analyzing-active-directory-acl-abuse

Q: How do I install analyzing-active-directory-acl-abuse?

Run npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill analyzing-active-directory-acl-abuse in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/analyzing-active-directory-acl-abuse/ (personal) or .claude/skills/analyzing-active-directory-acl-abuse/ (project).

by mukul975AI & Agents

Detect dangerous ACL misconfigurations in Active Directory using ldap3 to identify GenericAll, WriteDACL, and WriteOwner abuse paths

Installs: 549
Last 24h: —
Trending rank: —
Security: Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill analyzing-active-directory-acl-abuse

01
Install
Run the command in your project. The CLI asks which agents to install for.
02
Describe the task
Ask your agent for something this skill covers. It loads analyzing-active-directory-acl-abuse automatically when relevant.
03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Analyzing Active Directory ACL Abuse

Overview

Active Directory Access Control Lists (ACLs) define permissions on AD objects through Discretionary Access Control Lists (DACLs) containing Access Control Entries (ACEs). Misconfigured ACEs can grant non-privileged users dangerous permissions such as GenericAll (full control), WriteDACL (modify permissions), WriteOwner (take ownership), and GenericWrite (modify attributes) on sensitive objects like Domain Admins groups, domain controllers, or GPOs.

This skill uses the ldap3 Python library to connect to a Domain Controller, query objects with their nTSecurityDescriptor attribute, parse the binary security descriptor into SDDL (Security Descriptor Definition Language) format, and identify ACEs that grant dangerous permissions to non-administrative principals. These misconfigurations are the basis for ACL-based attack paths discovered by tools like BloodHound.

When to Use

When investigating security incidents that require analyzing active directory acl abuse
When building detection rules or threat hunting queries for this domain
When SOC analysts need structured procedures for this analysis type
When validating security monitoring coverage for related attack techniques

Prerequisites

Python 3.9 or later with ldap3 library (pip install ldap3)
Domain user credentials with read access to AD objects
Network connectivity to Domain Controller on port 389 (LDAP) or 636 (LDAPS)
Understanding of Active Directory security model and SDDL format

Steps

Connect to Domain Controller: Establish an LDAP connection using ldap3 with NTLM or simple authentication. Use LDAPS (port 636) for encrypted connections in production.
Query target objects: Search the target OU or entire domain for objects including users, groups, computers, and OUs. Request the nTSecurityDescriptor, distinguishedName, objectClass, and sAMAccountName attributes.
Parse security descriptors: Convert the binary nTSecurityDescriptor into its SDDL string representation. Parse each ACE in the DACL to extract the trustee SID, access mask, and ACE type (allow/deny).
Resolve SIDs to principals: Map security identifiers (SIDs) to human-readable account names using LDAP lookups against the domain. Identify well-known SIDs for built-in groups.
Check for dangerous permissions: Compare each ACE's access mask against dangerous permission bitmasks: GenericAll (0x10000000), WriteDACL (0x00040000), WriteOwner (0x00080000), GenericWrite (0x40000000), and WriteProperty for specific extended rights.
Filter non-admin trustees: Exclude expected administrative trustees (Domain Admins, Enterprise Admins, SYSTEM, Administrators) and flag ACEs where non-privileged users or groups hold dangerous permissions.
Map attack paths: For each finding, document the potential attack chain (e.g., GenericAll on user allows password reset, WriteDACL on group allows adding self to group).
Generate remediation report: Output a JSON report with all dangerous ACEs, affected objects, non-admin trustees, and recommended remediation steps.

Expected Output

{
  "domain": "corp.example.com",
  "objects_scanned": 1247,
  "dangerous_aces_found": 8,
  "findings": [
    {
      "severity": "critical",
      "target_object": "CN=Domain Admins,CN=Users,DC=corp,DC=example,DC=com",
      "target_type": "group",
      "trustee": "CORP\\helpdesk-team",
      "permission": "GenericAll",
      "access_mask": "0x10000000",
      "ace_type": "ACCESS_ALLOWED",
      "attack_path": "GenericAll on Domain Admins group allows adding arbitrary members",
      "remediation": "Remove GenericAll ACE for helpdesk-team on Domain Admins"
    }
  ]
}

FAQ

What does the analyzing-active-directory-acl-abuse skill do?

Detect dangerous ACL misconfigurations in Active Directory using ldap3 to identify GenericAll, WriteDACL, and WriteOwner abuse paths

How do I install analyzing-active-directory-acl-abuse?

Run npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill analyzing-active-directory-acl-abuse in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/analyzing-active-directory-acl-abuse/ (personal) or .claude/skills/analyzing-active-directory-acl-abuse/ (project).

Which AI agents can use analyzing-active-directory-acl-abuse?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is analyzing-active-directory-acl-abuse safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains analyzing-active-directory-acl-abuse?

It is published by mukul975 in mukul975/anthropic-cybersecurity-skills. It has 549 recorded installs.