About

Imported from mukul975/anthropic-cybersecurity-skills (skills/performing-supply-chain-attack-simulation/SKILL.md). Install upstream with npx skills add mukul975/anthropic-cybersecurity-skills --skill performing-supply-chain-attack-simulation. Copyright stays with the author (Apache-2.0).

Performing Supply Chain Attack Simulation

Name: performing-supply-chain-attack-simulation
Author: mukul975

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

Prerequisites

Python 3.9+ with pip-audit, Levenshtein, requests
Access to PyPI JSON API (https://pypi.org/pypi/{package}/json)
Network access for package metadata retrieval

Legal Notice: This skill is for authorized security testing and educational purposes only. Unauthorized use against systems you do not own or have written permission to test is illegal and may violate computer fraud laws.

Key Detection Areas

Typosquatting — compare package names against top PyPI packages using edit distance thresholds
Dependency confusion — check if internal package names exist on public PyPI with higher version numbers
Hash verification — download packages and verify SHA-256 digests match published hashes
Vulnerability scanning — audit installed packages against OSV and PyPA advisory databases
Metadata anomalies — flag packages with suspicious author emails, missing homepages, or very recent first upload dates

Output

JSON report with risk scores per package, detected attack vectors, hash verification results, and CVE findings.

Use it

Copy one of these into your project. Installing also returns the manifest and these snippets.

yaml

targets:
  - https://api.opensmartroute.ai/api/v1/registry/mukul975-anthropic-cybersecurity-skills-performing-suppl-8eb666/manifest   # or paste the manifest below

Manifest

An Open Capability Manifest: the router reads it to know what this does, what it costs and when to pick it.

mukul975-anthropic-cybersecurity-skills-performing-suppl-8eb666.ocm.jsonjson

{
  "ocm": "1",
  "id": "mukul975-anthropic-cybersecurity-skills-performing-suppl-8eb666",
  "kind": "skill",
  "name": "performing-supply-chain-attack-simulation",
  "description": "Simulates and detects software supply chain attacks: typosquatting detection via Levenshtein distance against popular PyPI package names, dependency confusion testing against private registries, SHA-256 package hash verification, and known-CVE scanning with pip-audit. Use when auditing a project's dependencies for malicious or confused packages, or when assessing package-registry supply-chain risk.",
  "publisher": "mukul975",
  "version": "1.0.0",
  "capabilities": {
    "domains": [
      "general"
    ],
    "tags": [
      "skill-md",
      "supply-chain",
      "typosquatting",
      "dependency-confusion",
      "package-verification",
      "pip-audit",
      "pypi",
      "software-composition-analysis",
      "skills-sh"
    ],
    "languages": [
      "en"
    ]
  },
  "quality_prior": 0.6,
  "examples": [
    "Simulates and detects software supply chain attacks: typosquatting detection via Levenshtein distance against popular PyPI package names, dependency confusion testing against private registries, SHA-256 package hash verification, and known-CVE scanning with pip-audit. Use when auditing a project's dependencies for malicious or confused packages, or when assessing package-registry supply-chain risk."
  ],
  "primary": false,
  "metadata": {
    "source": {
      "provider": "skills.sh",
      "repository": "https://github.com/mukul975/anthropic-cybersecurity-skills",
      "path": "skills/performing-supply-chain-attack-simulation/SKILL.md",
      "ref": "HEAD",
      "url": "https://github.com/mukul975/anthropic-cybersecurity-skills/blob/HEAD/skills/performing-supply-chain-attack-simulation/SKILL.md",
      "key": "mukul975/anthropic-cybersecurity-skills/skills/performing-supply-chain-attack-simulation/SKILL.md"
    },
    "license": "Apache-2.0"
  },
  "instructions": "# Performing Supply Chain Attack Simulation\n\n## Overview\n\nSoftware 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 vuln",
  "cost": {
    "context_tokens": 506
  }
}

Fetch it by URL: GET /api/v1/registry/mukul975-anthropic-cybersecurity-skills-performing-suppl-8eb666/manifest?version=1.0.0

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