detecting-service-account-abuse

$npx mdskill add mukul975/Anthropic-Cybersecurity-Skills/detecting-service-account-abuse

Detect service account abuse via anomalous logins and privilege escalation.

  • Identifies suspicious patterns like interactive logins and unauthorized access.
  • Integrates with EDR, SIEM, Sysmon, and Windows Security Event Logs.
  • Correlates threat intelligence feeds to validate detection hypotheses.
  • Delivers actionable alerts for incident response and threat hunting.
SKILL.md
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---
name: detecting-service-account-abuse
description: Detect abuse of service accounts through anomalous interactive logons, privilege escalation, lateral movement, and unauthorized access patterns.
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
---

# 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]
```
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