abusing-dpapi-for-cred…
Extract and decrypt Windows DPAPI-protected secrets (Credential Manager, browser logins/cookies, Wi-Fi credentials, KeePass keys)…
Detect dangerous ACL misconfigurations in Active Directory using ldap3
Claude Code
$ npx -y skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-active-directory-acl-abuse --agent claude-code
Codex
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-active-directory-acl-abuse -a codex -y
Cursor
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-active-directory-acl-abuse -a cursor -y
Gemini CLI
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-active-directory-acl-abuse -a gemini-cli -y
GitHub Copilot
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-active-directory-acl-abuse -a github-copilot -y
OpenCode
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-active-directory-acl-abuse -a opencode -y
Windsurf
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill analyzing-active-directory-acl-abuse -a windsurf -y
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 mitre_attack: - T1098 - T1098.007 - T1484.001 - T1222.001 - T1078.002
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.
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.
{
"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"
}
]
}817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io standard · Works with Claude Code, GitHub Copilot, Codex CLI, Cursor, Gemini CLI & 20+ platforms · 29 security domains · Apache 2.0
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