MicroFuzz: An Efficient Fuzzing Framework for Microservices
January 10, 2024 Β· Declared Dead Β· π 2024 IEEE/ACM 46th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP)
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Authors
Peng Di, Bingchang Liu, Yiyi Gao
arXiv ID
2401.05529
Category
cs.SE: Software Engineering
Citations
4
Venue
2024 IEEE/ACM 46th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP)
Last Checked
4 months ago
Abstract
This paper presents a novel fuzzing framework, called MicroFuzz, specifically designed for Microservices. Mocking-Assisted Seed Execution, Distributed Tracing, Seed Refresh and Pipeline Parallelism approaches are adopted to address the environmental complexities and dynamics of Microservices and improve the efficiency of fuzzing. MicroFuzz has been successfully implemented and deployed in Ant Group, a prominent FinTech company. Its performance has been evaluated in three distinct industrial scenarios: normalized fuzzing, iteration testing, and taint verification.Throughout five months of operation, MicroFuzz has diligently analyzed a substantial codebase, consisting of 261 Apps with over 74.6 million lines of code (LOC). The framework's effectiveness is evident in its detection of 5,718 potential quality or security risks, with 1,764 of them confirmed and fixed as actual security threats by software specialists. Moreover, MicroFuzz significantly increased program coverage by 12.24% and detected program behavior by 38.42% in the iteration testing.
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