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ProFuzzBench: a benchmark for stateful protocol fuzzing

Published:11 July 2021Publication History

ABSTRACT

We present a new benchmark (ProFuzzBench) for stateful fuzzing of network protocols. The benchmark includes a suite of representative open-source network servers for popular protocols, and tools to automate experimentation. We discuss challenges and potential directions for future research based on this benchmark.

References

  1. Humberto J Abdelnur, Radu State, and Olivier Festor. 2007. KiF: a stateful SIP fuzzer. In Intl. Conf. on Princ., Sys. and Apps. of IP Telecom.. 47–56.Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. T. Alrahem, A. Chen, N. DiGiuseppe, J. Gee, S.-P. Hsiao, S. Mattox, and T. Park. 2007. Interstate: A stateful protocol fuzzer for SIP. Defcon, 15 (2007), 1–5.Google ScholarGoogle Scholar
  3. Greg Banks, Marco Cova, Viktoria Felmetsger, Kevin Almeroth, Richard Kemmerer, and Giovanni Vigna. 2006. SNOOZE: toward a Stateful NetwOrk prOtocol fuzZEr. In Intl. Conf. on Information Security. 343–358.Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Beyond Security. 2020. beSTORM Black Box Testing. https://beyondsecurity.com/solutions/bestorm.html [Online; accessed 12-10-2020].Google ScholarGoogle Scholar
  5. Brian Caswell. 2020. Cyber Grand Challenge Corpus. http://www.lungetech.com/cgc-corpus/ [Online; accessed 12-01-2021].Google ScholarGoogle Scholar
  6. Joeri De Ruiter and Erik Poll. 2015. Protocol State Fuzzing of TLS Implementations. In 24th USENIX Security Symp.. 193–206.Google ScholarGoogle Scholar
  7. Brendan Dolan-Gavitt, Patrick Hulin, Engin Kirda, Tim Leek, Andrea Mambretti, Wil Robertson, Frederick Ulrich, and Ryan Whelan. 2016. LAVA: Large-scale automated vulnerability addition. In Symp. on Security and Privacy (SP). 110–121.Google ScholarGoogle ScholarCross RefCross Ref
  8. Paul Fiterau-Brostean, Bengt Jonsson, Robert Merget, Joeri de Ruiter, Konstantinos Sagonas, and Juraj Somorovsky. 2020. Analysis of DTLS Implementations Using Protocol State Fuzzing. In 29th USENIX Security Symp..Google ScholarGoogle Scholar
  9. Z. Gao, W. Dong, R. Chang, and Y. Wang. 2020. Fw-fuzz: A code coverage-guided fuzzing framework for network protocols on firmware. Concur. and Comp..Google ScholarGoogle Scholar
  10. Hugo Gascon, Christian Wressnegger, Fabian Yamaguchi, Daniel Arp, and Konrad Rieck. 2015. Pulsar: Stateful black-box fuzzing of proprietary network protocols. In Intl. Conf. on Sec. and Priv. in Comm. Sys.. 330–347.Google ScholarGoogle ScholarCross RefCross Ref
  11. Ahmad Hazimeh, Adrian Herrera, and Mathias Payer. 2020. Magma: A Ground-Truth Fuzzing Benchmark. ACM Meas. Anal. Comput. Syst., 4, 3 (2020).Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. George Klees, Andrew Ruef, Benji Cooper, Shiyi Wei, and Michael Hicks. 2018. Evaluating fuzz testing. In ACM Conf. on Comp. and Comm. Security. 2123–2138.Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. V. J. M. Manès, H. Han, C. Han, S. K. Cha, M. Egele, E. J. Schwartz, and M. Woo. 2019. The Art, Science, and Engineering of Fuzzing: A Survey. IEEE Trans. on Soft. Eng..Google ScholarGoogle ScholarCross RefCross Ref
  14. László Szekeres Jonathan Metzman, Abhishek Arya, and L Szekeres. 2020. FuzzBench: Fuzzer benchmarking as a service. Google Security Blog.Google ScholarGoogle Scholar
  15. Barton P. Miller, Louis Fredriksen, and Bryan So. 1990. An Empirical Study of the Reliability of UNIX Utilities. Commun. ACM.Google ScholarGoogle Scholar
  16. Van-Thuan Pham, Marcel Böhme, and Abhik Roychoudhury. 2020. AFLNET: A Greybox Fuzzer for Network Protocols. In Intl. Conf. on Software Testing, Verification and Validation (Testing Tools Track).Google ScholarGoogle Scholar
  17. Rapid7. 2020. Metasploit Vulnerability & Exploit Database. https://www.rapid7.com/db/?q=fuzzer&type=metasploit [Online; accessed 12-10-2020].Google ScholarGoogle Scholar
  18. R. Shapiro, S. Bratus, E. Rogers, and S. Smith. 2011. Identifying vulnerabilities in SCADA systems via fuzz-testing. In Intl. Conf. on Critical Infr. Protect.. 57–72.Google ScholarGoogle Scholar
  19. Synopsis, Inc.. 2020. Defensics Fuzz Testing. https://www.synopsys.com/software-integrity/security-testing/fuzz-testing.html [Online; accessed 12-10-2020].Google ScholarGoogle Scholar
  20. Ari Takanen, Jared D Demott, Charles Miller, and Atte Kettunen. 2018. Fuzzing for software security testing and quality assurance. Artech House.Google ScholarGoogle Scholar
  21. A. Walz and A. Sikora. 2017. Exploiting dissent: Towards fuzzing-based differential black box testing of TLS implementations. IEEE Trans. Dep. Sec. Comp..Google ScholarGoogle Scholar
  22. Zhiqiang Wang, Quanqi Li, Yazhe Wang, Biao Liu, Jianyi Zhang, and Qixu Liu. 2019. Medical Protocol Security: DICOM Vulnerability Mining Based on Fuzzing Technology. In ACM Conf. on Comp. and Comm. Security. 2549–2551.Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Michal Zalewski. 2020. AFL Documentation - Understanding the status screen. https://github.com/mirrorer/afl/blob/master/docs/status_screen.txt [Online; accessed 12-01-2021].Google ScholarGoogle Scholar
  24. Yaowen Zheng, Ali Davanian, Heng Yin, Chengyu Song, Hongsong Zhu, and Limin Sun. 2019. FIRM-AFL: High-throughput greybox fuzzing of IoT firmware via augmented process emulation. In 28th USENIX Security Symp.. 1099–1114.Google ScholarGoogle Scholar

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    • Published in

      cover image ACM Conferences
      ISSTA 2021: Proceedings of the 30th ACM SIGSOFT International Symposium on Software Testing and Analysis
      July 2021
      685 pages
      ISBN:9781450384599
      DOI:10.1145/3460319

      Copyright © 2021 ACM

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      Publication History

      • Published: 11 July 2021

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      Overall Acceptance Rate58of213submissions,27%

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