The Complete Guide to Software Composition Analysis

Software composition analysis (SCA) has emerged as an increasingly necessary tool to help organizations control risks that stem from the use of open source software. The sheer volume of OSS in modern applications — the average app uses 147 different open source components (which pull in even more dependencies) — makes it hard for organizations to stay on top of issues in areas like:

• Security
• Code quality
• License compliance
• Long-term project viability

Software composition analysis helps teams mitigate these risks by automating the discovery of vulnerabilities, licenses, and potential quality issues — then offering actionable insight to inform remediation. Finally, SCA tools also generally include capabilities that enable teams to apply security and license compliance policies at scale. (For example, an organization might use this functionality to flag anything with a GPL-licensed component across all builds.)

Many organizations pair software composition analysis (which can only be used with open source code) with tools for proprietary code (like SAST, DAST, IAST, and RASP) to form a complete suite of application security testing products.

Before diving into the specifics of how software composition analysis enables organizations to reduce risk associated with OSS, it's helpful to understand just how widespread OSS is in our modern world of application development.

• More than 90% of modern applications use at least some open source software.
• The average application uses 147 different open source components.
• Open source vulnerabilities continue to rise year over year.

This background brings into focus the importance of having an up-to-date, accurate understanding of the OSS components you use. Today's applications simply have so much open source that it can be easy to miss a license or vulnerability in a deep dependency.

SCA tools generally apply an "inventory, analyze, and control" framework to give teams a full view of their open source usage — and guidance on how to resolve any issues.

The three-step framework most SCA tools use to help organizations manage open source risk

1. Inventory

The road to managing OSS vulnerabilities starts with a comprehensive and accurate inventory of your dependencies. An organization can't address vulnerabilities or license compliance issues without understanding all of the components in its codebase.

2. Analyze

If the SCA tool detects a vulnerable library, it will disclose important contextual information like vulnerability description, affected version, CVSS score and severity, CVE and CWE identifications, and how the exploit was introduced into the code. It will also highlight any license compliance issues and show where licenses were discovered in your code.

3. Control

SCA solutions help organizations control open source risk by offering remediation guidance, including information on how best to upgrade the problematic OSS component. Users can also implement deny/flag/approve policies for different components to ensure an optimal risk posture.

Organizations across every industry and geographic region use software applications to fuel product development. Generally, these applications are built with many individual software components, often from a variety of open source and proprietary packages.

A software bill of materials (SBOM) gives individuals involved with the product (manufacturers, operators, buyers) full visibility into the software supply chain and any license compliance, security, and quality risks that may exist. SBOMs generally include a description of all proprietary and open source components that comprise the product, along with data such as:

• Supplier name
• Component name
• Version string
• Author name
• Summary of the involved open source licenses

The relationship between SCA and SBOMs has become increasingly important with the rise of software supply chain security concerns and new regulatory requirements. The U.S. government's 2021 cybersecurity executive order, for example, requires vendors to provide SBOMs for software sold to federal agencies.

Software composition analysis is just one of several security testing methodologies used in modern application development. Understanding how SCA differs from other security tools can help organizations build a comprehensive application security program.

While each of these security testing approaches has its strengths and limitations, they complement each other well in a comprehensive application security program. Many organizations implement a combination of these tools to achieve complete coverage across their application portfolio.

Given the popularity of open source software, there are many software composition analysis tools on the market today. However, best-in-class SCA solutions tend to have three key capabilities:

High Signal-to-Noise Ratio

Developer adoption is key for any SCA tool to have an impact. The best solutions:

• Minimize false positives: They should differentiate between vulnerability or license issues that actually impact security and compliance.
• Integrate with developer tools: SCA should work within existing developer ecosystems (e.g., GitHub, Jira).

CI/CD Integration

Effective SCA tools don't just flag security, license, and code quality issues — they allow teams to address them as early as possible in the software development lifecycle. Full CI/CD integration ensures continuous monitoring and prevents vulnerabilities from reaching production.

Automated Policy Governance

Organizations have different policies regarding OSS security and compliance risks. Automated, flexible policy engines let teams filter, approve/deny, and flag specific vulnerabilities and packages to maintain an optimal risk posture.

The world of open source software has evolved significantly, and SCA tools are no exception. The next generation of SCA solutions will focus on:

• Advanced policy engines: Allowing automated approvals and enforcement within workflows.
• Developer-friendly tools: Fully integrated into native workflows to encourage adoption.
• Code quality and provenance insights: Offering guidance on whether dependencies are from safe and trusted sources.
• Next-gen reporting: Providing detailed insights for both technical and non-technical stakeholders.
• AI and ML integration: Using artificial intelligence to better prioritize vulnerabilities, predict potential issues, and recommend remediation actions.
• Supply chain risk management: Going beyond direct dependencies to assess the entire software supply chain for security and compliance risks.

As software development continues to rely more heavily on open source components, the importance of robust SCA tools will only increase. Organizations that adopt advanced SCA solutions will be better positioned to manage the complex risks associated with modern software development.