Jiazhen Zhao, Kailong Zhu, Canju Lu, Jun Zhao, Yuliang Lu
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引用次数: 0
Abstract
PHP is the most widely used server-side programming language, but it remains highly susceptible to diverse classes of vulnerabilities. Static Application Security Testing (SAST) tools are commonly adopted for vulnerability detection; however, their evaluation lacks systematic criteria capable of quantifying information loss and uncertainty in analysis. Existing approaches, often based on small real-world case sets or heuristic sampling, fail to control experimental entropy within test cases. This uncontrolled variability makes it difficult to measure the information gain provided by different tools and to accurately differentiate their performance under varying levels of structural and semantic complexity. In this paper, we have developed a systematic evaluation framework for PHP SAST tools, designed to provide accurate and comprehensive assessments of their vulnerability detection capabilities. The framework explicitly isolates key factors influencing data flow analysis, enabling evaluation over four progressive dimensions with controlled information diversity. Using a benchmark instance, we validate the framework's feasibility and show how it reduces evaluation entropy, enabling the more reliable measurement of detection capabilities. Our results highlight the framework's ability to reveal the limitations in current SAST tools, offering actionable insights for their future improvement.
期刊介绍:
Entropy (ISSN 1099-4300), an international and interdisciplinary journal of entropy and information studies, publishes reviews, regular research papers and short notes. Our aim is to encourage scientists to publish as much as possible their theoretical and experimental details. There is no restriction on the length of the papers. If there are computation and the experiment, the details must be provided so that the results can be reproduced.