analyzing-active-directory-acl-abuse

mukul975/Anthropic-Cybersecurity-Skills · updated May 25, 2026

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$npx skills install mukul975/Anthropic-Cybersecurity-Skills/analyzing-active-directory-acl-abuse
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summary

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

skill.md
name
analyzing-active-directory-acl-abuse
description
Detect dangerous ACL misconfigurations in Active Directory using ldap3 to identify GenericAll, WriteDACL, and WriteOwner abuse paths
domain
cybersecurity
subdomain
identity-security
tags
- active-directory - acl-abuse - ldap - privilege-escalation
version
'1.0'
author
mahipal
license
Apache-2.0
nist_csf
- PR.AA-01 - PR.AA-05 - PR.AA-06

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

  1. Connect to Domain Controller: Establish an LDAP connection using ldap3 with NTLM or simple authentication. Use LDAPS (port 636) for encrypted connections in production.

  2. 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.

  3. 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).

  4. 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.

  5. 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.

  6. 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.

  7. 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).

  8. 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"
    }
  ]
}
how to use analyzing-active-directory-acl-abuse

How to use analyzing-active-directory-acl-abuse on Cursor

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1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add analyzing-active-directory-acl-abuse
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills install mukul975/Anthropic-Cybersecurity-Skills/analyzing-active-directory-acl-abuse

The skills CLI fetches analyzing-active-directory-acl-abuse from GitHub repository mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/analyzing-active-directory-acl-abuse

Reload or restart Cursor to activate analyzing-active-directory-acl-abuse. Access the skill through slash commands (e.g., /analyzing-active-directory-acl-abuse) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.671 reviews
  • Liam Menon· Dec 28, 2024

    analyzing-active-directory-acl-abuse is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Chaitanya Patil· Dec 16, 2024

    I recommend analyzing-active-directory-acl-abuse for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Evelyn Sanchez· Dec 16, 2024

    analyzing-active-directory-acl-abuse is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Yusuf Ghosh· Dec 4, 2024

    Useful defaults in analyzing-active-directory-acl-abuse — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Diya Martin· Dec 4, 2024

    Solid pick for teams standardizing on skills: analyzing-active-directory-acl-abuse is focused, and the summary matches what you get after install.

  • Diya Tandon· Dec 4, 2024

    analyzing-active-directory-acl-abuse fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Ishan Kim· Nov 23, 2024

    I recommend analyzing-active-directory-acl-abuse for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Diya Verma· Nov 23, 2024

    analyzing-active-directory-acl-abuse is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Diya Khanna· Nov 23, 2024

    We added analyzing-active-directory-acl-abuse from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Evelyn Diallo· Nov 19, 2024

    Solid pick for teams standardizing on skills: analyzing-active-directory-acl-abuse is focused, and the summary matches what you get after install.

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