Software vulnerabilities are a grave threat to the security of computer systems. They often go undetected for years until it is too late and the consequences are irreversible. In order to find these weaknesses, software security testers and developers often have to manually test the entire codebase and determine if any vulnerabilities exist. However, this can take months or even years of work due to the scale of modern software projects.
One way of handling all this is with neural fuzzing. The fuzzing process throws random input at code or software, looking for bugs that might not have been found with traditional testing techniques. In recent years, approaches like neural fuzzing have emerged to make application security testing faster and more accurate.