seikaikyo/performing-active-directory-forest-trust-attack
external/anthropic-cybersecurity-skills/skills/performing-active-directory-forest-trust-attack/SKILL.md
Enumerate and audit Active Directory forest trust relationships using Impacket for SID filtering analysis, trust key extraction, cross-forest SID history abuse detection, and inter-realm Kerberos ticket assessment. Use when red-teaming multi-forest AD environments or auditing forest trusts for cross-forest privilege escalation and trust ticket forgery exposure.
$ install --global
skillsauthnpx skillsauth add seikaikyo/dash-skills performing-active-directory-forest-trust-attackInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Aug 17, 2026, 5:40 AM145.8s3 files scanned
SKILL.md
- name:
- performing-active-directory-forest-trust-attack
- description:
- Enumerate and audit Active Directory forest trust relationships using
- domain:
- cybersecurity
- subdomain:
- red-team
- version:
- 1.0
- author:
- mahipal
- license:
- Apache-2.0
Performing Active Directory Forest Trust Attack
Overview
Active Directory forest trusts enable authentication across organizational boundaries but introduce attack surface if misconfigured. This skill uses impacket to enumerate trust relationships, analyze SID filtering configuration, detect SID history abuse vectors, perform cross-forest SID lookups via LSA/LSAT RPC calls, and assess inter-realm Kerberos ticket configurations for trust ticket forgery risks.
When to Use
- When conducting security assessments that involve performing active directory forest trust attack
- When following incident response procedures for related security events
- When performing scheduled security testing or auditing activities
- When validating security controls through hands-on testing
Prerequisites
- Python 3.9+ with
impacket,ldap3 - Domain credentials with read access to AD trust objects
- Network access to Domain Controllers (ports 389, 445, 88)
- Authorized penetration testing engagement or lab environment
Legal Notice: This skill is for authorized security testing and educational purposes only. Unauthorized use against systems you do not own or have written permission to test is illegal and may violate computer fraud laws.
Steps
- Enumerate forest trust relationships via LDAP trusted domain objects
- Query trust attributes and SID filtering status for each trust
- Perform SID lookups across trust boundaries using LsarLookupNames3
- Enumerate foreign security principals in trusted domains
- Check for SID history on cross-forest accounts
- Assess trust direction and transitivity for lateral movement paths
- Generate trust security audit report with risk findings
Expected Output
- JSON report listing all trust relationships, SID filtering status, foreign principals, trust direction/transitivity, and risk assessment
- Cross-forest attack path analysis with remediation recommendations
Related Skills
seikaikyo/conducting-gdpr-compliance-assessment
tools
VerifiedTrustedCommunity
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.
2SKILL.mdUpdated Sep 11, 2026
seikaikyo/parsing-artifacts-with-eric-zimmerman-tools
tools
VerifiedTrustedCommunity
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.
2SKILL.mdUpdated Jun 23, 2026
seikaikyo/orchestrating-llm-attacks-with-pyrit
development
VerifiedTrustedCommunity
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.
2SKILL.mdUpdated Jun 23, 2026
seikaikyo/operationalizing-misp-threat-feeds
testing
VerifiedTrustedCommunity
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.
2SKILL.mdUpdated Jun 23, 2026