Pentest Copilot: Automating Advanced ACL Exploitation in Active Directory Environments

Executive Summary

Active Directory Access Control List (ACL) exploitation is one of the most sophisticated attack vectors in modern enterprise environments. While traditional penetration testing requires extensive manual effort and deep expertise, AI-powered tools are revolutionizing this landscape.

This comprehensive technical analysis demonstrates how Pentest Copilot, an advanced AI agent specifically designed for penetration testing, successfully automates end-to-end ACL exploitation chains in the Game of Active Directory (GOAD) laboratory.

Our research reveals Pentest Copilot's capability to autonomously execute complex, multi-stage ACL attack paths that traditionally require significant expertise and manual intervention. Through a series of detailed proofs-of-concept, we showcase the automated exploitation of critical ACL permissions, including ForceChangePassword, GenericWrite, WriteDacl, AddSelf, AddMember, WriteOwner, GenericAll, and advanced techniques like GPO abuse.

Understanding the GOAD Laboratory Architecture

GOAD Technical Foundation

The Game of Active Directory (GOAD) laboratory is a sophisticated, multi-domain Active Directory environment designed to simulate realistic enterprise network configurations. The lab architecture incorporates multiple domains with complex trust relationships, including a root domain, a child domain, and an external forest. The environment is built with a realistic network topology and a comprehensive set of Active Directory objects, including hundreds of user accounts, nested security groups, and computer accounts that mirror enterprise hierarchies.

ACL Misconfiguration Landscape

The GOAD environment incorporates deliberately vulnerable ACL configurations that mirror real-world security weaknesses. By default, Active Directory uses the AdminSDHolder mechanism to reset ACLs on protected groups, but this feature has been intentionally disabled in the GOAD environment to allow for persistent exploitation on critical security groups like Domain Admins and Enterprise Admins. The lab features intricate attack paths, such as the sevenkingdoms.local killchain, which demonstrates the cascading nature of ACL exploitation.

Tywin → Jaime (ForceChangePassword)
  → Joffrey (GenericWrite)
    → Tyron (WriteDacl)
      → Small Council (AddSelf)
        → Dragon Stone (AddMember)
          → Kingsguard (WriteOwner)
            → Stannis (GenericAll on User)
              → Kingslanding DC (GenericAll on Computer)

Active Directory ACL Architecture Deep Dive

Security Descriptor Components

Active Directory objects are protected by Security Descriptors that contain key components: the Discretionary Access Control List (DACL), which defines specific permissions; the System Access Control List (SACL), which handles auditing policies; and the Object Owner, which has implicit rights to modify the object's DACL.

Critical ACL Permissions Analysis

We analyzed the exploitation of several critical ACL permissions:

• ForceChangePassword: An extended right that allows an attacker to reset a user's password without knowing the current one, primarily through an RPC interface and LDAP modification of the unicodePwd attribute.
• GenericWrite: Provides broad modification rights, enabling attacks like Shadow Credentials, where attackers inject their own certificates for authentication, and Targeted Kerberoasting, where they modify SPNs to request crackable service tickets.
• WriteDacl: Allows an attacker to modify an object's DACL to grant themselves additional, often full, control over the object.
• AddSelf & AddMember: These permissions allow an attacker to add themselves or other principals to a security group, providing a direct path to privilege escalation through group membership manipulation.
• WriteOwner: Enables an attacker to change an object's owner, effectively granting them complete control to modify the object's DACL and escalate their permissions.
• GenericAll: The highest level of permissions, equivalent to FullControl, which enables all possible operations on a target object, including attribute modification, DACL manipulation, and ownership changes.

Pentest Copilot's ACL Exploitation Engine

Pentest Copilot's automated workflow is driven by a sophisticated AI engine:

• Entity Recognition: The system automatically identifies and categorizes Active Directory objects, including users, groups, and computers, and their permission relationships.
• Vulnerability Assessment & Attack Path Planning: The platform analyzes discovered objects to identify exploitable ACL misconfigurations and then constructs an optimal, multi-stage attack path based on available credentials and target objectives.
• Dynamic Execution: The engine autonomously executes the planned exploitation techniques in real-time, adapting to environmental constraints and acquiring new credentials as it moves through the attack chain.

Detailed ACL Exploitation: Step-by-Step Automation

Pentest Copilot's exploitation capabilities are highly automated, with each step of the attack chain precisely orchestrated by the AI agent. The following sections detail the end-to-end exploitation of specific ACL permissions.

