{"ID":2863448,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.24498","arxiv_id":"2509.24498","title":"JSProtect: A Scalable Obfuscation Framework for Mini-Games in WeChat","abstract":"The WeChat mini-game ecosystem faces rampant intellectual property theft to other platforms via secondary development, yet existing JavaScript obfuscation tools are ill-equipped for large-scale applications, suffering from prohibitive processing times, severe runtime performance degradation, and unsustainable code size inflation. This paper introduces JSProtect, a high-throughput parallelized obfuscation framework designed to overcome these fundamental limitations. At the core of our framework is the Parallel-Aware Scope Analysis (PASA) algorithm, which enables two key optimizations: independent code partitioning for multi-core processing and independent namespace management that aggressively reuses short identifiers to combat code bloat. Our evaluation demonstrates that JSProtectprocesses 20MB codebases in minutes, maintaining 100\\% semantic equivalence while controlling code size inflation to as low as 20\\% compared to over 1,000\\% with baseline tools. Furthermore, it preserves near-native runtime performance and provides superior security effectiveness against both static analysis tools and large language models. This work presents a new paradigm for industrial-scale JavaScript protection that effectively balances robust security with high performance and scalability.","short_abstract":"The WeChat mini-game ecosystem faces rampant intellectual property theft to other platforms via secondary development, yet existing JavaScript obfuscation tools are ill-equipped for large-scale applications, suffering from prohibitive processing times, severe runtime performance degradation, and unsustainable code size...","url_abs":"https://arxiv.org/abs/2509.24498","url_pdf":"https://arxiv.org/pdf/2509.24498v1","authors":"[\"Zhihao Li\",\"Chaozheng Wang\",\"Zongjie Li\",\"Xinyong Peng\",\"Zelin Su\",\"Qun Xia\",\"Haochuan Lu\",\"Ting Xiong\",\"Man Ho Lam\",\"Shuzheng Gao\",\"Yuchong Xie\",\"Cuiyun Gao\",\"Shuai Wang\",\"Yuetang Deng\",\"Huafeng Ma\"]","published":"2025-09-29T09:13:18Z","proceeding":"cs.SE","tasks":"[\"cs.SE\"]","methods":"[\"Language Model\"]","has_code":false}