VERJava: Vulnerable Version Identification for Java OSS with a Two-Stage Analysis

The software version information affected by the CVEs (Common Vulnerabilities and Exposures) provided by the National Vulnerability Database (NVD) is not always accurate. This could seriously mislead the repair priority for software users, and greatly hinder the work of security researchers. Bao et al. improved the well-known Sliwerski-Zimmermann-Zeller (SZZ) algorithm for vulnerabilities (called V-SZZ) to precisely refine vulnerable software versions. But V-SZZ only focuses on those CVEs of which patches only have deleted lines.In this study, we target Java Open Source Software (OSS) by virtue of its pervasiveness and ubiquitousness. Due to Java’s object-oriented characteristic, a single security patch often involves modifications of multiple functions. Existing patch code similarity analysis does not consider patch existence from the point of view of an entire patch, which would generate too many false positives for Java CVEs. In this work, we address these limitations by introducing a two-stage approach named VERJava, to systematically assess vulnerable versions for a target vulnerability in Java OSS. Specifically, vulnerable versions are calculated respectively at a function level and an entire patch level, then the results are synthesized to decide the final vulnerable versions. For evaluation, we manually annotated the vulnerable versions of 167 real CVEs from seven popular Java open source projects. The result shows that VERJava achieves the precision of 90.7% on average, significantly outperforming the state-of-the-art work V-SZZ. Furthermore, our study reveals some interesting findings that have not yet been discussed.