Software composition analysis (SCA)

Software composition analysis (SCA) is an application security practice used to identify open-source and third-party libraries within a codebase and detect known security vulnerabilities in those software components. It helps organizations understand what their applications are built from and where security risks may exist.

SCA has become a core part of modern cybersecurity because most applications rely heavily on open-source software, package managers, and external dependencies. As software supply chains grow more complex and supply chain attacks increase, maintaining visibility into dependencies is essential for effective risk management and a strong security posture.

What is software composition analysis?

Software composition analysis is the process of discovering the components that make up an application, identifying their versions, and comparing them against vulnerability intelligence sources such as the National Vulnerability Database (NVD).

In practice, SCA answers a simple but critical question: “What third-party code are we running, and is any of it known to be vulnerable?” Analysis may include:

• Open-source code from public repositories such as GitHub
• Third-party libraries and packages managed through package managers
• Transitive dependencies introduced by other components

By mapping these dependencies and linking them to known security vulnerabilities, SCA enables vulnerability detection at scale and supports broader vulnerability management efforts.

Why SCA matters more now

Modern development teams rarely build everything from scratch. Instead, they assemble applications using reusable components and libraries from open-source projects across a growing ecosystem. While this accelerates the development process, it also introduces open-source risk as well as potential legal risk related to licensing issues and open-source licenses.

At the same time, the volume of disclosed vulnerabilities continues to grow. A dependency that was safe yesterday can become a critical issue overnight as new entries appear in the NVD. SCA is essential because it can:

• Provide visibility into software components across the SDLC
• Help security teams quickly identify exposure to newly disclosed vulnerabilities
• Support software supply chain security and reduce the impact of supply chain attacks
• Enable license compliance and help manage compliance issues tied to open-source license obligations

In the context of a wider application security program, SCA should be seen as a continuous capability for managing software supply chain security risks. Because new vulnerabilities are being disclosed all the time, effective SCA requires ongoing monitoring and real-time updates rather than one-time scans.

How SCA works

SCA solutions analyze applications to build an inventory of open-source components and dependencies, then match them against vulnerability intelligence sources to check if CVEs have been reported for them. Depending on the approach and specific tools used, software composition analysis tools may:

• Analyze source code, manifests, and binary artifacts in repositories
• Inspect container images and cloud-native workloads
• Integrate into the development workflow, including IDEs, pull requests, and CI/CD pipelines

The SCA process typically includes:

• Discovering and identifying software components and their versions
• Mapping dependency relationships, including transitive dependencies
• Matching components against vulnerability databases
• Identifying known security vulnerabilities and potential licensing issues
• Providing remediation guidance and policy enforcement options

Many SCA solutions also support software bill of materials (SBOM) generation in standardized formats such as SPDX to give organizations a structured and audit-ready record of their software components.

Static SCA vs. dynamic SCA

There are two main approaches to software composition analysis: static and dynamic. Each plays a distinct role in modern DevSecOps and DevOps environments.

• Static SCA analyzes source code, manifests, and dependency files in repositories during the development process. It is commonly integrated into CI/CD pipelines and supports shift-left security by identifying issues early in the software development lifecycle (SDLC).
• Dynamic SCA identifies components and technologies in running applications, including those deployed in cloud-native environments. This approach provides runtime context and helps reduce false positives by focusing on components that are actually present and exposed. It can also catch dynamic dependencies that are only pulled in at runtime and be combined with runtime tech stack security checks.

The two approaches work towards the same goal and are complementary. Static SCA provides broad visibility into declared open-source libraries across the codebase, while dynamic SCA adds real-world context by focusing on deployed applications and the components that are actually in use. Using both together gives development teams and security teams a more accurate view of open-source security risks.

What SCA can and cannot find

SCA is an effective best practice for catching certain classes of security risk, but it also has some clear limitations to keep in mind. Most importantly, SCA doesn’t perform code or behavior security checks but rather focuses on identifying components and checking if they have been reported as vulnerable.

What SCA can find

• Known vulnerable components in open-source software and third-party libraries
• Outdated or unsupported dependencies
• Dependency relationships across the application ecosystem
• Licensing issues, including open-source license obligations and legal risk
• Component inventories for SBOM and compliance reporting

What SCA cannot find

• Vulnerable components that are not yet listed in vulnerability databases, including zero-day risks
• Unreported vulnerabilities in custom application code

How SCA fits with DAST, SAST, and other AppSec testing

Software composition analysis is an important part of any comprehensive application security approach, alongside static and dynamic testing:

• SCA checks if the building blocks of your applications are safe to use.
• Static application security testing (SAST) checks your source code for vulnerabilities during development.
• Dynamic application security testing (DAST) tests your running applications and APIs for externally observable issues.

These methods complement each other. For example, SCA may identify vulnerable dependencies, while DAST can help determine whether those vulnerabilities are exploitable in a live application. Combining all three approaches improves your coverage and security prioritization across the SDLC.

Best practices for using SCA effectively

To get meaningful value from SCA, organizations should integrate it into their development workflow and treat it as an ongoing process to:

• Automate SCA scans within CI/CD pipelines and DevOps processes
• Integrate SCA into IDEs and pull requests to support shift-left security
• Monitor container images and deployed applications for real-time exposure
• Maintain up-to-date inventories of software components across repositories
• Use policy enforcement to manage license compliance and security risks
• Combine static and dynamic SCA to reduce false positives and improve accuracy
• Support SBOM initiatives and software supply chain security efforts

On the Invicti Platform, static and dynamic SCA are provided alongside DAST, SAST, API security testing, and a host of other integrated security tools to help organizations streamline their AppSec program and gain unified visibility into application and supply-chain risk.

To learn more about how Invicti brings together static and dynamic SCA with DAST, SAST, API security, SBOM generation, and other testing approaches on a unified platform, see the Invicti Platform overview.