external/anthropic-cybersecurity-skills/skills/performing-active-directory-compromise-investigation/SKILL.md
Investigate Active Directory compromise by analyzing authentication logs, replication metadata, Group Policy changes, and Kerberos ticket anomalies to identify attacker persistence and lateral movement paths.
npx skillsauth add seikaikyo/dash-skills performing-active-directory-compromise-investigationInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Active Directory (AD) compromise investigation is a critical incident response capability that focuses on identifying how attackers gained access to domain services, what persistence mechanisms they established, and the scope of credential compromise. Since 88% of breaches involve compromised credentials (Verizon 2025 DBIR), AD is the primary target for enterprise-wide attacks. Investigators must analyze NTDS.dit database integrity, Kerberos ticket-granting activity, Group Policy modifications, replication metadata, and privileged group membership changes to reconstruct the attack chain and determine full compromise scope.
The NTDS.dit file is the core Active Directory credential database containing all password hashes for domain accounts. Attackers commonly exfiltrate this file using tools like ntdsutil, secretsdump.py, or DCSync attacks via Mimikatz.
Detection indicators:
Golden Ticket indicators:
Silver Ticket indicators:
Kerberoasting indicators:
Track modifications to these critical groups:
1. Identify potentially compromised domain controllers
2. Collect Security, System, Directory Service event logs
3. Extract AD replication metadata using repadmin
4. Capture ntdsutil snapshots for offline analysis
5. Collect DNS server logs and zone transfer records
6. Export Group Policy Object configurations
7. Document current privileged group memberships
1. Parse Event ID 4624/4625 for logon patterns
2. Identify pass-the-hash indicators (Event ID 4624 Type 3 with NTLM)
3. Analyze Event ID 4768/4769/4771 for Kerberos anomalies
4. Review Event ID 4776 for NTLM authentication failures
5. Cross-reference logon events with known compromised accounts
6. Map lateral movement paths through authentication chains
1. Enumerate AdminSDHolder ACL modifications
2. Check for SID History abuse on accounts
3. Verify krbtgt account password age
4. Audit DSRM password configuration
5. Check for skeleton key malware indicators
6. Review AD Certificate Services for rogue certificates
7. Validate DNS records for poisoning
1. Double-rotate krbtgt password (wait replication between rotations)
2. Reset all compromised account passwords
3. Remove unauthorized privileged group members
4. Revoke rogue certificates if AD CS compromised
5. Rebuild domain controllers from clean media if needed
6. Implement tiered administration model
7. Enable Protected Users group for privileged accounts
| Event ID | Source | Description | |----------|--------|-------------| | 4624 | Security | Successful logon | | 4625 | Security | Failed logon | | 4648 | Security | Explicit credential logon | | 4662 | Security | Operation on AD object | | 4768 | Security | Kerberos TGT requested | | 4769 | Security | Kerberos service ticket requested | | 4771 | Security | Kerberos pre-authentication failed | | 4776 | Security | NTLM credential validation | | 5136 | Security | Directory object modified | | 5137 | Security | Directory object created | | 4706 | Security | Trust created | | 4707 | Security | Trust removed | | 4742 | Security | Computer account changed | | 8222 | System | Shadow copy created |
| Tool | Purpose | |------|---------| | BloodHound | Attack path mapping and privilege escalation analysis | | Pingcastle | AD security assessment and risk scoring | | Purple Knight | AD vulnerability scanning by Semperis | | ADRecon | Active Directory data gathering | | Mimikatz | Credential extraction and Kerberos analysis | | Impacket | DCSync detection and NTLM relay analysis | | Velociraptor | Remote forensic artifact collection | | Timeline Explorer | Event log timeline analysis |
| Technique | ID | Relevance | |-----------|----|-----------| | DCSync | T1003.006 | NTDS.dit credential extraction | | Golden Ticket | T1558.001 | Kerberos TGT forgery | | Silver Ticket | T1558.002 | Service ticket forgery | | Kerberoasting | T1558.003 | Service account hash extraction | | Pass-the-Hash | T1550.002 | NTLM hash reuse | | Group Policy Modification | T1484.001 | Persistence via GPO | | Account Manipulation | T1098 | Privileged group changes | | SID-History Injection | T1134.005 | Privilege escalation |
tools
Conduct comprehensive GDPR compliance assessments by evaluating data processing activities against EU Regulation 2016/679, including Article 30 records of processing, lawful basis validation, data subject rights implementation, Data Protection Impact Assessments (DPIAs) under Article 35, breach notification procedures, international transfer safeguards (SCCs, adequacy decisions), and technical/organizational measures under Article 32. Use when processing personal data of EU residents, preparing for supervisory authority audits, implementing privacy-by-design for new systems, scoping compliance gaps for M&A due diligence, assessing third-party processors, or responding to data subject access requests at scale. Incorporates 2026 guidance from ICO, EDPB, and post-Data (Use and Access) Act 2025 UK-GDPR considerations. Do not use for implementing specific Article 32 controls — use implementing-gdpr-data-protection-controls; or for DSAR automation — use implementing-gdpr-data-subject-access-request.
tools
Parse Windows forensic artifacts—$MFT/$J (MFTECmd), Prefetch (PECmd), registry hives (RECmd), shellbags, and Amcache—into normalized CSV/JSON with Eric Zimmerman's EZ Tools, then load results into Timeline Explorer for analysis. Use during DFIR/incident-response investigations, after triage collection (e.g. with KAPE), to establish program execution, file/folder access, and persistence evidence from acquired forensic images.
development
Build automated multi-turn adversarial attacks against conversational LLM targets using Microsoft PyRIT's RedTeamingOrchestrator, CrescendoOrchestrator (gradual escalation), and TreeOfAttacksWithPruningOrchestrator (adaptive branching), with scorer feedback loops and persisted conversation memory. Use when single-shot LLM scanning is insufficient and you need multi-turn, scorer-driven AI red-team campaigns against a chatbot or agent.
testing
Stand up MISP, enable and cache curated threat feeds (CIRCL, abuse.ch, Feodo Tracker), apply warninglists to suppress false positives, query indicators with PyMISP, and export attributes as auto-generated Suricata/Sigma/Wazuh detection rules. Use when maturing a MISP instance to actively drive detection, curating threat feeds with quality controls, or automating IOC-to-detection pipelines for the SIEM/IDS.