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Commerce Security Authority
Category: Vulnerability and Software Security

Software Composition Analysis

Also known as: SCA, Component Analysis (software subset)
Simply put

Software Composition Analysis (SCA) is an automated process that scans an application's codebase to find the open source and third-party software components it uses. It then helps identify and manage risks in those components, such as known security vulnerabilities and software license obligations. It is intended to give teams visibility into code they did not write themselves but still depend on.

Formal definition

SCA is an automated cybersecurity technique that inventories and analyzes the open source and third-party software components within an application, then identifies and manages associated risks such as known vulnerabilities and license compliance obligations. As described by OWASP, SCA is a software-only subset of the broader practice of Component Analysis, with limited scope relative to that superset. Practitioners typically use SCA to build a component inventory, correlate components against vulnerability data, and surface licensing and management concerns; its coverage and accuracy depend on implementation and the completeness of the analyzed codebase.

Why it matters

Modern applications are assembled as much as they are written, drawing heavily on open source and third-party components that development teams did not author but still depend on. Software Composition Analysis matters because it gives teams visibility into that dependency layer, surfacing known vulnerabilities and license obligations in code that would otherwise remain unexamined. Without this visibility, an organization may unknowingly ship or operate software containing components with publicly disclosed weaknesses.

For payment and commerce environments, where handling of cardholder data and the integrity of transaction-processing software are subject to scrutiny, understanding the composition of an application supports broader vulnerability management and secure software practices. Note that PCI DSS, the PCI Software Security Framework, and related standards each address application security differently and evolve across versions; SCA is a technique that can inform such efforts but is not itself a compliance validation, and readers should confirm specific requirements against the current published standard.

SCA is intended to help reduce risk from vulnerable or non-compliant components, but it does not eliminate it. Its coverage and accuracy depend on implementation and the completeness of the analyzed codebase, and results may include false positives or miss components that are not detected. It addresses the third-party and open source portion of an application and does not, on its own, evaluate custom-written code or runtime behavior.

Who it's relevant to

Application security engineers
Security engineers use SCA to build and maintain an inventory of open source and third-party components and to correlate them against known vulnerability data. This helps them prioritize remediation of vulnerable dependencies, though they should account for the possibility of false positives and undetected components depending on the tool and codebase coverage.
Software development teams
Developers depend on SCA to gain visibility into code they did not write themselves but still rely on. Integrating component analysis into the development workflow can help teams identify vulnerable or license-encumbered components earlier, reducing the effort needed to address issues later.
Compliance and license management personnel
Beyond security vulnerabilities, SCA surfaces software license obligations associated with open source components. Personnel responsible for legal and license compliance use this output to identify and manage licensing concerns, recognizing that the analysis covers detected components and its completeness depends on implementation.
Payment application and product security teams
Teams building or maintaining software that handles payment or cardholder data can use SCA to inform broader secure-development and vulnerability-management practices. SCA is a supporting technique, not a compliance validation; teams should confirm applicable requirements against the current published PCI standards, which differ by standard and version.

Inside SCA

Dependency inventory
An enumeration of open-source and third-party components used by an application, including direct and transitive dependencies. This inventory is the foundation for identifying which components are subject to known vulnerabilities or license obligations.
Known vulnerability detection
Matching identified components and their versions against vulnerability data sources to flag components associated with publicly disclosed weaknesses. Results depend on the accuracy of component identification and the coverage and freshness of the underlying data, so both false positives and false negatives can occur.
License and compliance data
Information about the open-source licenses associated with identified components, used to help teams manage legal and policy obligations. This is a governance function distinct from vulnerability detection.
Software Bill of Materials (SBOM) support
The ability to generate or consume a structured list of components that make up an application. An SBOM supports transparency and downstream analysis but is a record of composition, not by itself an assurance that components are free of vulnerabilities.
Prioritization and risk context
Contextual signals such as severity ratings, reachability, or exploit availability that help teams triage findings. Prioritization is intended to focus remediation effort and is not a substitute for validating whether a finding is exploitable in the specific deployment.

Common questions

Answers to the questions practitioners most commonly ask about SCA.

