Model-Based Fuzzing Using Symbolic Transition Systems Wouter Bohlken
[email protected] January 31, 2021, 48 pages Academic supervisor: Dr. Ana-Maria Oprescu,
[email protected] Daily supervisor: Dr. Machiel van der Bijl,
[email protected] Host organisation: Axini, https://www.axini.com Universiteit van Amsterdam Faculteit der Natuurwetenschappen, Wiskunde en Informatica Master Software Engineering http://www.software-engineering-amsterdam.nl Abstract As software is getting more complex, the need for thorough testing increases at the same rate. Model- Based Testing (MBT) is a technique for thorough functional testing. Model-Based Testing uses a formal definition of a program and automatically extracts test cases. While MBT is useful for functional testing, non-functional security testing is not covered in this approach. Software vulnerabilities, when exploited, can lead to serious damage in industry. Finding flaws in software is a complicated, laborious, and ex- pensive task, therefore, automated security testing is of high relevance. Fuzzing is one of the most popular and effective techniques for automatically detecting vulnerabilities in software. Many differ- ent fuzzing approaches have been developed in recent years. Research has shown that there is no single fuzzer that works best on all types of software, and different fuzzers should be used for different purposes. In this research, we conducted a systematic review of state-of-the-art fuzzers and composed a list of candidate fuzzers that can be combined with MBT. We present two approaches on how to combine these two techniques: offline and online. An offline approach fully utilizes an existing fuzzer and automatically extracts relevant information from a model, which is then used for fuzzing.