Software security vulnerabilities are one of the critical issues in the realm of computer
security. Due to their potential high severity impacts, many different approaches have been …

Fuzzing is an effective and widely used technique for finding security bugs and
vulnerabilities in software. It inputs irregular test data into a target program to try to trigger a …

Context: Previous studies have shown that existing deep learning-based approaches can
significantly improve the performance of vulnerability detection. They represent code in …

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

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 …

Fuzzing is an effective software testing technique to find bugs. Given the size and complexity
of real-world applications, modern fuzzers tend to be either scalable, but not effective in …

The vast majority of security breaches encountered today are a direct result of insecure
code. Consequently, the protection of computer systems critically depends on the rigorous …

We present Harvey, an industrial greybox fuzzer for smart contracts, which are programs
managing accounts on a blockchain. Greybox fuzzing is a lightweight test-generation …

The Internet of Things is the evolutionary step of the Internet that creates a worldwide
infrastructure interconnecting machines and humans. As the Internet became public in the …

Coverage-based fuzzing has been actively studied and widely adopted for finding
vulnerabilities in real-world software applications. With coverage information, such as …