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OOPSLA2025顶会

Extraction and Mutation at a High Level: Template-Based Fuzzing for JavaScript Engines

Wai Kin Wong, Dongwei Xiao, Anthony Cheuk Tung Lai, Yiteng Peng, Daoyuan Wu, Shuai Wang

2025年份
4被引次数
3顶会引用

摘要

JavaScript (JS) engines implement complex language semantics and optimization strategies to support the dynamic nature of JS, making them difficult to test thoroughly and prone to subtle, security-critical bugs. Existing fuzzers often struggle to generate diverse and valid test cases. They either rely on syntax-level mutations that lack semantic awareness or perform limited, local mutations on concrete code, thus failing to explore deeper, more complex program behaviors. This paper presents TemuJs , a novel fuzzing framework that performs extraction and mutation at a high level, operating on abstract templates derived from real-world JS programs. These templates capture coarse-grained program structures with semantic placeholders, enabling semantics-aware mutations that preserve the high-level intent of the original code while diversifying its behavior. By decoupling mutation from concrete syntax and leveraging a structured intermediate representation for the templates, TemuJs explores a broader and more meaningful space of program behaviors. Evaluated on three major JS engines, namely, V8, SpiderMonkey, and JavaScriptCore, TemuJs discovers 44 bugs and achieves a 10.3% relative increase in edge coverage compared to state-of-the-art fuzzers on average. Our results demonstrate the efficacy of high-level, template-mutation fuzzing in testing JS engines.

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