PatchFuzz: Patch fuzzing for JavaScript engines

Patch fuzzing is a technique aimed at identifying vulnerabilities that arise from newly patched code. While researchers have made efforts to apply patch fuzzing to testing JavaScript (JS) engines with considerable success, these efforts have been limited to using ordinary test cases or publicly available vulnerability PoCs (Proof of Concepts) as seeds, and the sustainability of these approaches is hindered by the challenges associated with automating the PoC collection. To address these limitations, we propose an end-to-end sustainable approach for JS engine patch fuzzing, named PatchFuzz. It automates the collection of PoCs of a broader range of historical vulnerabilities and leverages both the PoCs and their corresponding patches to uncover new vulnerabilities more effectively. PatchFuzz starts by recognizing git commits which intend to fix security bugs. Subsequently, it extracts and processes PoCs from these commits to form the seeds for fuzzing, while utilizing code revisions to focus limited fuzzing resources on the more vulnerable code areas through selective instrumentation. The mutation strategy of PatchFuzz is also optimized to maximize the potential of the PoCs. Experimental results demonstrate the effectiveness of PatchFuzz. Notably, 54 bugs across six popular JS engines have been exposed and a total of $62,500 bounties has been received. PatchFuzz effectively enables sustainable and automated patch fuzzing for JavaScript engines by leveraging historical PoCs and selective instrumentation to focus on vulnerable code regions.

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Publication Details

Journal
Information and Software Technology
Published
2026-02-17
DOI
https://doi.org/10.1016/j.infsof.2026.108087
Primary Topic
Software Testing and Debugging Techniques
Type
article
Field-Weighted Citation Impact
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article

PatchFuzz: Patch fuzzing for JavaScript engines

Xiaoning Du, Xiangwei Zhang, Xiaofei Xie, Junjie Wang et al.
Information and Software Technology
Software Testing and Debugging Techniques
article

PatchFuzz: Patch fuzzing for JavaScript engines

Xiaoning Du, Xiangwei Zhang, Xiaofei Xie, Junjie Wang, Zhihua Xie
article en

Abstract

Patch fuzzing is a technique aimed at identifying vulnerabilities that arise from newly patched code. While researchers have made efforts to apply patch fuzzing to testing JavaScript (JS) engines with considerable success, these efforts have been limited to using ordinary test cases or publicly available vulnerability PoCs (Proof of Concepts) as seeds, and the sustainability of these approaches is hindered by the challenges associated with automating the PoC collection. To address these limitations, we propose an end-to-end sustainable approach for JS engine patch fuzzing, named PatchFuzz. It automates the collection of PoCs of a broader range of historical vulnerabilities and leverages both the PoCs and their corresponding patches to uncover new vulnerabilities more effectively. PatchFuzz starts by recognizing git commits which intend to fix security bugs. Subsequently, it extracts and processes PoCs from these commits to form the seeds for fuzzing, while utilizing code revisions to focus limited fuzzing resources on the more vulnerable code areas through selective instrumentation. The mutation strategy of PatchFuzz is also optimized to maximize the potential of the PoCs. Experimental results demonstrate the effectiveness of PatchFuzz. Notably, 54 bugs across six popular JS engines have been exposed and a total of $62,500 bounties has been received. PatchFuzz effectively enables sustainable and automated patch fuzzing for JavaScript engines by leveraging historical PoCs and selective instrumentation to focus on vulnerable code regions.

Information and Software TechnologyVol. 194
Tianjin University (CN), Monash University (AU), Singapore Management University (SG)
Openalex Percentile: Top 60%
Software Testing and Debugging Techniques
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PatchFuzz: Patch fuzzing for JavaScript engines — Xiaoning Du, Xiangwei Zhang, et al. · Information and Software Technology (2026) | TGRS Research Map | TGRS