Hunting For Supply Chain Compromise
SkillMonitoring & opsLets your agent hunt security logs for signs that software updates or dependencies were tampered with.
Then ask your AI: use the Hunting For Supply Chain Compromise skill
Details
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; Ahel provides instructions and does not run this skill.
No other account needed.
Add it as a step in a pipeline you build on Ahel, or connect Ahel to Claude, ChatGPT, Cursor, Claude Code or Codex and ask your AI to use it.
About this skill
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, scop
What this skill tells your AI
The instructions your AI receives, as published by mukul975/anthropic-cybersecurity-skills in skills/hunting-for-supply-chain-compromise/SKILL.md and read by Ahel’s review.
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
- 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 |
|---|---|
| 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
- Scenario 1: SolarWinds-style update mechanism compromise
- Scenario 2: Compromised npm/PyPI package with backdoor
- Scenario 3: Tampered build server deploying malicious artifacts
- 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]
Signals
- GitHub stars
- 34k
- Forks
- 4k
- Last commit
- Aug 2026
Advanced
- Item type
- skill
- Key
hunting-for-supply-chain-compromise- Source
- github.com/mukul975/anthropic-cybersecurity-skills
github.com/mukul975/anthropic-cybersecurity-skills
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