Analysis & detection
What is SCA (Software Composition Analysis)?
Identifying third-party dependencies and matching them against known vulnerability databases.
SCA reads your manifests and lockfiles, builds a dependency tree including transitive packages, and cross-references it with advisory sources such as CVE, GHSA and vendor feeds. Most of a modern application is dependencies, so this is usually where the raw finding count lives.
The interesting variable is not whether a tool does SCA, nearly all do, but what it does with the volume. Reachability analysis, exploit-maturity signals and auto-remediation pull requests are what make the output actionable rather than a standing backlog.
Top 16 SCA (Software Composition Analysis) tools
Every tool in the directory documented as supporting SCA (Software Composition Analysis), 15 fully, 1 partially, with what its own documentation says.
Support is not the same as parity, since some implementations are narrower in scope, gated to a higher plan tier, or maintained only for existing customers. The note under each tool is what its own documentation describes.
- 1
Trivy scans 12+ package ecosystems with dependency-chain visualization and CVE/GHSA/CVSS metadata.
- 2AikidoCode Security Platform
Lockfile and dependency-tree scanning across 20+ package managers with chain visualization
- 3Checkmarx OneCode Security Platform
File analysis, package-manager or lock-file resolution, and evidence analysis against Checkmarx vulnerability databases.
- 4CodeAnt AIPR Review
Dependency vulnerability scanning with an SCA Scan Center for unified vulnerability tracking
- 5
OSV Scanner and Trivy in tool catalog; dedicated Dependencies scan requires Security add-on
- 6CorgeaCode Security Platform
Lockfile/manifest scanning across 25+ ecosystems with CVE/CVSS
- 7
Full transitive tree checked against NVD and other advisories, but billed pay-as-you-go per active dependency target on all plans.
- 8Gemini Code AssistAgent Coding Tool
Optional extension's /security:scan-deps runs OSV-Scanner against declared deps for known CVEs.
- 9
Dependency graph plus Dependabot alerts from the GitHub Advisory Database with CVE/GHSA, CVSS, CWE data
- 10GreptilePR Review
SCA scan type in Security Check reviews dependencies against known vulnerability databases for CVEs
- 11
OSV-Scanner and Trivy cover npm, Maven, PyPI, NuGet, Conan, CocoaPods and Swift ecosystems
- 12SemgrepCode Security Platform
Semgrep Supply Chain parses lockfiles/manifests for 13 languages; Dynamic Dependency Resolution beta scans without lockfiles.
- 13SnykCode Security Platform
Snyk Open Source builds full dependency graph including transitive deps against Snyk Vulnerability Database.
- 14
SCA is a separate product subscription, available only to Team and Enterprise plans.
- 15
Agent-based scan with quick, full and vulnerable-methods depths; direct vs transitive dependency graph
- 16
Vulnerability Scanner flags known vulnerabilities and outdated dependencies; beta, Team/Enterprise
What to look for
- Ecosystem coverage for your package managers, including transitive depth
- Whether fix guidance names a specific safe version
- Automatic upgrade pull requests, and how noisy they are
- Advisory freshness and whether the vendor curates beyond public feeds
Related terms
FAQ
What is SCA (Software Composition Analysis)?
Identifying third-party dependencies and matching them against known vulnerability databases.
How many tools support SCA (Software Composition Analysis)?
16 of the 20 tools tracked in this directory support SCA (Software Composition Analysis), 15 fully and 1 partially, including Codacy, Aikido, Checkmarx One, CodeAnt AI, CodeRabbit. Support is not the same as parity, since some implementations are narrower in scope, gated to a higher plan tier, or maintained only for existing customers. The note under each tool is what its own documentation describes.
What should you look for in SCA (Software Composition Analysis)?
Ecosystem coverage for your package managers, including transitive depth. Whether fix guidance names a specific safe version. Automatic upgrade pull requests, and how noisy they are. Advisory freshness and whether the vendor curates beyond public feeds.