Does SCA replace the need for other application security testing like SAST or DAST?
No. SCA focuses on identifying and assessing third-party and open-source components, their known vulnerabilities, and their licenses. It does not analyze custom-written code for flaws the way SAST does, nor does it test running applications the way DAST does. These approaches address different risks and are generally used together rather than as substitutes. Relying on SCA alone leaves gaps in coverage for first-party code defects.
Is running an SCA tool enough to satisfy PCI DSS software security expectations?
No single tool satisfies a standard by itself. PCI DSS addresses vulnerability management and secure software practices, and requirement numbering and wording differ between versions, so confirm the specifics against the current published standard. SCA can support component inventory and vulnerability identification activities, but it is one input among many. Software developed for sale or licensing may fall under separate standards such as PA-DSS or the PCI Software Security Framework, which have their own validation expectations. Using SCA does not by itself demonstrate compliance.
How do we build and maintain an accurate component inventory for SCA?
An accurate inventory typically starts by identifying all third-party and open-source dependencies, including transitive dependencies pulled in indirectly. Many teams generate a software bill of materials as part of the build pipeline so the inventory reflects what is actually shipped rather than what is assumed. Keeping the inventory current requires re-running analysis as dependencies change, since a point-in-time inventory drifts as libraries are added, updated, or removed.
Where should SCA be integrated in the development and deployment workflow?
SCA is commonly integrated into version control, continuous integration builds, and pre-deployment gates so component issues surface early and repeatedly. Placing checks in the pipeline helps catch newly introduced or newly disclosed vulnerabilities before release. Some teams also run periodic scans against deployed artifacts to catch vulnerabilities disclosed after a component was already shipped, since a component that was clean at build time may later be associated with a known vulnerability.
How should teams handle the false positives and false negatives that SCA can produce?
SCA results carry trade-offs. False positives can arise when a reported vulnerability affects a code path the application does not use, or when version matching is imprecise. False negatives can occur when a component is misidentified, bundled in a non-standard way, or when a vulnerability has not yet been disclosed in the data sources the tool relies on. Practical handling usually involves a triage process to validate findings, document justified exceptions, and avoid treating raw tool output as a final risk determination.
How do we prioritize remediation of the vulnerabilities SCA reports?
Prioritization generally considers factors such as severity, whether the vulnerable function is actually reachable in the application, exposure of the affected component, and availability of a fixed version. Because remediation capacity is limited, many teams combine vendor-provided severity ratings with their own context rather than treating every finding as equally urgent. Exact scoring depends on the source, period, and methodology, so document the basis used for prioritization decisions and revisit them as new information becomes available.

Common misconceptions

SCA is the same as or a replacement for other application security testing methods.
SCA focuses on identifying third-party and open-source components and their known issues. It does not analyze custom source code for defects the way static analysis does, nor does it test running applications the way dynamic testing does. These approaches address different risks and are typically complementary.
A clean SCA scan means the software is secure or automatically satisfies PCI DSS software security expectations.
SCA reports reflect only what the tool could identify against its data sources at scan time, and coverage varies. Where secure software development and component management are relevant, controls are governed by the applicable standard, such as PCI DSS or the PCI Software Security Framework, and readers should confirm the specific requirements against the current published standard rather than treating a scan result as validation.
An SBOM produced by SCA guarantees there are no vulnerable components.
An SBOM documents which components are present; it is a composition record, not an attestation of safety. Whether a listed component carries a known vulnerability still depends on version accuracy and the coverage and timeliness of the vulnerability data used for analysis.

Best practices

Maintain an up-to-date inventory of direct and transitive dependencies, since transitive components are a common source of overlooked exposure.
Run SCA continuously across the development lifecycle and in build pipelines rather than as a one-time check, because component vulnerability data changes over time.
Triage findings using contextual signals such as severity and reachability, and validate whether a flagged issue is exploitable in the specific deployment before treating remediation as complete.
Treat SCA as one layer alongside other application security testing and secure development controls, not as a standalone assurance of software security.
Manage open-source license and policy obligations as a distinct governance activity separate from vulnerability remediation.
Where component and software security controls are relevant to compliance, confirm the applicable requirements against the current published standard rather than assuming a scan result satisfies them.