NettetStateful greybox fuzzing. We discuss several heuristics to increase the coverage of the state space via greybox fuzzing. First, we propose to add generated inputs to the seed corpus that exercise new nodes in the STT. As we will demonstrate, code coverage alone is insufficient to capture the order across different requests.

Fugu-MT 論文翻訳(概要): ADI: Adversarial Dominating Inputs in …

Nettet2 dager siden · Directed greybox fuzzing guides fuzzers to explore specific objective code areas and has achieved good performance in some scenarios such as patch testing. … NettetIn this paper, we introduce Directed Greybox Fuzzing (DGF) which generates inputs with the objective of reaching a given set of target program locations efficiently. ... [SEC'20] … list of banks potentially in trouble

Proj THUDBFuzz Paper Reading: A Review of Machine Learning

NettetDuring the greybox fuzzing search, our tool AFLSMART measures the degree of validity of the inputs produced with respect to the file format specification. It prioritizes valid inputs over invalid ones, by enabling the fuzzer to explore more mutations of a valid file as opposed to an invalid one. As a result, our smart fuzzer largely Nettetseed using the blackbox fuzzer. Assume that our greybox fuzzer has the following mutation operator: Given a seed, choose an arbi-trary character uniformly at random and substitute it with another character chosen uniformly at random. Table 1: Expected #inputs to generate the next coverage-increasing seed (To), given the current corpus. Nettetegories of fuzzing tools and techniques: blackbox, greybox and whitebox fuzzing. Blackbox fuzzing generates inputs without any knowledge of the program. There are two main variants of blackbox fuzzing: mutational and gen-erational. In mutational blackbox fuzzing, the fuzz campaign starts with one or more seed inputs. list of banks that accept ach transfer