Detect Kerberoasting attacks by monitoring for anomalous Kerberos TGS requests (Event ID 4769) targeting service accounts with SPNs, which attackers request offline to crack service account passwords.
Imported from mukul975/anthropic-cybersecurity-skills (skills/detecting-kerberoasting-attacks/SKILL.md). Install upstream with npx skills add mukul975/anthropic-cybersecurity-skills --skill detecting-kerberoasting-attacks. Copyright stays with the author (Apache-2.0).
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
Formulate Hypothesis: Define a testable hypothesis based on threat intelligence or ATT&CK gap analysis.
Identify Data Sources: Determine which logs and telemetry are needed to validate or refute the hypothesis.
Execute Queries: Run detection queries against SIEM and EDR platforms to collect relevant events.
Analyze Results: Examine query results for anomalies, correlating across multiple data sources.
Validate Findings: Distinguish true positives from false positives through contextual analysis.
Correlate Activity: Link findings to broader attack chains and threat actor TTPs.
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
Scenario 1: Rubeus kerberoast targeting all SPN accounts
Scenario 2: GetUserSPNs.py from Impacket requesting RC4 tickets
Scenario 3: Targeted kerberoast against high-privilege service accounts
Scenario 4: AS-REP roasting accounts without pre-authentication
Copy one of these into your project. Installing also returns the manifest and these snippets.
yaml
targets:
- https://api.opensmartroute.ai/api/v1/registry/mukul975-anthropic-cybersecurity-skills-detecting-kerber-31dd52/manifest # or paste the manifest below
Manifest
An Open Capability Manifest: the router reads it to know what this does, what it costs and when to pick it.
{
"ocm": "1",
"id": "mukul975-anthropic-cybersecurity-skills-detecting-kerber-31dd52",
"kind": "skill",
"name": "detecting-kerberoasting-attacks",
"description": "Detect Kerberoasting attacks by monitoring for anomalous Kerberos TGS requests (Event ID 4769) targeting service accounts with SPNs, which attackers request offline to crack service account passwords. Use when hunting for MITRE T1558 credential access activity or investigating suspected service account password cracking attempts in Active Directory Kerberos logs.",
"publisher": "mukul975",
"version": "1.0.0",
"capabilities": {
"domains": [
"general"
],
"tags": [
"skill-md",
"threat-hunting",
"mitre-attack",
"kerberoasting",
"credential-access",
"kerberos",
"t1558",
"proactive-detection",
"skills-sh"
],
"languages": [
"en"
]
},
"quality_prior": 0.6,
"examples": [
"Detect Kerberoasting attacks by monitoring for anomalous Kerberos TGS requests (Event ID 4769) targeting service accounts with SPNs, which attackers request offline to crack service account passwords. Use when hunting for MITRE T1558 credential access activity or investigating suspected service account password cracking attempts in Active Directory Kerberos logs."
],
"primary": false,
"metadata": {
"source": {
"provider": "skills.sh",
"repository": "https://github.com/mukul975/anthropic-cybersecurity-skills",
"path": "skills/detecting-kerberoasting-attacks/SKILL.md",
"ref": "HEAD",
"url": "https://github.com/mukul975/anthropic-cybersecurity-skills/blob/HEAD/skills/detecting-kerberoasting-attacks/SKILL.md",
"key": "mukul975/anthropic-cybersecurity-skills/skills/detecting-kerberoasting-attacks/SKILL.md"
},
"license": "Apache-2.0"
},
"instructions": "# Detecting Kerberoasting Attacks\n\n## When to Use\n\n- When proactively hunting for indicators of detecting kerberoasting attacks in the environment\n- After threat intelligence indicates active campaigns using these techniques\n- During incident response to scope compromise related to these techniques\n- When EDR or SIEM alerts trigger on related indicators\n- During periodic security assessments and purple team exercises\n\n## Prerequisites\n\n- EDR platform with process and network telemetry (CrowdStrike, MDE, SentinelOne)\n- SIEM with relevant log data ingested (Splunk, Elastic, Sentinel)\n- Sysmon de",
"cost": {
"context_tokens": 679
}
}
Fetch it by URL: GET /api/v1/registry/mukul975-anthropic-cybersecurity-skills-detecting-kerber-31dd52/manifest?version=1.0.0
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