Detect dangerous ACL misconfigurations in Active Directory using ldap3 to identify GenericAll, WriteDACL, and WriteOwner abuse paths
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node --versionanalyzing-active-directory-acl-abuseExecute the skills CLI command in your project's root directory to begin installation:
Fetches analyzing-active-directory-acl-abuse from mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.
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Restart Cursor to activate analyzing-active-directory-acl-abuse. Access via /analyzing-active-directory-acl-abuse in your agent's command palette.
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| 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 |
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.
pip install ldap3)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.
{
"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"
}
]
}
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
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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.
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mukul975/Anthropic-Cybersecurity-Skills
mukul975/Anthropic-Cybersecurity-Skills
mukul975/Anthropic-Cybersecurity-Skills
mukul975/Anthropic-Cybersecurity-Skills
mukul975/Anthropic-Cybersecurity-Skills
mukul975/Anthropic-Cybersecurity-Skills
analyzing-active-directory-acl-abuse is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
I recommend analyzing-active-directory-acl-abuse for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
analyzing-active-directory-acl-abuse is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Useful defaults in analyzing-active-directory-acl-abuse — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Solid pick for teams standardizing on skills: analyzing-active-directory-acl-abuse is focused, and the summary matches what you get after install.
analyzing-active-directory-acl-abuse fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
I recommend analyzing-active-directory-acl-abuse for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
analyzing-active-directory-acl-abuse is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
We added analyzing-active-directory-acl-abuse from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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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