Grey-Box Fuzzing in Constrained Ultra-Large Systems: Lessons for SE Community

Testing ultra-large microservices-based FinTech systems presents significant challenges, including restricted access to production environments, complex dependencies, and stringent security constraints. We propose SandBoxFuzz, a scalable grey-box fuzzing technique that addresses these limitations by leveraging aspect-oriented programming and runtime reflection to enable dynamic specification mining, generating targeted inputs for constrained environments. SandBoxFuzz also introduces a log-based coverage mechanism, seamlessly integrated into the build pipeline, eliminating the need for runtime coverage agents that are often infeasible in industrial settings. SandBoxFuzz has been successfully deployed to Ant Group's production line and, compared to an initial solution built on a state-of-the-art fuzzing framework, it demonstrates superior performance in their microservices software. SandBoxFuzz achieves a 7.5% increase in branch coverage, identifies 1,850 additional exceptions, and reduces setup time from hours to minutes, highlighting its effectiveness and practical utility in a real-world industrial environment. By open-sourcing SandBoxFuzz1, we provide a practical and effective tool for researchers and practitioners to test large-scale microservices systems.

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Publication Details

Published
2025-06-23
DOI
https://doi.org/10.1145/3696630.3728546
Primary Topic
Distributed and Parallel Computing Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Grey-Box Fuzzing in Constrained Ultra-Large Systems: Lessons for SE Community

Tiehua Zhang, Hong Jin Kang, Jiazhao Yu, Xi Zheng et al.
Distributed and Parallel Computing Systems
article

Grey-Box Fuzzing in Constrained Ultra-Large Systems: Lessons for SE Community

Tiehua Zhang, Hong Jin Kang, Jiazhao Yu, Xi Zheng, Zixi Zhang, Weigang Wu, Cheng Xu, Yu-Hao Tu
article en

Abstract

Testing ultra-large microservices-based FinTech systems presents significant challenges, including restricted access to production environments, complex dependencies, and stringent security constraints. We propose SandBoxFuzz, a scalable grey-box fuzzing technique that addresses these limitations by leveraging aspect-oriented programming and runtime reflection to enable dynamic specification mining, generating targeted inputs for constrained environments. SandBoxFuzz also introduces a log-based coverage mechanism, seamlessly integrated into the build pipeline, eliminating the need for runtime coverage agents that are often infeasible in industrial settings. SandBoxFuzz has been successfully deployed to Ant Group's production line and, compared to an initial solution built on a state-of-the-art fuzzing framework, it demonstrates superior performance in their microservices software. SandBoxFuzz achieves a 7.5% increase in branch coverage, identifies 1,850 additional exceptions, and reduces setup time from hours to minutes, highlighting its effectiveness and practical utility in a real-world industrial environment. By open-sourcing SandBoxFuzz1, we provide a practical and effective tool for researchers and practitioners to test large-scale microservices systems.

Tongji University (CN), The University of Sydney (AU), Sun Yat-sen University (CN), Shanghai Construction Group (China) (CN), Macquarie University (AU)
Australian Research Council
Openalex Percentile: Top 77%
Distributed and Parallel Computing Systems
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Grey-Box Fuzzing in Constrained Ultra-Large Systems: Lessons for SE Community — Tiehua Zhang, Hong Jin Kang, et al. · (2025) | TGRS Research Map | TGRS