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Fuzz testing (or fuzzing) is an effective technique used to find security vulnerabilities. It consists of feeding a software under test with malformed inputs, waiting for a weird system behaviour (often a crash of the system). Over the…

密码学与安全 · 计算机科学 2023-03-14 Marcello Maugeri , Cristian Daniele , Giampaolo Bella , Erik Poll

Fuzzing is a widely used software security testing technique that is designed to identify vulnerabilities in systems by providing invalid or unexpected input. Continuous fuzzing systems like OSS-FUZZ have been successful in finding security…

密码学与安全 · 计算机科学 2023-07-04 Chaitanya Rahalkar

Fuzzing has become the de facto standard technique for finding software vulnerabilities. However, even state-of-the-art fuzzers are not very efficient at finding hard-to-trigger software bugs. Most popular fuzzers use evolutionary guidance…

密码学与安全 · 计算机科学 2019-07-16 Dongdong She , Kexin Pei , Dave Epstein , Junfeng Yang , Baishakhi Ray , Suman Jana

Coverage-based graybox fuzzer (CGF), such as AFL has gained great success in vulnerability detection thanks to its ease-of-use and bug-finding power. Since some code fragments such as memory allocation are more vulnerable than others,…

密码学与安全 · 计算机科学 2021-03-02 Wenshuo Wang , Liang Cheng , Yang Zhang

GPUs play an increasingly important role in modern software. However, the heterogeneous host-device execution model and expanding software stacks make GPU programs prone to memory-safety and concurrency bugs that evade static analysis.…

密码学与安全 · 计算机科学 2026-03-16 Mohamed Tarek Ibn ziad , Christos Kozyrakis

Fuzzing has become one of the most popular techniques to identify bugs in software. To improve the fuzzing process, a plethora of techniques have recently appeared in academic literature. However, evaluating and comparing these techniques…

密码学与安全 · 计算机科学 2021-08-17 David Paaßen , Sebastian Surminski , Michael Rodler , Lucas Davi

In recent years, fuzz testing has benefited from increased computational power and important algorithmic advances, leading to systems that have discovered many critical bugs and vulnerabilities in production software. Despite these…

密码学与安全 · 计算机科学 2022-05-31 Anastasios Andronidis , Cristian Cadar

Fuzzing is a popular vulnerability automated testing method utilized by professionals and broader community alike. However, despite its abilities, fuzzing is a time-consuming, computationally expensive process. This is problematic for the…

软件工程 · 计算机科学 2023-07-25 Michael Wang , Michael Robinson

Fuzzing -- testing programs with random inputs -- has become the prime technique to detect bugs and vulnerabilities in programs. To generate inputs that cover new functionality, fuzzers require execution feedback from the program -- for…

软件工程 · 计算机科学 2020-12-29 Rahul Gopinath , Bachir Bendrissou , Björn Mathis , Andreas Zeller

Fuzzing is widely used for software vulnerability detection. There are various kinds of fuzzers with different fuzzing strategies, and most of them perform well on their targets. However, in industry practice and empirical study, the…

软件工程 · 计算机科学 2019-05-07 Yuanliang Chen , Yu Jiang , Fuchen Ma , Jie Liang , Mingzhe Wang , Chijin Zhou , Zhuo Su , Xun Jiao

Fuzzing is utilized for testing software and systems for cybersecurity risk via the automated adaptation of inputs. It facilitates the identification of software bugs and misconfigurations that may create vulnerabilities, cause abnormal…

密码学与安全 · 计算机科学 2023-06-08 Jack Hance , Jeremy Straub

Buffer-overruns are a prevalent vulnerability in software libraries and applications. Fuzz testing is one of the effective techniques to detect vulnerabilities in general. Greybox fuzzers such as AFL automatically generate a sequence of…

软件工程 · 计算机科学 2021-04-22 Raveendra Kumar Medicherla , Malathy Nagalakshmi , Tanya Sharma , Raghavan Komondoor

Fuzzing has proven to be very effective for discovering certain classes of software flaws, but less effective in helping developers process these discoveries. Conventional crash-based fuzzers lack enough information about failures to…

密码学与安全 · 计算机科学 2024-11-04 Allison Naaktgeboren , Sean Noble Anderson , Andrew Tolmach , Greg Sullivan

Fuzz testing is a fundamental technique employed to identify vulnerabilities within software systems. However, the process can be protracted and resource-intensive, especially when confronted with extensive codebases. In this work, I…

软件工程 · 计算机科学 2024-12-12 Saket Upadhyay

As researchers, we already understand how to make testing more effective and efficient at finding bugs. However, as fuzzing (i.e., automated testing) becomes more widely adopted in practice, practitioners are asking: Which assurances does a…

软件工程 · 计算机科学 2018-12-18 Marcel Böhme

Over 70% of security vulnerabilities in critical software systems today result from memory safety violations. To address this challenge, fuzzing and static analysis are widely used automated methods to discover such vulnerabilities. Fuzzing…

密码学与安全 · 计算机科学 2026-03-31 Keno Hassler , Philipp Görz , Stephan Lipp

BACKGROUND: Software engineers must be vigilant in preventing and correcting vulnerabilities and other critical bugs. In servicing this need, numerous tools and techniques have been developed to assist developers. Fuzzers, by autonomously…

软件工程 · 计算机科学 2023-05-22 Brandon Keller , Andrew Meneely , Benjamin Meyers

Fuzz testing, or fuzzing, has become one of the de facto standard techniques for bug finding in the software industry. In general, fuzzing provides various inputs to the target program to discover unhandled exceptions and crashes. In…

软件工程 · 计算机科学 2021-09-20 Yifan Wang , Yuchen Zhang , Chengbin Pang , Peng Li , Nikolaos Triandopoulos , Jun Xu

Grey-box fuzz testing has revealed thousands of vulnerabilities in real-world software owing to its lightweight instrumentation, fast coverage feedback, and dynamic adjusting strategies. However, directly applying grey-box fuzzing to…

软件工程 · 计算机科学 2020-08-03 Hongxu Chen , Shengjian Guo , Yinxing Xue , Yulei Sui , Cen Zhang , Yuekang Li , Haijun Wang , Yang Liu

Semantic understanding of programs has attracted great attention in the community. Inspired by recent successes of large language models (LLMs) in natural language understanding, tremendous progress has been made by treating programming…

机器学习 · 计算机科学 2023-06-13 Jianyu Zhao , Yuyang Rong , Yiwen Guo , Yifeng He , Hao Chen