What is software composition analysis (SCA)?

SCA focuses on risks inherited from external components rather than flaws in proprietary application logic. It can identify both direct dependencies and transitive dependencies introduced through other packages, helping teams understand what third-party software is present and where known risks may enter a product.

Software composition analysis gives teams visibility into the open-source and third-party software included in an application. It identifies packages, libraries, frameworks, and other dependencies, determines their versions, and connects that inventory with information such as known vulnerabilities and license metadata.

This matters because modern applications often depend on software that the development team did not write. A direct package can also bring in its own dependencies, creating a much larger dependency tree.

SCA is therefore part of software supply-chain security. It shows which risks may be inherited from external components, but it does not replace testing of proprietary code or prove that every reported vulnerability is exploitable.

For more context on third-party software risk, see Supply Chain Attacks.

SCA typically starts by building an inventory of the components used by an application. Depending on the tool and environment, it may inspect manifests, lockfiles, source repositories, build artifacts, containers, or an existing software bill of materials.

A typical process includes:

1. Identify components. Detect packages, libraries, and direct or transitive dependencies.
2. Determine names and versions. Identify components precisely enough to match them with external data.
3. Build or consume an inventory. Represent the component list internally or through an SBOM.
4. Match components with risk data. Compare components with known vulnerability and license information.
5. Report findings. Show affected dependencies and possible remediation options.

Detection methods vary between SCA tools. Scanning source manifests can also provide a different inventory from analyzing the artifact that is actually built and shipped.

SCA primarily identifies risks and metadata associated with third-party software components.

SCA can match component versions with databases of publicly known vulnerabilities. A match means the component requires investigation, not that the vulnerability is necessarily exploitable in the application.

Direct dependencies are packages explicitly added to a project. Transitive dependencies are introduced through those packages. Identifying both helps reveal risks several levels down the dependency tree.

SCA tools can report licenses associated with third-party components and flag conditions that may require review. This data can support compliance processes, but it is not a substitute for legal assessment.

Some SCA systems also identify outdated, deprecated, unsupported, or end-of-life packages. Coverage depends on the tool, ecosystem, and available package metadata.

SCA and Static Application Security Testing (SAST) examine different sources of application risk.

SCA analyzes open-source and third-party components. It identifies which external dependencies are present and whether known security or license risks are associated with them.

SAST analyzes application source code for security weaknesses in the code itself, such as unsafe data handling or vulnerable coding patterns.

The distinction matters because secure proprietary code can still rely on a vulnerable dependency, while software with up-to-date dependencies can contain flaws in its own code. The two approaches therefore complement each other rather than replace one another.

Learn more about SAST here:

A software bill of materials and SCA are closely related, but they serve different purposes.

An SBOM is a structured inventory of the components and dependencies in a software product. It records what the software contains.

SCA is an analysis process that identifies components and connects them with security, license, and dependency-risk information. SCA tools may generate an SBOM, consume an existing SBOM, or use component inventory data for further analysis.

The simplest distinction is: an SBOM is the inventory; SCA is the analysis.

Having an SBOM does not mean that component risks are continuously assessed, just as running SCA does not remove the need for an accurate component inventory.

SCA can run during development, on pull or merge requests, in CI/CD pipelines, during builds, and against deployed software.

Earlier scanning can help teams address dependency issues before release, while analysis of built artifacts can verify what actually ships. SCA also needs to be repeated because dependency risk changes over time. A component that had no known vulnerability at release may later be linked to a newly disclosed issue.

For this reason, SCA often becomes part of broader DevSecOps practices rather than a one-time pre-release check.

SCA depends on accurate component identification and reliable vulnerability data, so findings still need context before teams decide what to remediate.

Component inventories can be incomplete, especially when source manifests do not fully represent what ships in the final artifact. Transitive dependencies can create large numbers of findings, while differences in package names, versions, or vulnerability data can produce false positives or ambiguous matches.

A reported vulnerable dependency is also not automatically exploitable. The affected function may never be called, the vulnerable code path may be unreachable, or required conditions may not exist in the application. Reachability analysis can help prioritize findings, but its accuracy depends on the tool and technology stack.

SCA also does not identify every flaw in proprietary code, architecture, configuration, or business logic. It is one part of application and supply-chain security, not a complete security assessment.