Individual skill
performing-supply-chain-attack-simulation
Simulate and detect software supply chain attacks including typosquatting detection via Levenshtein distance, dependency confusion testing against private registries, package hash verification with pip, and known vulnerability scanning with pip-audit.
internal/tools/skills/data/supply-chain-security/performing-supply-chain-attack-simulation/SKILL.md
Source commit d42f381ad34843e71a42658e5c57290c713e85af
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- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- Yes
- Repository scan complete
- No
- Skill scan complete
- Yes
- Observed behavior
- Network or broad shell
- Last checked
- Nov 7, 2026
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Repository context
- Repository stars (not skill ratings)
- 1,307
- Repository last updated
- Nov 5, 2026
- License
- Apache-2.0
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- cybersecurity Repository topic
- security Repository topic
- bug-bounty Repository topic
- automation Repository topic
- autonomous-pentesting Repository topic
- ai-agent Repository topic
- ai-security Repository topic
- ethical-hacking Repository topic
- golang Repository topic
- penetration-testing Repository topic
- supply-chain Declared skill tag
- typosquatting Declared skill tag
- dependency-confusion Declared skill tag
- package-verification Declared skill tag
- pip-audit Declared skill tag
- pypi Declared skill tag
- software-composition-analysis Declared skill tag
- security Derived category
- engineering Derived category
- operations Derived category
- testing Derived category
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SKILL.mdcore · 4,332 bytes
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# Performing Supply Chain Attack Simulation
## Overview
Software supply chain attacks exploit trust in package registries through typosquatting (registering names similar to popular packages), dependency confusion (publishing higher-version public packages matching private names), and compromised package distribution. This skill detects these attack vectors by computing Levenshtein distance between package names and popular PyPI packages, verifying package integrity via SHA-256 hash comparison, scanning for known CVEs with pip-audit, and testing dependency resolution order for confusion vulnerabilities.
## When to Use
- When conducting security assessments that involve performing supply chain attack simulation
- When following incident response procedures for related security events
- When performing scheduled security testing or auditing activities
- When validating security controls through hands-on testing
