Revisiting Third-Party Library Detection: A Ground Truth Dataset and Its Implications Across Security Tasks

• URL: http://arxiv.org/abs/2509.04091v2
• Date: Fri, 05 Sep 2025 10:34:25 GMT
• Title: Revisiting Third-Party Library Detection: A Ground Truth Dataset and Its Implications Across Security Tasks
• Authors: Jintao Gu, Haolang Lu, Guoshun Nan, Yihan Lin, Kun Wang, Yuchun Guo, Yigui Cao, Yang Liu,
• Abstract summary: We present the first large-scale empirical study of ten state-of-the-art TPL detection techniques across over 6,000 apps.<n>Our evaluation exposes tool fragility to R8-era transformations, weak version discrimination, inaccurate correspondence of candidate libraries, difficulty in generalizing similarity thresholds, and prohibitive runtime/memory overheads at scale.
• Score: 12.328841506102963
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Accurate detection of third-party libraries (TPLs) is fundamental to Android security, supporting vulnerability tracking, malware detection, and supply chain auditing. Despite many proposed tools, their real-world effectiveness remains unclear. We present the first large-scale empirical study of ten state-of-the-art TPL detection techniques across over 6,000 apps, enabled by a new ground truth dataset with precise version-level annotations for both remote and local dependencies. Our evaluation exposes tool fragility to R8-era transformations, weak version discrimination, inaccurate correspondence of candidate libraries, difficulty in generalizing similarity thresholds, and prohibitive runtime/memory overheads at scale. Beyond tool assessment, we further analyze how TPLs shape downstream tasks, including vulnerability analysis, malware detection, secret leakage assessment, and LLM-based evaluation. From this perspective, our study provides concrete insights into how TPL characteristics affect these tasks and informs future improvements in security analysis.

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