Best Practices for Selecting Software Composition Analysis Tools

Software composition analysis (SCA) tools were created after developers and application security teams encountered problems tracking open source components, both direct and transitive dependencies within their code bases. Relying on manual processes and spreadsheets was inefficient, error-prone, and not scalable.

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How Software Composition Analysis Tools Work

Adopting software composition analysis (SCA) tools can automate the process of identifying and categorizing the open source code used in the development environment and identify security, licensing and quality issues and their dependencies.

To this end, we need to discuss best practices for selecting a software composition analysis (SCA) solution.

Software Composition Analysis (SCA) and Continuous Monitoring

To work effectively, SCA tools must continuously monitor the code because modern development methodologies using open source code are continuous in nature.

One security team leader liked the feature, saying, "We're always developing new applications, and we're finding a lot of vulnerabilities that need to be fixed in applications that aren't being actively developed."

That’s why visibility becomes an important consideration when choosing a software composition analysis (SCA) solution. Developers, as well as those responsible for analysis, must understand the open source components used in development.

“It’s like working in the dark and suddenly you have visibility,” said one employee at a financial services organization with 10,000 employees. “You can see exactly what you’re using and get recommendations. If you can’t use something, you have other options.”

Another user, a large financial services organization that has adopted software composition analysis (SCA), echoed this sentiment, saying, "We are no longer blindly using vulnerable components. We have realized that we are promoting this awareness to developers and think we have a better understanding of the threat landscape. We didn't even know what was a bug or vulnerability before, and now we know and can remediate it very quickly."

Low false alarm rate

False positives waste time and cause users to be overwhelmed in their SCA efforts. Conversely, false negatives can introduce security and licensing issues into the code. For these reasons, SCA solutions need to be as accurate as possible.

A senior executive at a solution provider noted the importance of this issue. He said, “This helps us avoid exposing critical vulnerabilities in the field. It saves us time on remediation activities that might be done after deployment, because if we discover security issues after the application is fully developed and deployed, it will be more difficult to make changes or reuse if needed.”

Improve developer productivity and ROI

Software Composition Analysis (SCA) is more than just about protecting your code. It should also be a driver for improving developer productivity.

The executive also found that when solving problems, the solution increased developer productivity by 5% to 10% because the problem was clearly laid out.

He said that adopting software composition analysis (SCA) technology may pay a certain cost because it will cost a lot of money to fix security holes in the development life cycle.

Open Source Code Policy

The ultimate goal of SCA practices and solutions is to enforce security policies to all parts of the code base. Therefore, the preferred SCA solution is one that can enforce open source code policies.

“Because of its proactive nature and real-time data, you can immediately know if any part of the application is vulnerable right now,” the executive added.

While strong security policies are certainly needed, if they are too restrictive they can negatively impact developer productivity, or they may even be circumvented altogether. Therefore, it is useful if a software composition analysis (SCA) solution can provide flexible policy enforcement.

Software Composition Analysis (SCA) is a new mitigation control that can discover new classes of vulnerabilities. It helps enforce secure coding practices, which may take some time when first rolled out, but will become less expensive after a while as more developers become familiar with it.

Additionally, SCA tools can even inherit certain components because in the real world, you can’t always take the time to update it since it’s not backwards compatible. Having these features makes it easier to use and more practical without taking an all-or-nothing approach.

Many users want SCA to provide continuous monitoring of development activity visibility and awareness. They also want SCA to have high-quality data from multiple sources, low false positives, increased developer productivity, ROI, flexible policy enforcement, open source policy enforcement by breaking builds, integration capabilities, and strong vendor support.