name: detecting-kerberoasting-attacks description: Detect Kerberoasting attacks by monitoring for anomalous Kerberos TGS requests targeting service accounts with SPNs for offline password cracking. domain: cybersecurity subdomain: threat-hunting tags:

• threat-hunting
• mitre-attack
• kerberoasting
• credential-access
• kerberos
• t1558
• proactive-detection

version: '1.0' author: mahipal license: Apache-2.0 d3fend_techniques:

• Application Protocol Command Analysis
• Network Isolation
• Network Traffic Analysis
• Client-server Payload Profiling
• Network Traffic Community Deviation

nist_csf:

• DE.CM-01
• DE.AE-02
• DE.AE-07
• ID.RA-05

mitre_attack:

• T1046
• T1057
• T1082
• T1083
• T1003

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]