Network Fuzzing: State of the art

As fuzzing has seen increased interest not only in academia but also in industry settings, algorithmic advancements have become increasingly difficult to obtain. Moreover, the computational requirements for finding new bugs in well known Open Source projects have also experienced an upturn. These factors have prompted a shift in focus towards a previously neglected but critical type of stateful system: network applications. In this paper we present an overview of recent network fuzzing advancements, implementation techniques used in state-of-the-art fuzzers, and benchmarking frameworks used in fuzzer evaluation and scale testing. Our goal is to provide a better understanding of current day challenges and research directions with respect to network fuzzing.