What is Software Composition Analysis (SCA)?

With the world of software becoming increasingly complex and interconnected, it’s more important than ever before to scan a codebase for vulnerabilities before using it or integrating it into one’s own software.

A subset of application security testing, software composition analysis (SCA) refers to an automated process which scans open source software, allowing security analysts to identify precisely which libraries and components have been used in a piece of software. Code is parsed automatically and scanned against a known list of open source vulnerabilities.

Specifically, they can be used to inspect:

• Raw source code
• Containers
• Binaries
• Components of an operating system

SCA tools can either be self-standing or can be integrated into wider-ranging application testing solutions. For instance, one SCA tool may be used to identify what’s running on Linux workstations while another could be used in order to inspect finished binaries as they move through the DevOps process. They are also commonly used in order to create a bill of materials (BOM) for software developers. BOMs will list all the components used in a piece of software, allowing the security team to flag any potential vulnerabilities.

SCA tools can also be used to identify the licenses associated with any open source components integrated into a piece of delivered software. Open source doesn’t necessarily mean free, and by scanning codebases for licenses, developers can avoid costly fines and reputational damage.

Advantages of Software Composition Analysis(SCA)

Using an SCA tool in your organization’s development workflow can confer several advantages:

Licensing

Your organization can avoid costly fines which could be accrued by accidentally using open source components that require licenses which the organization has not taken out.

Vulnerability Management

The primary rationale for using technologies leveraging SCA is avoiding forking code that has known vulnerabilities. Using SCA tools, these can be quickly identified and, where possible, remediated. If a bug fix isn’t available or can’t be quickly deployed, the development team may decide to simply forego using that component altogether.

Bill of Materials

One of the main SCA benefits is the fact that by cataloging which open source components are used in a given piece of software it can be used to help collate a software bill of materials (SBOM). Sometimes, producing SBOMs is a regulatory requirement – or one asserted by potential customers.

How Software Composition Analysis (SCA) supports API security

SCA provides a code-level security assessment. In order to secure APIs and their endpoints, it can be helpful to know more about the services which are attempting to connect with them. This can be used, for example, to help identify malicious software or software with unresolved open source vulnerabilities flooding endpoints with requests.

Therefore, SCA tools can provide a useful component in a holistic strategy intended to protect APIs through preventing their unwanted use, degrading service availability for legitimate users.

Software Composition Analysis (SCA) vs SAST

On face value, SCA tools may sound a lot like SAST, or Static Application Security Testing, tools. However, they’re two distinct cybersecurity components with slightly different uses.

Some of the differences that mark the divide between SAST vs SCA:

• SAST tools are used to detect vulnerabilities in code is closed source. By contrast, software composition analysis tools specialize in flagging vulnerabilities in open source components.
• When it comes to prioritizing bug fixes, SCAs result in less developer headaches. This is because remediating open source vulnerabilities is relatively straightforward given that the overwhelming majority of known bugs have a fix. By contrast, remediating bugs detected in closed-source components can be more arduous work.
• Whereas SCA tools can run on software in a variety of formats – both before and after compilation – SAST tools typically run on source code.