In the past, the development of software was something that required a lot of effort and resources. Basically, every piece of code was developed in-house, and code reuse was quite limited. The situation is now the opposite. Open-source packages are so widely used that they make up the bulk of the total amount of software produced by passionate hobbyists and virtually all the software professionals in tech companies. The convenience of reusing and fine-tuning components made open-source is just too strong for most software engineers to ignore it and keep "reinventing the wheel".

To get a better idea of how big open source has become, we have some recent insights: according to a survey from Gartner, over 90% of the respondents stated that they rely on open source components. In another report from Synopsis, 98% of the audited codebases contained at least one open-source component, and 75% of the source code came from open-source. The report also noted that 85% of the audited codebases contained components "more than four years out of date".

This last data reveals the growing concern about the reliability and security of all this open-source material found in private code bases. Packages that are not maintained anymore cannot be patched for recently discovered vulnerabilities. Therefore it's become critical for organizations to be able to inventory open-source components and assess their vulnerabilities, making the use of software composition analysis mandatory. But not all SCA tools are created equal.

This blog post will provide eight factors to consider when choosing an SCA tool.

What is SCA (Software Composition Analysis)?

SCA is the process of analyzing an application's dependencies to determine if it is affected by known security vulnerabilities. Organizations can more effectively manage security risks by understanding the dependencies between components.

SCA can be performed either manually or using automated tools. Manual SCA is not scalable as the engineers must constantly check a vulnerability database such as NVD (National Vulnerability Database, maintained by NIST) and then compare the vulnerable versions with their existing dependencies. Much more efficient is to use automated SCA scanning tools, which can be triggered manually or integrated into the CI/CD pipeline for continuous checks.

Importance of Software Composition Analysis

SCA is integral to application security, as it helps identify and mitigate risks associated with using third-party components. SCA can help identify vulnerabilities in third-party components that attackers could exploit. It can also help track the versions of third-party components and ensure that they are up to date. By keeping track of the components used in an application, SCA can also help ensure compliance with license and security policies.

In short, SCA is an essential part of the code security toolkit, focused on third-party components.

How is SCA different from SAST?

SAST is a software testing technique that involves analyzing the source code of a software application to identify potential security vulnerabilities such as injection attacks, cross-site scripting (XSS), improper error handling, and insecure use of cryptographic functions.

SAST aims to identify security vulnerabilities early in the software development cycle to mitigate them before the application is compiled and deployed.

While SAST is an analysis technique used to check for known vulnerabilities in source code, SCA is used to scan dependencies for security vulnerabilities and license issues.

Both are usually performed pre-build (against source code), or post-build (against binaries), as they don't require an application's execution to identify potential vulnerabilities. Both are equally important in ensuring the security of a software application.

How to Choose an SCA tool?

The many SCA tools on the market today can make it hard to decide which is the right one for your needs. To help you select the right one, we have curated a list of 9 things you should look out for in an SCA tool:

1. Language Support

When opting for an SCA tool, it's vital to check what all languages are supported by the tool. Software composition analysis is language, end even ecosystem-dependent (package managers, build system, etc.): for instance, most SCA tools rely on lock files such as package-lock.json or Pipfile.lock to find dependencies and their respective versions. So you need to be careful here.

2. Accessible to Use/Developer Friendliness

The SCA tool you choose should make your life easier, not harder. It should be intuitive and easy to use so that you can focus on your work, not on learning the tool. It should also be developer friendly so that you can easily integrate it into your existing development process. Also, it should be scalable to grow with your organization.

The vendor should also have proper technical documentation available for the developers and having technical support for the tool is always a plus.

3. Support for Binary scanning

When looking for a Software Composition Analysis (SCA) tool, choosing one that supports the scanning of binary files is essential. Many SCA tools don't support this type of scanning, which can leave vulnerabilities in the binaries used by the developers unchecked.

Scanning binary files such as wheel files(.whl) are essential because it can find vulnerabilities that would otherwise be missed by scanning the dependencies. If you are not doing binary scanning used by your developers, you are not getting the complete picture of your code's security.