SNPSFuzzer: A Fast Greybox Fuzzer for Stateful Network Protocols using Snapshots

February 08, 2022 Β· Declared Dead Β· πŸ› IEEE Transactions on Information Forensics and Security

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Authors Junqiang Li, Senyi Li, Gang Sun, Ting Chen, Hongfang Yu arXiv ID 2202.03643 Category cs.CR: Cryptography & Security Cross-listed cs.CY Citations 53 Venue IEEE Transactions on Information Forensics and Security Last Checked 5 months ago
Abstract
Greybox fuzzing has been widely used in stateless programs and has achieved great success. However, most state-of-the-art greybox fuzzers generally have the problems of slow speed and shallow state depth coverage in the process of fuzzing stateful network protocol programs which are able to remember and store details of the interactions. The existing greybox fuzzers for network protocol programs send a series of well-defined prefix sequences of input messages first and then send mutated messages to test the target state of a stateful network protocol. The process mentioned above causes a high time cost. In this paper, we propose SNPSFuzzer, a fast greybox fuzzer for stateful network protocol using snapshots. SNPSFuzzer dumps the context information when the network protocol program is under a specific state and restores it when the state needs to be fuzzed. Furthermore, we design a message chain analysis algorithm to explore more and deeper network protocol states. Our evaluation shows that, compared with the state-of-the-art network protocol greybox fuzzer AFLNET, SNPSFuzzer increases the speed of network protocol fuzzing by 112.0%-168.9% and improves path coverage by 21.4%-27.5% within 24 hours. Moreover, SNPSFuzzer exposes a previously unreported vulnerability in program Tinydtls.
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