Detecting Golden Ticket Attacks In Kerberos Logs

Detecting Golden Ticket Attacks In Kerberos Logs

Overview

Cybersecurity skill for detecting golden ticket attacks in kerberos logs. Follows industry best practices and security standards.

When to Use

Trigger phrases:

• "detecting golden ticket attacks in kerberos logs"

• "Detect Golden Ticket attacks in Active Directory by analyzing Kerberos TGT anoma"

• When KRBTGT account hash may have been compromised via DCSync or NTDS.dit extraction

• When hunting for forged Kerberos tickets used for persistent domain access

• After incident response reveals credential theft at the domain level

• When investigating impossible logon patterns (users logging in from multiple locations simultaneously)

• During post-breach assessment to determine if Golden Tickets are in use

When NOT to Use

• When you lack proper authorization for testing
• For production systems without change management
• When the task requires legal or compliance expertise beyond technical scope

Prerequisites

• Windows Security Event IDs 4768, 4769, 4771 on domain controllers
• Kerberos policy configuration knowledge (max ticket lifetime, encryption types)
• Domain controller audit policy enabling Kerberos Service Ticket Operations
• SIEM with ability to correlate Kerberos events across multiple DCs

Workflow

# Example: IOC detection
import re

IOC_PATTERNS = {
    "ip": r"\b(?:\d{1,3}\.){3}\d{1,3}\b",
    "domain": r"\b[a-z0-9-]+\.[a-z]{2,}\b",
    "hash_md5": r"\b[a-f0-9]{32}\b",
    "hash_sha256": r"\b[a-f0-9]{64}\b",
}

def extract_iocs(text: str) -> dict:
    return {k: re.findall(v, text) for k, v in IOC_PATTERNS.items()}

1. Define Detection Scope — Identify the specific golden ticket attacks in kerberos logs techniques or indicators to hunt. Map to MITRE ATT&CK tactics/techniques where applicable.
2. Collect Baseline Data — Gather historical logs and establish normal behavior patterns for golden ticket attacks in kerberos logs.
3. Build Detection Queries — Write detection rules, Sigma rules, or SIEM queries targeting golden ticket attacks in kerberos logs indicators.
4. Execute Hunts — Run queries against the collected data, starting with broad filters and narrowing down.
5. Triage Results — Investigate alerts, filter false positives, and validate findings against known-good behavior.
6. Document Findings — Record confirmed detections, IOCs, and affected systems. Update detection rules based on findings.

Tools

• SIEM Platform — Central log aggregation and query execution
• Sigma Rules — Vendor-agnostic detection rule format
• MITRE ATT&CK Navigator — Technique mapping and coverage analysis

Process

1. Reconnaissance — Gather target information, identify attack surface, enumerate services
2. Analysis/Exploitation — Execute the technique, analyze results, document findings
3. Reporting — Document IOCs, write findings, provide remediation recommendations

Verification

• All golden ticket attacks in kerberos logs procedures executed completely and documented
• Findings validated against multiple data sources
• False positives identified and filtered
• Results documented with evidence and timestamps
• Recommendations provided with risk-based prioritization

Anti-Rationalization Table