1. Automating ForceChangePassword

The exploitation begins with the identification of a Vulnerability entity where the tywin.lannister user possesses the ForceChangePassword permission on the jaime.lannister account. With a pre-existing Secret entity for tywin.lannister, the platform initiates the exploitation process by selecting the EXP_ACL submodule. The AI agent, present on the target host, is instructed to use the identified vulnerability. The agent autonomously executes the password change, and upon success, the Vulnerability entity is updated to verified, indicating the attack was successful. Simultaneously, a new Secret entity is created, containing the newly changed password for the jaime.lannister account, providing the platform with fresh credentials for further movement.

2. Automating GenericWrite

Leveraging the documentation for the GOAD environment, Pentest Copilot targets a Vulnerability entity where jaime.lannister holds the GenericWrite permission on the joffrey user. The goal is to perform a Shadow Credentials attack, a highly stealthy technique. The platform, using the EXP_ACL submodule, initiates the attack. The agent automatically generates an attacker-controlled certificate and injects it into the msDS-KeyCredentialLink attribute of the joffrey user. The successful exploitation is confirmed as the Vulnerability entity is updated to verified and a new Secret entity is created. This new entity contains the NT hash for the joffrey user, giving the platform a powerful, non-password credential for the next stage of the attack.

3. Automating WriteDacl

In this stage, the platform identifies a Vulnerability entity where a principal has WriteDacl permission on a target. The AI agent’s objective is to modify the target's Access Control List to give the principal Full Control. Upon initiating the EXP_ACL module, the agent uses tools like impacket's dacledit.py to change the DACL. After successfully changing the permissions, the platform leverages its new privileges to perform a Shadow Credentials attack, as seen previously. The successful exploitation is marked by the Vulnerability entity's verified key changing to true and the creation of a new Secret entity containing the target user's NT hash.

4. Automating AddSelf

The platform now targets a Vulnerability entity where the tyron.lannister user has the AddSelf permission on the Small Council group. With the NT hash for tyron.lannister already in a Secret entity, the AI agent initiates the exploitation. The agent automatically modifies the group's membership list to add the tyron user. Once the modification is complete, the Vulnerability entity's verified key is set to true, and the tyron user's profile is updated to show they are now a member of the Small Council group.

5. Automating AddMember

Building on the previous step, the platform identifies that the Small Council group now has AddMember permission on the Dragonstone group. Since tyron.lannister is a member of Small Council, the agent leverages this to add another principal to the Dragonstone group. After selecting the appropriate Vulnerability entity and initiating the EXP_ACL submodule, the platform autonomously modifies the Dragonstone group's membership. The successful operation is confirmed by the Vulnerability entity's verified status and the Dragonstone group’s member list being updated to include the new principal.

6. Automating WriteOwner

Next, the platform targets a Vulnerability entity where the Dragonstone group has WriteOwner permission on another object. Using the NT hash for the tyron.lannister user (who is a member of the Dragonstone group), the agent initiates the exploitation. The AI agent automatically takes ownership of the target object, then leverages its new owner rights to modify the object's DACL to grant itself Full Control. The successful completion of this complex, two-stage process is reflected in the Vulnerability entity's verified key and the updated object permissions.

7. Automating GenericAll on a User

This step targets a Vulnerability entity where a principal has GenericAll permissions on a user account. The platform’s goal is to fully compromise the target user by changing their password. The AI agent, with the principal's credentials in a Secret entity, automatically executes the password change using its broad privileges. This action, a direct outcome of the GenericAll permission, is verified by a verified status update on the Vulnerability entity and the creation of a new Secret entity containing the target user's new password.

8. Automating GenericAll on a Computer

The platform now pivots to a computer account, targeting a Vulnerability entity where a principal has GenericAll permission on the KINGSLANDING computer. The goal is to obtain the NT hash of this critical machine. Using the principal’s existing credentials, the agent initiates the exploitation of the vulnerability. The platform autonomously executes a series of commands made possible by its GenericAll privilege, ultimately succeeding in extracting the computer's NT hash. This is immediately reflected in a new Secret entity containing the KINGSLANDING computer's NT hash and a verified status on the Vulnerability entity.

9. Automating GPO Abuse

The final stage demonstrates an advanced persistence technique. The platform identifies a Vulnerability entity where a principal has WriteOwner permission on a Group Policy Object (GPO). Using the EXP_ACL submodule, the AI agent exploits this vulnerability to gain control of the GPO. The agent then automatically modifies the GPO to create a scheduled task that executes a payload with SYSTEM privileges on all affected machines. This payload creates a new, highly privileged user account called pentestcopilot. The successful exploitation is confirmed by the verified key on the Vulnerability entity and the automatic creation of a new Secret entity containing the password for the newly created pentestcopilot user.

