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PPT4J: Patch Presence Test for Java Binaries

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arxiv 2312.11013 v2 pith:GTZXOUY3 submitted 2023-12-18 cs.SE cs.CR

classification cs.SEcs.CR
keywords ppt4jbinariespatchtextbfpatchessoftwaretestjava
verification ladder T0 review T1 audit T2 compute T3 formal
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abstract

The number of vulnerabilities reported in open source software has increased substantially in recent years. Security patches provide the necessary measures to protect software from attacks and vulnerabilities. In practice, it is difficult to identify whether patches have been integrated into software, especially if we only have binary files. Therefore, the ability to test whether a patch is applied to the target binary, a.k.a. patch presence test, is crucial for practitioners. However, it is challenging to obtain accurate semantic information from patches, which could lead to incorrect results. In this paper, we propose a new patch presence test framework named PPT4J ($\textbf{P}$atch $\textbf{P}$resence $\textbf{T}$est $\textbf{for}$ $\textbf{J}$ava Binaries). PPT4J is designed for open-source Java libraries. It takes Java binaries (i.e. bytecode files) as input, extracts semantic information from patches, and uses feature-based techniques to identify patch lines in the binaries. To evaluate the effectiveness of our proposed approach PPT4J, we construct a dataset with binaries that include 110 vulnerabilities. The results show that PPT4J achieves an F1 score of 98.5% with reasonable efficiency, improving the baseline by 14.2%. Furthermore, we conduct an in-the-wild evaluation of PPT4J on JetBrains IntelliJ IDEA. The results suggest that a third-party library included in the software is not patched for two CVEs, and we have reported this potential security problem to the vendor.

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  1. There are More Fish in the Sea: Automated Vulnerability Repair via Binary Templates

    cs.SE 2024-11 conditional novelty 6.0 of 10

    A template-based tool that operates on Java bytecode can fix more vulnerabilities than source-level automated repair baselines in the authors' evaluation, and extends the available benchmark dataset.

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