Yue Xiao (IBM Research), Dhilung Kirat (IBM Research), Douglas Lee Schales (IBM Research), Jiyong Jang (IBM Research), Luyi Xing (Indiana University Bloomington), Xiaojing Liao (Indiana University)

Abstract—A Software Bill of Materials (SBOM) is a detailed inventory that lists the dependencies that make up a software product. Accurate, complete, and up-to-date SBOMs are essential for vulnerability management, reducing license compliance risks, and maintaining high software integrity. The US National Institute of Standards and Technology (NTIA) has established minimum requirements for SBOMs to comply with, especially the correctness and completeness of listed dependencies in SBOMs. However, these requirements remain unexamined in practice. This paper presents the first systematic study on the landscape of SBOMs, including their prevalence, release trends, and characteristics in the Java ecosystem. We developed an end-to-end tool to evaluate the completeness and accuracy of dependencies in SBOMs. Our tool analyzed 25,882 SBOMs and associated JAR files, identifying that 7,907 SBOMs failed to disclose direct dependencies, highlighting the prevalence and severity of SBOM noncompliance issues. Furthermore, 4.97% of these omitted dependencies were vulnerable, leaving software susceptible to potential exploits. Through detailed measurement studies and analysis of root causes, this research uncovers significant security implications of non-compliant SBOMs, especially concerning vulnerability management. These findings, crucial for enhancing SBOM compliance assurance, are being responsibly reported to relevant stakeholders.

View More Papers

Scale-MIA: A Scalable Model Inversion Attack against Secure Federated...

Shanghao Shi (Virginia Tech), Ning Wang (University of South Florida), Yang Xiao (University of Kentucky), Chaoyu Zhang (Virginia Tech), Yi Shi (Virginia Tech), Y. Thomas Hou (Virginia Polytechnic Institute and State University), Wenjing Lou (Virginia Polytechnic Institute and State University)

Read More

KernelSnitch: Side Channel-Attacks on Kernel Data Structures

Lukas Maar (Graz University of Technology), Jonas Juffinger (Graz University of Technology), Thomas Steinbauer (Graz University of Technology), Daniel Gruss (Graz University of Technology), Stefan Mangard (Graz University of Technology)

Read More

A Method to Facilitate Membership Inference Attacks in Deep...

Zitao Chen (University of British Columbia), Karthik Pattabiraman (University of British Columbia)

Read More

Analysis of Misconfigured IoT MQTT Deployments and a Lightweight...

Seyed Ali Ghazi Asgar, Narasimha Reddy (Texas A&M University)

Read More