Boosting Fuzzer Efficiency: An Information Theoretic Perspective

Entropic is an information-theoretic power schedule implemented based on LibFuzzer. It boosts performance by changing weights assigned to the seeds in the corpus. Seeds revealing more “information” are assigned a higher weight. Entropic has been independently evaluated by a team at Google and invited for integration into mainline LibFuzzer @ LLVM (C++ code base), whereupon Entropic was subject to a substantial code reviewing process.

Ankou: Guiding Grey-box Fuzzing towards Combinatorial Difference

Grey-box fuzzing is an evolutionary process, which maintains and evolves a population of test cases with the help of a fitness …

The Art, Science, and Engineering of Fuzzing: A Survey

This paper surveys both the academic papers and the open-sourced tools in the field of fuzzing. We present a unified, general-purpose model to better understand the design and trade-offs of fuzzers.

Domain Isolated Kernel: A lightweight sandbox for untrusted kernel extensions

Monolithic kernel is one of the prevalent configurations out of various kernel design models. While monolithic kernel excels in …