Active Directory Domain Services (AD DS) feature onto the raw Windows Server. Instead of manually typing Install-WindowsFeature AD-Domain-Services, the AI provisions the forest unattended.

3. Injecting Realistic Vulnerabilities

A lab is useless if it's perfectly secure. The true value of combining AI with Ansible lies in rapidly generating complex Attack Paths that tools like BloodHound can visualize.

By modifying your Cursor prompt, you can seamlessly add advanced enterprise misconfigurations:

  • DCSync Vulnerabilities: Ask Cursor to "Add an Ansible task to grant a standard user 'Replicating Directory Changes' and 'Replicating Directory Changes All' permissions at the domain root." You can now practice DCSync attacks using Mimikatz or Impacket's secretsdump.py.
  • Delegation Attacks: Ask the AI to configure Unconstrained Delegation on a specific computer object, setting the stage for devastating Kerberos ticket theft.
  • GPO Misconfigurations: Have Ansible deploy a Group Policy Object that pushes a local administrator password across the domain, allowing you to practice lateral movement via SMB Relay or Pass-the-Hash.

4. Validating the Range

Once Terraform finishes applying and Ansible completes configuring the Domain Controller, your vulnerable environment is live. Connecting to it via a Kali Linux instance or OpenVPN allows you to execute your attack chain:

  1. Run GetNPUsers.py to exploit the AS-REP Roasting vulnerability the AI created.
  2. Crack the hash offline using Hashcat.
  3. Use the compromised user to map the environment using bloodhound-python.

By integrating AI into infrastructure provisioning, offensive security professionals are no longer constrained by the tedious limits of IT administration. Build your custom range, conquer the Domain, and automate your mastery.