Year: 2021
Type: preprint
Abstract: Fuzz Testing techniques are the state of the art in software testing for security issues nowadays. Their great effectiveness attracted the attention of researchers and hackers and involved them in developing a lot of new techniques to improve Fuzz Testing. The evaluation and the cross-comparison of these techniques is an almost open problem. In this paper, we propose a human-driven approach to this problem based on information visualization. We developed a prototype upon the AFL++ fuzzing framework, FuzzSplore, that an analyst can use to get useful insights about different fuzzing configurations applied to a specific target in order to choose or tune the best technique during a fuzzing campaign.
Source: arXiv (Cornell University)
Authors: Fioraldi, Andrea, Pileggi, Luigi Paolo
Institution: Sapienza University of Rome
Language: English
Subfield: Software
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3128661280