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Open Access

Test Data Generation for Stateful Network Protocol Fuzzing Using a Rule-Based State Machine

Rui Ma( ), Daguang Wang, Changzhen Hu, Wendong Ji, Jingfeng Xue
Beijing Key Laboratory of Software Security Engineering Technology, School of Software, Beijing Institute of Technology, Beijing 100081, China.
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Abstract

To improve the efficiency and coverage of stateful network protocol fuzzing, this paper proposes a new method, using a rule-based state machine and a stateful rule tree to guide the generation of fuzz testing data. The method first builds a rule-based state machine model as a formal description of the states of a network protocol. This removes safety paths, to cut down the scale of the state space. Then it uses a stateful rule tree to describe the relationship between states and messages, and then remove useless items from it. According to the message sequence obtained by the analysis of paths using the stateful rule tree and the protocol specification, an abstract data model of test case generation is defined. The fuzz testing data is produced by various generation algorithms through filling data in the fields of the data model. Using the rule-based state machine and the stateful rule tree, the quantity of test data can be reduced. Experimental results indicate that our method can discover the same vulnerabilities as traditional approaches, using less test data, while optimizing test data generation and improving test efficiency.

Keywords

fuzzingstateful network protocoltest data generationrule-based state machinestateful rule tree

References

[1]
Pan Z., Liu C., Liu S., and Guo S., Vulnerability discovery technology and its applications, Journal of Software, vol. 8, no. 8, pp. 2000-2007, 2013.
Crossref Google Scholar
[2]
Chen J., Wang H., Towey D., Mao C., Huang R., and Zhan Y., Worst-input mutation approach to Web services vulnerability testing based on SOAP messages, Tsinghua Science & Technology, vol. 19, no. 5, pp. 429-441, 2014.
Crossref Google Scholar
[3]
Stutton M., Greene A., and Amini P., Fuzzing: Brute Force Vulnerability Discovery. London, UK: Pearson Education, 2007.
[4]
Banks G., Cova M., Felmetsger V., Almeroth K., Kemmerer R., and Vigna G., SNOOZE: Toward a stateful network protocol fuzzer, Lecture Notes in Computer Science, vol. 4176, pp. 343-358, 2006.
Crossref Google Scholar
[5]
Abdelnur H. J., State R., and Festor O., KIF: A stateful SIP fuzzer, in Proc. 1st Int. Principles, Systems & Applications of IP Telecommunications Conf., New York, NY, USA, 2007, pp. 47-56.
Crossref
[6]
Raniwala A., Sharma S., De P., Krishnan R., and Chiueh T. C., Evaluation of a stateful tansport protocol for multi-channel wireless mesh networks, in Proc. 15th IEEE Int. Quality of Service Workshop, Evanston, IL, USA, 2007, pp. 74-82.
Crossref
[7]
Alrahem T., Chen A., DiGiussepe N., Gee J., Hsiao S., and Mattox S., INTERSTATE: A stateful protocol fuzzer for SIP, Defcon, no. 15, pp. 1-5, 2007.
Google Scholar
[8]
Yu H. H., Research on vulnerbility discovering for network protocol based on fuzz testing, (in Chinese), MS thesis, Dept. Sci. & Tech., Huazhong University, Wuhan, China, 2008.
Google Scholar
[9]
Kitagawa T., Hanaoka M., and Kono K., AspFuzz: A state aware protocol fuzzer based on application-layer protocols, in Proc. IEEE Computers & Communications Symposium, Riccione, Italy, 2010, pp. 202-208.
Crossref
[10]
Akbar M. A. and Faroop M., RTP-miner: A real-time security framework for RTP fuzzing attacks, in Proc. 20th Int. Network & Operating Systems Support for Digital Audio & Video Workshop, Amsterdam, Netherlands, 2010, pp. 87-92.
Crossref
[11]
Gorbunov S. and Rosenbloom A., Autofuzz: Automated network protocol fuzzing framework, International Journal of Computer Science & Network Security, vol. 10, no. 8, pp. 239-245, 2010.
Google Scholar
[12]
Li M. W., Zhang A. F., Liu J. C., and Li Z. T., An automatic network protocol fuzz testing and vulnerability discovering method, (in Chinese), Chinese Journal of Computer, vol. 34, no. 2, pp. 242-255, 2011.
Crossref Google Scholar
[13]
Sui A. F., Tang W., Hu J. J., and Li M. Z., An effective fuzz input generation method for protocol testing, in Proc. 13th IEEE Int. Communication Technology Conf., Jinan, China, 2011, pp. 728-731.
[14]
Tsankov P., Dashti M. T., and Basin D., SECFUZZ: Fuzztesting security protocols, in Proc. 7th Int. Automation of Software Test Workshop, Zurich, Switzerland, 2012, pp. 1-7.
Crossref
[15]
Seo D., Lee H., and Nuwere E., SIPAD: SIP-VoIP anomaly detection using a stateful rule tree, Computer Communications, vol. 36, no. 5, pp. 562-574, 2013.
Crossref Google Scholar
[16]
Pan F., Hou Y., Hong Z., Wu L., and Lai H., Efficient model based fuzz testing using higher-order attribute grammars, Journal of Software, vol. 8, no. 3, pp. 645-651, 2013.
Crossref Google Scholar
[17]
Ma R., Ji W. D., Hu C. Z., Shan C., and Peng W., Fuzz testing data generation for network protocol using classification tree, in Proc. Communication Security Conf., Beijing, China, 2014, pp. 97-101.
[18]
Hu C. Z., Ma R., Han X., Shan C., and Wang Y., A rule-based method of designing model for stateful network protocol, (in Chinese), China Patent CN201410333944.0, Nov. 12, 2014.
Google Scholar
[19]
Sulley, https://github.com/OpenRCE/sulley, 2015.
[20]
RFC3261, http://www.ietf.org/rfc/rfc3261.txt, 2015.
[21]
CVE, http://cve.scap.org.cn/CVE-2012-1008.html, 2015.
Tsinghua Science and Technology
Volume 21 Issue 3,
June 2016
Pages 352-360
DOI: 10.1109/TST.2016.7488746
Cite this article:
Ma R, Wang D, Hu C, et al. Test Data Generation for Stateful Network Protocol Fuzzing Using a Rule-Based State Machine. Tsinghua Science and Technology, 2016, 21(3): 352-360. https://doi.org/10.1109/TST.2016.7488746

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Received: 22 January 2016
Accepted: 24 March 2016
Published: 13 June 2016
© The author(s) 2016
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