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detecting-kerberoasting-attacks

Detect Kerberoasting attacks by monitoring for anomalous Kerberos TGS

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技能内容

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

| Concept | Description |

|---------|-------------|

| T1558.003 | Kerberoasting |

| T1558.004 | AS-REP Roasting |

| T1558.001 | Golden Ticket |

Tools & Systems

| Tool | Purpose |

|------|---------|

| CrowdStrike Falcon | EDR telemetry and threat detection |

| Microsoft Defender for Endpoint | Advanced hunting with KQL |

| Splunk Enterprise | SIEM log analysis with SPL queries |

| Elastic Security | Detection rules and investigation timeline |

| Sysmon | Detailed Windows event monitoring |

| Velociraptor | Endpoint artifact collection and hunting |

| Sigma Rules | Cross-platform detection rule format |

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]

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