In a network security system, security flaws are crucial. Fuzzing is a vulnerability detection technique that is extensively utilized to prevent damage before it occurs. Traditional fuzz testing, on the other hand, has a number of difficulties, including how to successfully alter input seed files, increase code coverage, and avoid format verification. In order to address these issues, machine learning techniques have been proposed as a new method in fuzz testing.
