Skills Development Detecting Pass-The-Ticket

Detecting Pass-The-Ticket

v20260317
detecting-pass-the-ticket-attacks
Analyze Windows Event IDs 4768, 4769, and 4771 within Splunk or Elastic SIEM to identify anomalous Kerberos ticket usage, RC4 downgrades, and unusual service requests, enabling proactive Pass-the-Ticket threat detection.
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Overview

Detecting Pass-the-Ticket Attacks

Overview

Pass-the-Ticket (PtT) is a credential theft technique (MITRE ATT&CK T1550.003) where adversaries steal Kerberos tickets (TGT or TGS) from one system and replay them on another to authenticate without knowing the user's password. This skill teaches detection of PtT attacks by correlating Windows Security Event IDs 4768 (TGT request), 4769 (TGS request), and 4771 (pre-authentication failure) for anomalies such as ticket reuse across different hosts, RC4 encryption downgrades, and unusual service ticket request volumes.

Prerequisites

  • Windows Domain Controller with advanced audit policy enabled (Audit Kerberos Authentication Service, Audit Kerberos Service Ticket Operations)
  • Splunk or Elastic SIEM ingesting Windows Security event logs
  • Sysmon deployed on endpoints for supplementary process telemetry
  • Python 3.8+ with requests library

Steps

  1. Enable Kerberos audit logging on Domain Controllers via Group Policy
  2. Forward Event IDs 4768, 4769, and 4771 to SIEM platform
  3. Deploy detection rules for RC4 encryption downgrade (TicketEncryptionType 0x17)
  4. Create correlation rule for ticket reuse across multiple source IPs
  5. Build baseline of normal TGS request volume per user/host
  6. Alert on standard deviation anomalies in ticket request patterns
  7. Investigate flagged events with enrichment from Active Directory

Expected Output

JSON report containing detected PtT indicators including anomalous ticket requests, RC4 downgrades, cross-host ticket reuse events, and risk-scored users with MITRE ATT&CK technique mapping.

Info
Category Development
Name detecting-pass-the-ticket-attacks
Version v20260317
Size 8.99KB
Updated At 2026-03-18
Language