analyzing-active-directory-acl-abuse
Detect dangerous ACL misconfigurations in Active Directory using ldap3 to identify GenericAll, WriteDACL, and WriteOwner abuse paths
- License 许可
- Apache-2.0
- 最近更新
- 2026-08-31
- Stars
- ★ 3.6w
- Forks
- 4.4k
01 前言 Front Matter
- name
- analyzing-active-directory-acl-abuse
- tags
- [ "active-directory", "acl-abuse", "ldap", "privilege-escalation" ]
- author
- mahipal
- domain
- cybersecurity
- license
- Apache-2.0
- version
- 1.0
- nist_csf
- [ "PR.AA-01", "PR.AA-05", "PR.AA-06" ]
- subdomain
- identity-security
- description
- Detect dangerous ACL misconfigurations in Active Directory using ldap3 to identify GenericAll, WriteDACL, and WriteOwner abuse paths
- mitre_attack
- [ "T1098", "T1098.007", "T1484.001", "T1222.001", "T1078.002" ]
02 资源文件 6
- 脚本helper.js83 B
- 许可证LICENSE11.0 KB
- 参考文档references/api-reference.md2.9 KB
- 脚本script.py64 B
- 脚本scripts/agent.py9.3 KB
- 其他widget.tsx93 B
03 SKILL.md 正文
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, andsAMAccountNameattributes. -
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"
}
]
}
04 同仓库更多 Skills
verifying-build-provenance-with-slsa-sigstore
Verifies artifact signatures and SLSA provenance using Sigstore's cosign (verify, verify-attestation, verify-blob-attestation) and slsa-verifier (verify-artifact), enforcing keyless OIDC builder identity and source repo against SLSA Build levels. Use in CI/CD before deploying artifacts, when consuming third-party attestations, establishing a SLSA Build L3 pipeline, or confirming provenance during incident response or admission control.
validating-tpm-measured-boot-attestation
Verifies TPM 2.0 measured-boot integrity and remote attestation with tpm2-tools -- reading PCRs (tpm2_pcrread), replaying the boot event log, generating and checking signed quotes (tpm2_quote/tpm2_checkquote), and sealing secrets to a PCR policy. Use to confirm a system booted trusted firmware/kernel for Zero Trust device posture, detect boot-chain tampering via PCR drift, or build a golden-value baseline for fleet attestation.
validating-backup-integrity-for-recovery
Validates backup integrity through cryptographic hash verification, automated restore testing, corruption detection, and recoverability checks to confirm backups are reliable for disaster recovery and ransomware response. Use before relying on backups for recovery, when building post-backup validation pipelines, auditing backup infrastructure for compliance, or checking immutable/air-gapped backups for silent corruption or tampering.
triaging-windows-with-kape
Runs KAPE (Kroll Artifact Parser and Extractor) to collect targeted forensic artifacts (registry hives, $MFT, event logs, prefetch, browser data) via Targets and parse them with Modules wrapping Eric Zimmerman's EZ Tools (PECmd, MFTECmd, RECmd). Use during early incident containment/triage when full disk imaging is impractical but a defensible, parseable Windows artifact set is needed quickly, including at-scale remote collection.
triaging-vulnerabilities-with-ssvc-framework
Triages and prioritizes vulnerabilities with CISA's Stakeholder-Specific Vulnerability Categorization (SSVC) decision tree, weighing exploitation status (via the CISA KEV catalog and FIRST EPSS API), technical impact, automatability, and mission prevalence to output Track/Track*/Attend/Act decisions. Use when prioritizing vulnerability scan results (OpenVAS, Nessus, Qualys) for remediation planning beyond raw CVSS scores.
triaging-security-incident
Performs initial triage of security incidents using the NIST SP 800-61r3 and SANS PICERL frameworks, classifying incident type, assigning priority by business impact, and routing to the appropriate response team. Use when a SIEM/EDR alert needs human classification, concurrent alerts must be prioritized, or a user report or threat-intel IOC match requires initial incident categorization.