MicroFuzz: An Efficient Fuzzing Framework for Microservices
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arXiv
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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866909092448043008 |
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| author | Di, Peng Liu, Bingchang Gao, Yiyi |
| author_facet | Di, Peng Liu, Bingchang Gao, Yiyi |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_05529 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | MicroFuzz: An Efficient Fuzzing Framework for Microservices Di, Peng Liu, Bingchang Gao, Yiyi Software Engineering 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. |
| title | MicroFuzz: An Efficient Fuzzing Framework for Microservices |
| topic | Software Engineering |
| url | https://arxiv.org/abs/2401.05529 |