xalgord 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
Detection Gaps & Validation
- AES roasting evades RC4-only rules. The classic signal is 4769 with
TicketEncryptionType=0x17(RC4) andTicketOptions=0x40810000, but modern Rubeus supports/aesto request AES (0x12/0x11) tickets that bypass any RC4-only detection. Also alert when an account that normally authenticates with AES suddenly requests RC4. - Audit subcategory must be on. No 4769 is produced unless "Audit Kerberos Service Ticket Operations" is enabled on DCs — verify with
auditpol /get /subcategory:"Kerberos Service Ticket Operations". - Volume drowns the signal. 4769 fires on every service access. Filter
ServiceName != krbtgt, drop machine ($) accounts and known SPNs, then threshold on many distinct SPNs requested by one account in a short window. - Targeted roasting hides under thresholds. A single high-value SPN roast won't trip a count rule — keep a separate low-volume rule for RC4 requests against sensitive service accounts.
- AS-REP roasting is a different path: hunt 4768 with
PreAuthType=0(0x17) for accounts flagged DONT_REQ_PREAUTH. - Validate the rule fires: run
Rubeus.exe kerberoastor ImpacketGetUserSPNs.pyagainst a lab SPN and confirm the 0x17 burst query returns it. - Tune false positives: legacy apps and older SQL Server SPNs legitimately use RC4. Allowlist those specific SPNs rather than ignoring RC4 entirely.
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
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]