Detecting Service Account Abuse

---
name: detecting-service-account-abuse
description: Detect abuse of service accounts by hunting for anomalous interactive
  logons, privilege escalation, and lateral movement using EDR/SIEM telemetry
  (CrowdStrike Falcon, Microsoft Defender, Splunk, Elastic Security, Sysmon,
  Velociraptor) and Sigma detection rules. Use when hunting for service-account
  misuse or investigating a service account performing unexpected interactive
  logons.
domain: cybersecurity
subdomain: threat-hunting
tags:
- threat-hunting
- mitre-attack
- service-accounts
- privilege-escalation
- t1078
- proactive-detection
version: '1.0'
author: mahipal
license: Apache-2.0
d3fend_techniques:
- Restore Access
- Password Authentication
- Biometric Authentication
- Strong Password Policy
- Restore User Account Access
nist_csf:
- DE.CM-01
- DE.AE-02
- DE.AE-07
- ID.RA-05
mitre_attack:
- T1078.002
- T1021.001
- T1098.001
- T1550.002
---

# Detecting Service Account Abuse

## When to Use

- When proactively hunting for indicators of detecting service account abuse 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 |
|---------|-------------|
| T1078.002 | Domain Accounts |
| T1078.001 | Default Accounts |
| T1021 | Remote Services |

## 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**: Service account RDP to domain controller
2. **Scenario 2**: SQL service accessing file shares outside scope
3. **Scenario 3**: Backup service lateral movement off-hours
4. **Scenario 4**: Compromised svc with DA privileges used for DCSync

## Output Format

```
Hunt ID: TH-DETECT-[DATE]-[SEQ]
Technique: T1078.002
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]
```