P-Fuzz: A Parallel Grey-Box Fuzzing Framework
Fuzzing is an effective technology in software testing and security vulnerability detection. Unfortunately, fuzzing is an extremely compute-intensive job, which may cause thousands of computing hours to find a bug. Current novel works generally improve fuzzing efficiency by developing delicate algor...
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| Veröffentlicht in: | Applied sciences 2019-12, Vol.9 (23), p.5100 |
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| creator | Song, Congxi Zhou, Xu Yin, Qidi He, Xinglu Zhang, Hangwei Lu, Kai |
| description | Fuzzing is an effective technology in software testing and security vulnerability detection. Unfortunately, fuzzing is an extremely compute-intensive job, which may cause thousands of computing hours to find a bug. Current novel works generally improve fuzzing efficiency by developing delicate algorithms. In this paper, we propose another direction of improvement in this field, i.e., leveraging parallel computing to improve fuzzing efficiency. In this way, we develop P-fuzz, a parallel fuzzing framework that can utilize massive, distributed computing resources to fuzz. P-fuzz uses a database to share the fuzzing status such as seeds, the coverage information, etc. All fuzzing nodes get tasks from the database and update their fuzzing status to the database. Also, P-fuzz handles some data races and exceptions in parallel fuzzing. We compare P-fuzz with AFL and a parallel fuzzing framework Roving in our experiment. The result shows that P-fuzz can easily speed up AFL about 2.59× and Roving about 1.66× on average by using 4 nodes. |
| doi_str_mv | 10.3390/app9235100 |
| format | Article |
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| source | DOAJ Directory of Open Access Journals; MDPI - Multidisciplinary Digital Publishing Institute; EZB-FREE-00999 freely available EZB journals |
| subjects | Algorithms Distributed processing Efficiency Feedback Mutation Nodes Security Seeds Software Software reliability Software testing Workloads |
| title | P-Fuzz: A Parallel Grey-Box Fuzzing Framework |
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