Fuzz testing (fuzzing) has witnessed its prosperity in detecting security flaws recently. It
generates a large number of test cases and monitors the executions for defects. Fuzzing has …

Security attacks abuse software vulnerabilities of IoT devices; hence, detecting and
eliminating these vulnerabilities immediately are crucial. Fuzzing is an efficient method to …

In this paper, we present AFL++, a community-driven open-source tool that incorporates
state-of-the-art fuzzing research, to make the research comparable, reproducible …

Among the many software testing techniques available today, fuzzing has remained highly
popular due to its conceptual simplicity, its low barrier to deployment, and its vast amount of …

Fuzzing is a popular technique for finding software bugs. However, the performance of the
state-of-the-art fuzzers leaves a lot to be desired. Fuzzers based on symbolic execution …

Existing Greybox Fuzzers (GF) cannot be effectively directed, for instance, towards
problematic changes or patches, towards critical system calls or dangerous locations, or …

Large language models (LLMs) have demonstrated significant potential in various tasks,
including vulnerability detection. However, current efforts in this area are preliminary, lacking …

In recent years, fuzz testing has proven itself to be one of the most effective techniques for
finding correctness bugs and security vulnerabilities in practice. One particular fuzz testing …

Coverage-guided fuzzing is a widely used and effective solution to find software
vulnerabilities. Tracking code coverage and utilizing it to guide fuzzing are crucial to …

Coverage-based Greybox Fuzzing (CGF) is a random testing approach that requires no
program analysis. A new test is generated by slightly mutating a seed input. If the test …