Comparing Source Code Analysis and Software Components Analysis

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What is the Difference Between Source Code Analysis Tools and Software Components Analysis Tools

Finding vulnerabilities in software is serious business. Weaknesses in software can lead to security risks such as costly ransomware or phishing attacks, and there are new types of vulnerabilities emerging all the time. The shift to remote and hybrid work models during the past two years has made vulnerability management even more complex—and necessary.

Plenty of products are available to help organizations and development teams find vulnerabilities. However, not all of these tools used to examine software for vulnerabilities are created equal. In fact, the various types of products offer different features and capabilities.

Source code analysis tools and software components analysis tools provide a case in point. While one is not necessarily better than the other for all situations, they each have strengths in certain areas. Organizations should take this into consideration when evaluating solutions to enhance their vulnerability management strategies.

Source code analysis is the process of analyzing uncompiled code during development phase, while binary analysis assesses binaries for vulnerabilities once the code has been compiled.

In general, source code analysis is typically performed in terms of programming language constructs such as functions, statements, expressions, and variables. Its primary focus is to assess and secure applications.

Software components analysis, on the other hand, is generally performed in terms of machine entities such as memory locations, registers, procedures, and instructions. Its main focus is to assess and secure operating systems, firmwares, libraries, packages, files, etc.

One functional area where the two methods differ is run time, the phase of a software program’s lifecycle in which code is being executed on a system’s central processing unit (CPU) as machine code. Run time errors can be detected after or during the running state of a program. Secure code analysis does not detect any run time issues, while binary analysis is capable of detecting issues in run time machine code.

The two also differ in how they handle supply chain issues. For instance, source code analysis does not address supply chain issues or provide provenance. Binary analysis provides comprehensive supply chain analysis including third party, open source, and provenance.

Source code analysis and software components analysis differ in terms of how they work with programming language. For instance, source code analysis is tied to specific languages. The methodology cannot mix programing languages, as it might lead to an unrecognized security issue.

Software components analysis works independent of any programming language, and therefore has no coverage limitations with regard to languages.

The two methods also differ in terms of false positives. Source code analysis has a high rate of false positives. This is due to the presence of duplicate or dead code and a lack of relational visibility to other dependencies, such as operating systems, libraries, or packages bundled with the code.

Software components analysis has comparatively lower false positives, due to the cleaner nature of compiled code.

Why SBOMs That Use Software Components Analysis Are Better

There are also differences related to the software bill of materials (SBOM), an area that has received increased attention following a federal mandate for organizations to provide purchasers of software products with an SBOM for each product directly or by publishing it on a public website. This was among the requirements of an executive order on improving the nation’s cybersecurity announced by the White House in May 2021.

Source code SBOMs are limiting and narrow and miss out on vulnerabilities; whereas software components analysis provides a comprehensive SBOM covering the entire environment.

Finally, there are differences in how these methods address vulnerabilities. Source code analysis does not prioritize vulnerabilities, which can lead to a large vulnerability workload. Software code analysis identifies vulnerabilities that are loaded to memory and thus exploitable, reducing vulnerability workload.

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