Finding SQL Injection and Cross Site Scripting Vulnerabilities with Diverse Static Analysis Tools

Abstract

The use of Static Analysis Tools (SATs) is mandatory when developing secure software and searching for vulnerabilities in legacy software. However, the performance of the various SATs concerning the detection of vulnerabilities and false alarm rate is usually unknown and depends on many factors. The simultaneous use of several tools should increase the detection capabilities, but also the number of false alarms. In this paper, we study the problem of combining several SATs to best meet the developer needs. We present results of analyzing the performance of diverse static analysis tools, based on a previously published dataset that resulted from the use of five diverse SATs to find two types of vulnerabilities, namely SQL Injections (SQLi) and Cross-Site Scripting (XSS), in 132 plugins of the WordPress Content Management System (CMS). We present the results based on well-established measures for binary classifiers, namely sensitivity and specificity for all possible diverse combinations that can be constructed using these 5 SAT tools. We then provide empirically supported guidance on which combinations of SAT tools provide the most benefits for detecting vulnerabilities with low false positive rates.