Detecting Kerberoasting Attacks

When to Use

• When proactively hunting for indicators of detecting kerberoasting attacks in the environment
• After threat intelligence indicates active campaigns using these techniques
• During incident response to scope compromise related to these techniques
• When EDR or SIEM alerts trigger on related indicators
• During periodic security assessments and purple team exercises

Prerequisites

• EDR platform with process and network telemetry (CrowdStrike, MDE, SentinelOne)
• SIEM with relevant log data ingested (Splunk, Elastic, Sentinel)
• Sysmon deployed with comprehensive configuration
• Windows Security Event Log forwarding enabled
• Threat intelligence feeds for IOC correlation

Workflow

1. Formulate Hypothesis: Define a testable hypothesis based on threat intelligence or ATT&CK gap analysis.
2. Identify Data Sources: Determine which logs and telemetry are needed to validate or refute the hypothesis.
3. Execute Queries: Run detection queries against SIEM and EDR platforms to collect relevant events.
4. Analyze Results: Examine query results for anomalies, correlating across multiple data sources.
5. Validate Findings: Distinguish true positives from false positives through contextual analysis.
6. Correlate Activity: Link findings to broader attack chains and threat actor TTPs.
7. Document and Report: Record findings, update detection rules, and recommend response actions.

Key Concepts

Tools & Systems

Common Scenarios

1. Scenario 1: Rubeus kerberoast targeting all SPN accounts
2. Scenario 2: GetUserSPNs.py from Impacket requesting RC4 tickets
3. Scenario 3: Targeted kerberoast against high-privilege service accounts
4. Scenario 4: AS-REP roasting accounts without pre-authentication

Output Format

Hunt ID: TH-DETECT-[DATE]-[SEQ]
Technique: T1558.003
Host: [Hostname]
User: [Account context]
Evidence: [Log entries, process trees, network data]
Risk Level: [Critical/High/Medium/Low]
Confidence: [High/Medium/Low]
Recommended Action: [Containment, investigation, monitoring]

Verification Criteria

Confirm successful execution by validating:

• [ ] All prerequisite tools and access requirements are satisfied
• [ ] Each workflow step completed without errors
• [ ] Output matches expected format and contains expected data
• [ ] No security warnings or misconfigurations detected
• [ ] Results are documented and evidence is preserved for audit

Compliance Framework Mapping

This skill supports compliance evidence collection across multiple frameworks:

• SOC 2: CC7.2 (Anomaly Detection), CC7.3 (Incident Identification)
• ISO 27001: A.12.4 (Logging & Monitoring), A.16.1 (Security Incident Management)
• NIST 800-53: SI-4 (System Monitoring), IR-4 (Incident Handling), RA-5 (Vulnerability Scanning)
• NIST CSF: DE.AE (Anomalies & Events), DE.CM (Continuous Monitoring), DE.DP (Detection Processes)

Claw GRC Tip: When this skill is executed by a registered agent, compliance evidence is automatically captured and mapped to the relevant controls in your active frameworks.

Deploying This Skill with Claw GRC

Agent Execution

Register this skill with your Claw GRC agent for automated execution:

# Install via CLI
npx claw-grc skills add detecting-kerberoasting-attacks

# Or load dynamically via MCP
grc.load_skill("detecting-kerberoasting-attacks")

Audit Trail Integration

When executed through Claw GRC, every step of this skill generates tamper-evident audit records:

• SHA-256 chain hashing ensures no step can be modified after execution
• Evidence artifacts (configs, scan results, logs) are automatically attached to relevant controls
• Trust score impact — successful execution increases your agent's trust score

Continuous Compliance

Schedule this skill for recurring execution to maintain continuous compliance posture. Claw GRC monitors for drift and alerts when re-execution is needed.