Program-Adaptive Mutational Fuzzing

Explore an innovative algorithm designed to maximize bug detection in black-box mutational fuzzing during this 21-minute IEEE conference talk. Delve into the presenter's approach of leveraging white-box symbolic analysis on execution traces to identify input bit position dependencies. Learn how this dependency relation is utilized to compute a probabilistically optimal mutation ratio for specific program-seed pairs. Discover the promising results, showcasing an average of 38.6% more bugs found compared to three previous fuzzers across 8 applications within the same fuzzing timeframe. Gain insights into this advanced fuzzing technique presented at the 2015 IEEE Symposium on Security & Privacy in San Jose, CA.