CIS Seminar: “Expanding the Reach of Fuzzing”

Software bugs are pervasive in modern software. As software is integrated into increasingly many aspects of our lives, these bugs have increasingly severe consequences, both from a security (e.g. Cloudbleed, Heartbleed, Shellshock) and cost standpoint. Fuzzing refers to a set of techniques that automatically find bug-triggering inputs by sending many random-looking inputs to the program under test. In this talk, I will discuss how, by identifying core under-generalized components of modern fuzzing algorithms, and building algorithms that generalize or tune these components, I have expanded the application domains of fuzzing. First, by building a general feedback-directed fuzzing algorithm, I enabled fuzzing to consistently find performance and resource consumption errors. Second, by developing techniques to maintain structure during mutation, I brought fuzzing exploration to “deeper” program states. Third, by decoupling the user-facing abstraction of random input generators from their sampling distributions, I built faster validity fuzzing and even tackled program synthesis. Finally, I will discuss the key research problems that must be tackled to make fuzzing readily-available and useful to all developers.