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Supply Chain Risk

Package, dependency & exploit risk

Supply Chain Risk audits open-source packages for known vulnerabilities, exploited CVEs, and dependency exposure across every major ecosystem — npm, PyPI, Maven, Go, Cargo, NuGet, RubyGems, and more. It turns a package name and version into a clear risk score in seconds.

Security teams and developers use it to triage dependency risk before shipping, catch vulnerabilities in pull requests, and investigate specific advisories. Each package audit returns a deterministic 0–100 risk score, severity breakdown, CISA KEV hits, EPSS exploitability probability, provenance checks, OpenSSF Scorecard health, fixed versions, and vulnerable dependency paths — everything you need to make a go/no-go call.

What you can do

  • package_risk — full security audit for one exact package version with risk score, advisories, and fix recommendations
  • batch_risk — rank up to 10 packages by risk in one call — great for triaging a dependency list
  • dependency_graph — fetch the full dependency tree for a package with per-node vulnerability counts and vulnerable paths
  • advisory_details — look up a specific CVE, GHSA, or OSV advisory by ID for full details

Who it's for

Security engineers, developers, and DevSecOps teams who need to understand and communicate dependency risk. Also useful for anyone doing vendor due diligence or supply chain compliance work.

How to use it

  1. Use package_risk with a package URL like pkg:npm/lodash@4.17.20 to get an instant risk score and advisory list
  2. For a list of dependencies, use batch_risk to get a ranked table sorted by descending risk
  3. Use dependency_graph to see which transitive dependencies are vulnerable and which direct upgrades would fix the most paths
  4. When you see a CVE or GHSA ID in results, use advisory_details to open the full record

Getting started

No setup needed — all four skills work immediately with no credentials required.

Package Risk

Assess the security risk of one exact package version. Returns advisories, severity counts, KEV hits, exploitability signals, provenance, repository health, fixed versions, and a deterministic risk score.

Returns: Risk score, severity breakdown, KEV hits, package metadata, and paginated advisory details for one package version
Batch Risk Audit

Audit up to 10 exact package versions in one request. Returns a sortable table with risk scores, advisory counts, KEV hits, exploitability signals, provenance, and repository health.

Returns: A ranked table of package versions with risk scores, advisory counts, KEV hits, and severity breakdowns
Dependency Graph

Fetch the dependency graph for one package version on ecosystems supported by deps.dev. Returns direct and transitive dependencies with per-node vulnerability counts from OSV, plus vulnerable paths and remediation candidates.

Returns: Dependency graph nodes with direct or indirect relation types, vulnerable paths, and remediation candidates
Advisory Details

Open a single advisory by ID. Works well for GHSA, CVE, and ecosystem-specific IDs and returns aliases, affected packages, fixed versions, KEV status, exploitability, and GitHub-reviewed metadata when available.

Returns: One advisory record with aliases, affected packages, fixed versions, KEV enrichment, exploitability, and source metadata when available
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v0.022026-03-27
  • Initial release with package_risk, batch_risk, dependency_graph, and advisory_details
v0.012026-03-27
  • Added exploitability enrichment via FIRST EPSS and GitHub global advisories
  • Added deps.dev provenance and related-project metadata plus OpenSSF Scorecard repository health
  • Added dependency remediation candidates and vulnerable path summaries

Supply Chain Risk Use Cases(3)

Browse all 3 Supply Chain Riskguides →
Open Analyse Dependency Graphs for Hidden Risk

Analyse Dependency Graphs for Hidden Risk

Map the full dependency tree for any npm package and identify risky transitive dependencies buried in the graph.

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Open Analyze App Review Sentiment

Analyze App Review Sentiment

Understand how users feel about your app by analyzing sentiment patterns across hundreds or thousands of reviews.

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See every Supply Chain Riskuse case (Claude, ChatGPT, Copilot, OpenClaw guides) →

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