Hunting For Supply Chain Compromise

---
name: hunting-for-supply-chain-compromise
description: Runs a hypothesis-driven threat hunt for supply-chain compromise (T1195) by querying SIEM/EDR logs for trojanized software updates, compromised dependencies, unauthorized code modifications, and tampered build artifacts. Use when hunting after threat intel flags a compromised vendor/dependency, scoping a build-pipeline compromise, or reviewing update/build integrity.
domain: cybersecurity
subdomain: threat-hunting
tags:
- threat-hunting
- mitre-attack
- supply-chain
- initial-access
- t1195
- proactive-detection
version: '1.0'
author: mahipal
license: Apache-2.0
d3fend_techniques:
- Platform Hardening
- Restore Object
- Restore Software
- Software Update
- Asset Inventory
nist_csf:
- DE.CM-01
- DE.AE-02
- DE.AE-07
- ID.RA-05
mitre_attack:
- T1046
- T1057
- T1082
- T1083
- T1195
---

# Hunting For Supply Chain Compromise

## When to Use

- When proactively hunting for indicators of hunting for supply chain compromise 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 |
|---------|-------------|
| T1195.001 | Compromise Software Dependencies |
| T1195.002 | Compromise Software Supply Chain |
| T1199 | Trusted Relationship |

## 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**: SolarWinds-style update mechanism compromise
2. **Scenario 2**: Compromised npm/PyPI package with backdoor
3. **Scenario 3**: Tampered build server deploying malicious artifacts
4. **Scenario 4**: Vendor VPN software update delivering malware

## Output Format

```
Hunt ID: TH-HUNTIN-[DATE]-[SEQ]
Technique: T1195.001
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]
```