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    Using software bill of materials for software supply chain security and its generation impact on vulnerability detection
    (Montana State University - Bozeman, College of Engineering, 2024) O'Donoghue, Eric Jeffery; Chairperson, Graduate Committee: Clemente Izurieta; This is a manuscript style paper that includes co-authored chapters.
    Cybersecurity attacks threaten the lives and safety of individuals around the world. Improving defense mechanisms across all vulnerable surfaces is essential. Among surfaces, the software supply chain (SSC) stands out as particularly vulnerable to cyber threats. This thesis investigates how Software Bill of Materials (SBOM) can be utilized to assess and improve the security of software supply chains. An informal literature review reveals the paucity of studies utilizing SBOM to assess SSC security, which further motivates this research. Our research adopts the Goal/Question/Metric paradigm with two goals: firstly, to utilize SBOM technology to assess SSC security; secondly, to examine the impact of SBOM generation on vulnerability detection. The study unfolds in two phases. Initially, we introduce a novel approach to assess SSC security risks using SBOM technology. Utilizing analysis tools Trivy and Grype, we identify vulnerabilities across a corpus of 1,151 SBOMs. The second phase investigates how SBOM generation affects vulnerability detection. We analyzed four SBOM corpora derived from 2,313 Docker images by varying the SBOM generation tools (Syft and Trivy) and formats (CycloneDX 1.5 and SPDX 2.3). Using SBOM analysis tools (Trivy, Grype, CVE-bin-tool), we investigated how the vulnerability findings for the same software artifact changed according to the SBOM generation tool and format. The first phase demonstrates SBOMs use in identifying SSC vulnerabilities, showcasing their utility in enhancing security postures. The subsequent analysis reveals significant discrepancies in vulnerability detection outcomes, influenced by SBOM generation tools and formats. These variations underscore the necessity for rigorous validation and enhancement of SBOM technologies to secure SSCs effectively. This thesis demonstrates the use of SBOMs in assessing the security of SSCs. We underscore the need for stringent standards and rigorous validation mechanisms to ensure the accuracy and reliability of SBOM data. We reveal how SBOM generation affects vulnerability detection, offering insights that enhanced SBOM methodologies can help improve security. While SBOM is promising for enhancing SSC security, it is clear the SBOM space is immature. Extensive development, validation, and verification of analysis tools, generation tools, and formats are required to improve the usefulness of SBOMs for SSC security.
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