Cracking the Code: Solving the Challenges of C/C++ Software Composition Analysis
Blog post from Endor Labs
Endor Labs has developed an innovative approach to software composition analysis (SCA) for C and C++ codebases, achieving significant improvements in accuracy by detecting 143% more true positives and 81% fewer false negatives in identifying vulnerabilities. This approach, detailed in a whitepaper by Andrew Stiefel and published on June 18, 2025, with an update on April 29, 2026, emphasizes the importance of indexing open-source dependencies to enhance security. The document also highlights related topics such as managing software bills of material (SBOMs), implementing low-code/no-code solutions for artifact signing, and fixing vulnerabilities without causing disruptions, showcasing a comprehensive strategy for enhancing open-source security practices.
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