Fuzzing: a survey

TLDR

Security vulnerabilities drive cyber‑security threats, and fuzzing—especially modern tools like AFL—has become the most widely used technique for early vulnerability discovery. This survey reviews recent advances in fuzzing, evaluates how they enhance the process, and identifies directions for future research. The authors compare fuzzing with other discovery methods, provide an overview of coverage‑based fuzzing, and discuss additional techniques that increase fuzzing intelligence and efficiency. The paper highlights practical applications of fuzzing, emerging trends, and outlines potential future developments in the field.

Abstract

Security vulnerability is one of the root causes of cyber-security threats. To discover vulnerabilities and fix them in advance, researchers have proposed several techniques, among which fuzzing is the most widely used one. In recent years, fuzzing solutions, like AFL, have made great improvements in vulnerability discovery. This paper presents a summary of the recent advances, analyzes how they improve the fuzzing process, and sheds light on future work in fuzzing. Firstly, we discuss the reason why fuzzing is popular, by comparing different commonly used vulnerability discovery techniques. Then we present an overview of fuzzing solutions, and discuss in detail one of the most popular type of fuzzing, i.e., coverage-based fuzzing. Then we present other techniques that could make fuzzing process smarter and more efficient. Finally, we show some applications of fuzzing, and discuss new trends of fuzzing and potential future directions.