Security Architecture Implications

Advanced Persistent Threat Simulation

The capabilities of Pentest Copilot closely mirror sophisticated APT techniques, as it relies on Living Off the Land tactics by exclusively using legitimate Active Directory features for exploitation. The platform's ability to orchestrate multi-stage attacks and pivot through compromised credentials demonstrates a level of sophistication that goes beyond traditional, manual attacks.

Defensive Architecture Evolution

Organizations must implement a proactive defense strategy to counter these automated attacks:

• Advanced Monitoring: Deploy analytics to detect unusual LDAP queries, rapid permission modifications, and abnormal certificate enrollments in real-time.
• Zero Trust & Hardening: Enforce a zero-trust model with privileged access management (PAM) and conduct systematic ACL hardening to eliminate excessive rights and limit the impact of exploitation.
• Proactive Threat Hunting: Regularly search for indicators of ACL abuse and multi-stage attack signatures to stay ahead of automated threats.

Conclusion

The automation of complex Active Directory ACL exploitation through platforms like Pentest Copilot represents a fundamental shift in the cybersecurity landscape. The traditional reliance on the obscurity and complexity of ACL exploitation techniques no longer provides adequate protection against determined adversaries equipped with AI-powered tools.

The future of Active Directory security requires proactive defense strategies that can match the sophistication of AI-powered attacks. Security architects must focus on comprehensive ACL hardening, advanced behavioral monitoring, and proactive threat hunting to defend against these increasingly automated and sophisticated attack vectors.

Technical Specifications

• Testing Environment: GOAD (Game of Active Directory) Laboratory
• Platform: Pentest Copilot AI Agent (https://copilot.bugbase.ai/)
• Domain Architecture: Multi-domain forest environment
• ACL Exploitation Scenarios: 9 distinct ACL permission abuse techniques demonstrated

References

• GOAD Project - Orange Cyberdefense: https://github.com/Orange-Cyberdefense/GOAD
• GOAD ACL Exploitation Guide: https://mayfly277.github.io/posts/GOADv2-pwning-part11/
• Pentest Copilot Platform: https://copilot.bugbase.ai/
• Microsoft Active Directory Security Architecture Documentation
• Active Directory ACL Security Research Archives
• Video POCs: https://www.youtube.com/playlist?list=PLykO1ama0mbIMoz-dz5lyxF3uhMPf2Va-

Top 5 Frequently Asked Questions (FAQs)

1. What is ACL exploitation in Active Directory and why is it critical for cybersecurity?

ACL (Access Control List) exploitation involves abusing misconfigured permissions in Active Directory to gain unauthorized access and escalate privileges. When permissions like ForceChangePassword, GenericWrite, or WriteDacl are misconfigured, attackers can chain them together to compromise entire domains. This is critical because it leverages legitimate AD features, making detection difficult, and can lead from a low-privileged user to Domain Admin access.

2. How does Pentest Copilot automate ACL exploitation?

Pentest Copilot uses an AI-powered engine with three key components: an Entity Recognition System to categorize AD objects and permissions; a Vulnerability Assessment Engine to find misconfigurations; and a Dynamic Execution Framework to build and execute optimal attack paths in real-time.

3. What is the GOAD laboratory?

GOAD (Game of Active Directory) is a deliberately vulnerable multi-domain AD lab environment designed for penetration testing research. It features a realistic forest architecture (sevenkingdoms.local, north.sevenkingdoms.local, essos.local) with intentional ACL misconfigurations that mirror real-world vulnerabilities. This environment is ideal for testing advanced attack techniques.

4. What are shadow credentials attacks?

Shadow credentials attacks exploit the msDS-KeyCredentialLink attribute in Active Directory to enable certificate-based authentication for a targeted account. Attackers use permissions like GenericWrite to inject an attacker-controlled certificate into the target's account. This allows them to perform Kerberos authentication and obtain a Ticket-Granting Ticket (TGT), often with minimal audit traces.

5. How should organizations defend against automated ACL exploitation?

Organizations need comprehensive defenses: ACL Security Hardening to eliminate excessive rights; Advanced Behavioral Monitoring to detect unusual LDAP queries and permission changes; and Zero Trust with privileged access management (PAM) to limit the impact of exploitation. Since these attacks are automated, continuous threat hunting is also essential.