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    基于前后端联合分析的Java Web漏洞挖掘方法

    Java Web Vulnerability Detection Mining Method Based on Co-Analysis of Front-End and Back-End

    • 摘要: 精准高效地挖掘Web应用当中存在的安全漏洞具有极高的研究价值.Web漏洞挖掘相关研究大多都是针对PHP应用的,无法直接应用于Java Web漏洞挖掘. 且现有的Web漏洞挖掘方法难以适应批量高效的需求,即难以在保持静态代码分析的性能下取得动态分析的精确度. 为解决上述问题,提出了一种前后端联合分析的Web漏洞挖掘方法,利用前端解析提取污点源信息帮助后端分析进行剪枝,提高漏洞覆盖率和检测性能;同时在漏洞挖掘时利用程序的动静态信息进行代码建模,结合数据流分析、污点分析、符号执行以及轻量动态求解技术完成漏洞的挖掘和验证,在引入较少开销前提下带来较大的效果提升. 选取了CVE(common vulnerabilities and exposure)漏洞、开源CMS(content management system)以及开源社区应用中共105个Java Web漏洞对本文提出的方法进行了实验,证明了各模块具有较好的分析效果,整体具有较强的漏洞挖掘能力.

       

      Abstract: Accurately and efficiently identifying security vulnerabilities in web applications holds significant research value, especially as web systems grow in complexity and scale. Most existing studies in the field of web vulnerability detection have focused on PHP-based applications, rendering them less effective or even inapplicable when transferred to the domain of Java Web applications. Furthermore, traditional vulnerability detection methods often struggle to meet the demands of large-scale and high-efficiency scenarios. Specifically, these methods face difficulties in achieving the precision of dynamic analysis while maintaining the performance benefits of static analysis.To address these challenges, this paper proposes a novel web vulnerability detection approach based on joint frontend-backend analysis. By parsing the frontend code to extract taint source information, the method guides backend analysis for pruning irrelevant paths, thereby enhancing both the vulnerability coverage and detection efficiency. Additionally, the approach integrates both static and dynamic features of the program to construct a comprehensive code model. It combines techniques such as data flow analysis, taint analysis, symbolic execution, and lightweight dynamic solving to detect and verify potential vulnerabilities. This integrated strategy leads to a significant performance boost with minimal computational overhead.The proposed method was evaluated on 105 Java Web vulnerabilities sourced from CVE (common vulnerabilities and exposure) entries, open-source CMS (content management system) platforms, and community-developed applications. The experimental results demonstrate that each component of the system performs effectively, and the overall framework exhibits strong capability in discovering real-world Java Web vulnerabilities.

       

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