# Detecting Kerberoasting Attacks

> Detect Kerberoasting attacks by monitoring for anomalous Kerberos TGS

Detect Kerberoasting attacks by monitoring for anomalous Kerberos TGS

- Page: https://ss33.ai/skills/mukul975/detecting-kerberoasting-attacks-60123495322
- Publisher: mukul975
- Category: [Security](https://ss33.ai/skills/category/security-w9g95g) › [Threat intel & forensics](https://ss33.ai/skills/category/security-w9g95g/threat-intel-and-forensics-rt4m7u)
- License: Apache-2.0
- Source: https://github.com/mukul975/anthropic-cybersecurity-skills/blob/54a798831d2266a3ca61ce68a7acb80b81160d57/skills/detecting-kerberoasting-attacks/SKILL.md

## Skill

SKILL.md: https://ss33.ai/api/v1/ss33/download/mukul975/detecting-kerberoasting-attacks-60123495322

# 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]
```