Benchmarking Static Analysis for PHP Applications Security

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.

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Publication Details

Journal
Entropy
Published
2025-09-03
DOI
https://doi.org/10.3390/e27090926
Citations
1
Primary Topic
Web Application Security Vulnerabilities
Type
article
Field-Weighted Citation Impact
3.25

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article

Benchmarking Static Analysis for PHP Applications Security

Canju Lu, Kailong Zhu, Jun Zhao, Jiazhen Zhao et al.
1 citations
Entropy
Web Application Security Vulnerabilities
3.25
article

Benchmarking Static Analysis for PHP Applications Security

Canju Lu, Kailong Zhu, Jun Zhao, Jiazhen Zhao, Yuliang Lu
article en
1 citations

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.

EntropyVol. 27(9)
Anhui University (CN), National University of Defense Technology (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Openalex Percentile: Top 7%
Web Application Security Vulnerabilities
3.25
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