How Snyk calculates direct versus transitive dependency v...
Snyk splits vulnerability exposure into direct and transitive dependencies using lockfile graphs, CVE version-range matching, and path-level reachability analysis.
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Snyk splits vulnerability exposure into direct and transitive dependencies using lockfile graphs, CVE version-range matching, and path-level reachability analysis.
A technical walkthrough of how Snyk's reachability analysis builds static call graphs to determine whether vulnerable dependency functions are actually invoked by your code.
Snyk's reachability analysis works differently across Java, JavaScript, and Python — here's why static, typed Java gets deeper coverage than dynamic Python and JS call graphs.
How Snyk's Priority Score blends CVSS severity, exploit maturity, and reachability analysis into a single 1-1000 vulnerability ranking score.
How Snyk's 0-1000 Risk Score starts from the CVSS impact subscore formula, then layers in exploit maturity, social trends, and reachability data.
Snyk Advisor scores packages 0-100 using four signals: popularity, maintenance, community, and security. Here is exactly how each one is calculated.
How Snyk's research team detects malicious and typosquatted open-source packages — from name-similarity heuristics to install-script analysis and source-code provenance checks.
A technical look at how Snyk detects dependency confusion attacks — from vulnerability database malicious-package flags to registry scoping and Advisor scoring.
How Snyk structures its default license policy—severity tiers, unknown-license handling, and PR enforcement—and the concrete steps to customize it for your org.
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