Martin Rosso | Searcharxiv

arXiv2025

A Practical Solution to Systematically Monitor Inconsistencies in SBOM-based Vulnerability Scanners

Software Bill of Materials (SBOM) provides new opportunities for automated vulnerability identification in software products. While the industry is adopting SBOM-based Vulnerability Scanning (SVS) to identify vulnerabilities, we increasingly observe inconsistencies and unexpected behavior, that result in false negatives and silent failures. In this work, we present the background necessary to understand the underlying complexity of SVS and introduce SVS-TEST, a method and tool to analyze the capability, maturity, and failure conditions of SVS-tools in real-world scenarios. We showcase the utility of SVS-TEST in a case study evaluating seven real-world SVS-tools using 16 precisely crafted SBOMs and their respective ground truth. Our results unveil significant differences in the reliability and error handling of SVS-tools; multiple SVS-tools silently fail on valid input SBOMs, creating a false sense of security. We conclude our work by highlighting implications for researchers and practitioners, including how organizations and developers of SVS-tools can utilize SVS-TEST to monitor SVS capability and maturity. All results and research artifacts are made publicly available and all findings were disclosed to the SVS-tool developers ahead of time.

cs.SE↗

arXiv2020

SAIBERSOC: Synthetic Attack Injection to Benchmark and Evaluate the Performance of Security Operation Centers

In this paper we introduce SAIBERSOC, a tool and methodology enabling security researchers and operators to evaluate the performance of deployed and operational Security Operation Centers (SOCs) (or any other security monitoring infrastructure). The methodology relies on the MITRE ATT&CK Framework to define a procedure to generate and automatically inject synthetic attacks in an operational SOC to evaluate any output metric of interest (e.g., detection accuracy, time-to-investigation, etc.). To evaluate the effectiveness of the proposed methodology, we devise an experiment with $n=124$ students playing the role of SOC analysts. The experiment relies on a real SOC infrastructure and assigns students to either a BADSOC or a GOODSOC experimental condition. Our results show that the proposed methodology is effective in identifying variations in SOC performance caused by (minimal) changes in SOC configuration. We release the SAIBERSOC tool implementation as free and open source software.

cs.CR↗