How We Cracked SCA for C/C++ Codebases
Blog post from Endor Labs
Software Composition Analysis (SCA) faces challenges in identifying dependencies for older languages like C and C++ due to the prevalent practice of developers copying third-party code into repositories without maintaining precise logs. This makes creating an accurate Software Bill of Materials (SBOM) difficult, increasing security and licensing risks. Endor Labs addresses these challenges by developing an innovative approach to SCA, leveraging techniques from code clone detection and semantic search to build a comprehensive index of C/C++ libraries. They utilize a combination of hash signatures and text embeddings to identify the origins of cloned source code, even creating an ingestion infrastructure to index various archives beyond GitHub. Through a combination of semi-automated analysis and manual annotation, Endor Labs' approach enables precise identification of library versions, surprising users with their depth of detection and potentially revealing unknown library usages. Their method has been benchmarked against high-profile OSS projects, demonstrating effective performance in library identification compared to competitors in the C/C++ SCA space.
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