PeachCI: Scalable Continuous Integration of Generation-Based Protocol Fuzzing

Continuous integration (CI) of protocol fuzzing is important to enhance the efficiency of fuzzing. However, current CI architecture only focus on mutation-based fuzzers, which neglects generation-based fuzzers. Even worse, it make fuzzers and target protocol into a single Docker image and use a simple front-end, which suffers the practical integration with enterprise-level monitoring and data visualization platforms. In this paper, we designed and implemented a scalable continuous integration platform for generation-based protocol fuzzing, PeachCI. PeachCI decoupling the fuzzer from the target protocol, with each component encapsulated in its own Docker image, enabling fuzzing through inter-container communication. Furthermore, the platform integrates with the widely-used systems and service monitoring system Prometheus, and the data visualization platform Grafana, using Pit files as inputs and displaying the results through Grafana. It supports parallel fuzzing and uses branch coverage as a key evaluation metric, which allows for comparison of the effectiveness of various generation-based fuzzers. The experimental results demonstrate that PeachCI is an effective method for evaluating the performance of different fuzzers and provides robust support for the network protocol fuzzing.

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Published
2025-06-23
DOI
https://doi.org/10.1145/3696630.3728612
Primary Topic
Software Testing and Debugging Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

PeachCI: Scalable Continuous Integration of Generation-Based Protocol Fuzzing

Fuchen Ma, Wanli Chen, Qi Xu, Yu Jiang et al.
Software Testing and Debugging Techniques
article

PeachCI: Scalable Continuous Integration of Generation-Based Protocol Fuzzing

Fuchen Ma, Wanli Chen, Qi Xu, Yu Jiang, Yuanliang Chen, Heyuan Shi, Qiang Fu, Ruikang Peng
article en

Abstract

Continuous integration (CI) of protocol fuzzing is important to enhance the efficiency of fuzzing. However, current CI architecture only focus on mutation-based fuzzers, which neglects generation-based fuzzers. Even worse, it make fuzzers and target protocol into a single Docker image and use a simple front-end, which suffers the practical integration with enterprise-level monitoring and data visualization platforms. In this paper, we designed and implemented a scalable continuous integration platform for generation-based protocol fuzzing, PeachCI. PeachCI decoupling the fuzzer from the target protocol, with each component encapsulated in its own Docker image, enabling fuzzing through inter-container communication. Furthermore, the platform integrates with the widely-used systems and service monitoring system Prometheus, and the data visualization platform Grafana, using Pit files as inputs and displaying the results through Grafana. It supports parallel fuzzing and uses branch coverage as a key evaluation metric, which allows for comparison of the effectiveness of various generation-based fuzzers. The experimental results demonstrate that PeachCI is an effective method for evaluating the performance of different fuzzers and provides robust support for the network protocol fuzzing.

Central South University (CN), Tsinghua University (CN)
National Natural Science Foundation of China, Central South University, Natural Science Foundation of Hunan Province
Openalex Percentile: Top 81%
Software Testing and Debugging Techniques
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PeachCI: Scalable Continuous Integration of Generation-Based Protocol Fuzzing — Fuchen Ma, Wanli Chen, et al. · (2025) | TGRS Research Map | TGRS