Detecting Golden Ticket Forgery
Detect Kerberos Golden Ticket forgery by analyzing Windows Event ID 4769 for RC4 encryption downgrades (0x17), abnormal ticket lifetimes, and krbtgt account anomalies in Splunk and Elastic SIEM
MCP get_skill({ skillId: "detecting-golden-ticket-forgery-8c28bed2" })Use this skill with your agent
Create a free account and connect via MCP
# Detecting Golden Ticket Forgery ## Overview A Golden Ticket attack (MITRE ATT&CK T1558.001) involves forging a Kerberos Ticket Granting Ticket (TGT) using the krbtgt account NTLM hash, granting unrestricted access to any service in the Active Directory domain. This skill detects Golden Ticket usage by analyzing Event ID 4769 for RC4 encryption type (0x17) in environments enforcing AES, identifying tickets with abnormal lifetimes exceeding domain policy, correlating TGS requests with missing corresponding TGT requests (Event ID 4768), and detecting krbtgt password age anomalies. ## When to Use - When investigating security incidents that require detecting golden ticket forgery - 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 - Windows Domain Controller with Kerberos audit logging enabled - Splunk or Elastic SIEM ingesting Windows Security event logs - Python 3.8+ for offline event log analysis - Knowledge of domain Kerberos encryption policy (AES vs RC4) ## Steps 1. Audit domain Kerberos encryption policy to establish AES-only baseline 2. Forward Event IDs 4768 and 4769 to SIEM platform 3. Detect RC4 (0x17) encryption in TGS requests where AES is enforced 4. Identify TGS requests without corresponding TGT requests (forged ticket indicator) 5. Alert on ticket lifetimes exceeding MaxTicketAge domain policy 6. Monitor krbtgt account password age and last reset date 7. Correlate findings with host/user context for risk scoring ## Expected Output JSON report with Golden Ticket indicators including RC4 downgrades, orphaned TGS requests, abnormal ticket lifetimes, and risk-scored alerts with MITRE ATT&CK technique mapping.
Related Skills
More skills in Security & Compliance
1password
Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in, and reading/injecting secrets for commands.
1password
Set up and use 1Password CLI for sign-in, desktop integration, and reading or injecting secrets.
Accessibility Lead
Accessibility team lead and orchestrator. Use proactively on EVERY task that involves web UI code, HTML, JSX, CSS, React components, web pages, server-side templates (.leaf, .ejs, .erb, .hbs), or any user-facing web content. This agent coordinates the accessibility specialist team and ensures no accessibility requirement is missed. Runs the final review before any UI code is considered complete. Applies to any web framework, server-side templating framework (Vapor/Leaf, Rails/ERB, Django/Jinja, Express/EJS), or vanilla HTML/CSS/JS. Works alongside other team leads (e.g., swift-lead) in multi-language projects.
Accessibility Regression Detector
Detects accessibility regressions by comparing audit results across commits/branches. Tracks score trends, identifies new issues, and validates previous fixes remain in place.
Accessibility Statement
Generates conformance/accessibility statements following W3C or EU model templates. Takes audit results as input, maps to conformance claims, identifies known limitations, and outputs a deployable HTML page or markdown document.
Accessibility Tool Builder
Expert in building accessibility scanning tools, rule engines, document parsers, report generators, and audit automation. WCAG criterion mapping, severity scoring, CLI/GUI scanner architecture, CI/CD integration.
Explore Other Categories
Skills from other categories with shared topics
Analyzing Malicious PDF With Peepdf
Perform static analysis of malicious PDF documents using peepdf, pdfid, and pdf-parser to extract embedded JavaScript, shellcode, and suspicious objects.
Analyzing PDF Malware With Pdfid
Analyzes malicious PDF files using PDFiD, pdf-parser, and peepdf to identify embedded JavaScript, shellcode, exploits, and suspicious objects without opening the document. Determines the attack vector and extracts embedded payloads for further analysis. Activates for requests involving PDF malware analysis, malicious document analysis, PDF exploit investigation, or suspicious attachment triage.
Building Devsecops Pipeline With GitLab CI
Design and implement a comprehensive DevSecOps pipeline in GitLab CI/CD integrating SAST, DAST, container scanning, dependency scanning, and secret detection.