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P2 Shrunk, Yet Complete: Code Shrinking-Resilient Android Third-Party Library Detection

缩减但完整:面向代码缩减鲁棒的 Android 第三方库检测
ASE 2025 40th IEEE/ACM International Conference on Automated Software Engineering (ASE)2025匹配度 2/10 · 该论文属于Android第三方库检测/软件成分分析,虽可能涉及程序分析技术,但与用户关注的PL与AI/LLM交叉、Agentic程序静态分析、浮点程序分析及贝叶斯程序分析均无直接关联。其核心是代码缩减与混淆场景下的库版本检测,匹配度较低。引用 1 inbox
Jingkun Zhang, Jingzheng Wu, Xiang Ling, Tianyue Luo, Bolin Zhou, Mutian Yang
crossref: 2026-09-12

AI 速览

一句话:提出抗代码缩减与混淆的 Android 第三方库检测工具 LibSleuth。

Android 第三方库管理对漏洞评估和许可证合规至关重要,但现有软件成分分析多关注混淆,忽视构建时缩减/优化对库结构的破坏。本文提出 LibSleuth,基于缩减后保留代码仍具功能完整性的观察。方法将特征匹配细化到方法级,以表示已用功能的相关方法构成功能模块,按其完整性检测库;并利用上下文增强特征稳定性,采用由粗到细的多级过滤抗混淆。在含混淆和优化的 Android 应用上,LibSleuth 优于现有学术与商业工具;缩减与混淆组合下版本级 F1 平均提升 27.74%。对 10,000 个真实应用,20.35% 仍依赖含漏洞库。

问题
如何在代码缩减/优化与混淆条件下准确检测 Android 应用中的第三方库,以支持漏洞评估和许可证合规。
方法
提出 LibSleuth,将匹配细化到方法级并定义功能模块,结合上下文增强特征与由粗到细多级过滤进行检测。
评估
在含混淆和优化的 Android 应用数据集上评估,优于现有学术与商业工具;缩减与混淆组合下版本级 F1 平均提升 27.74%,并分析 10,000 个真实应用发现 20.35% 依赖含漏洞库。
原文摘要(Abstract)

Managing third-party libraries is a costly and critical task for enterprises, essential for both vulnerability assessment and license compliance. Existing android software composition analysis tools focus on mitigating code obfuscation but neglect the impact of code optimization, which is deeply integrated into build pipelines and disrupts library structure.To tackle these challenges, we developed LibSleuth, a detection tool designed to be resilient to code shrinking and obfuscation. It is based on the observation that even after shrinking, the remaining code still retains functional completeness. LibSleuth adopts two novel strategies: (1) Method level functional module matching: We break down feature matching to method level and define a functional module as related methods that represent used functionality. This allows us to detect libraries based on functional module completeness to address code shrinking. (2) Context-enhanced multi-level filtering: To improve robustness against obfuscation and reduce the cost of pairing, LibSleuth leverages contextual relationships to enhance feature stability and adopts a coarse-to-fine progressive matching process.We evaluated LibSleuth on datasets containing obfuscated and optimized Android apps. LibSleuth outperforms state-of-the-art academic and commercial tools in both scenarios. Under combined code shrinking and obfuscation, LibSleuth achieves an average 27.74% higher version level F1-score. Moreover, our analysis of 10,000 real world Android apps shows that 20.35% still depend on vulnerable library, demonstrating the practical utility of LibSleuth for downstream tasks.

链接与引用

DOI 原文 ·

BibTeX
@inproceedings{paperbot9522,
  title = {Shrunk, Yet Complete: Code Shrinking-Resilient Android Third-Party Library Detection},
  author = {Jingkun Zhang and Jingzheng Wu and Xiang Ling and Tianyue Luo and Bolin Zhou and Mutian Yang},
  booktitle = {ASE},
  year = {2025},
  doi = {10.1109/ase63991.2025.00294}
}