• Fuzzing Against the Machine: Automate vulnerability research with emulated IoT devices on QEMU (2023)
• The Fuzzing Book (2019)
• The Art, Science, and Engineering of Fuzzing: A Survey (2019) - Actually, this document is a paper, but it contains more important and essential content than any other book.
• Fuzzing for Software Security Testing and Quality Assurance, 2nd Edition (2018)
• Fuzzing: Brute Force Vulnerability Discovery, 1st Edition (2007)
• Open Source Fuzzing Tools, 1st Edition (2007)

To achieve a well-defined scope, I have chosen to include publications on fuzzing from 4 top major security conferences (2008–2025): (i) Network and Distributed System Security Symposium (NDSS), (ii) IEEE Symposium on Security and Privacy (S&P), (iii) USENIX Security Symposium (USEC), and (iv) ACM Conference on Computer and Communications Security (CCS).

Note: Papers are selected based on whether the title contains the keyword "fuzz." If a paper is related to fuzzing but does not include "fuzz" in its title, it may have been missed. In that case, please open a Pull Request and it will be reviewed for inclusion.

A curated collection of open-source fuzzing tools, organized by target category based on the taxonomy from fuzzing-survey.org. Tools are selected based on a combination of factors including GitHub popularity, recency, availability of official repositories from original authors, and whether the project is actively maintained.

• ACTOR (2023) - An action-guided kernel fuzzing framework that generates inputs leveraging triggered actions and their temporal relationships.
• NTFuzz (2021) - A type-aware Windows kernel fuzzer that statically analyzes system binaries to infer system call types for more effective fuzzing.
• KRACE (2020) - A coverage-guided fuzzing framework that detects data races in kernel file systems by exploring concurrency through multi-threaded syscall sequences.
• Razzer (2019) - A kernel fuzzer that uses static analysis and two-phase fuzzing to detect race conditions and concurrency bugs in Linux kernels.
• Hydra (2019) - A fuzzing framework for automatically discovering semantic bugs in file systems using input mutators, feedback engines, and customizable checkers.
• Janus (2019) - A file system fuzzer that finds memory corruptions in Linux kernel file systems by mutating both filesystem images and syscall sequences simultaneously.
• DIFUZE (2017) - An interface-aware fuzzer for Linux kernel drivers that automatically recovers ioctl interfaces via LLVM analysis and generates targeted test cases.
• IMF (2017) - A kernel API fuzzer that leverages automated API model inference to discover vulnerabilities in macOS kernel APIs.
• kAFL (2017) - A hardware-assisted x86-64 VM kernel fuzzing framework with performant VM reloads for finding OS kernel vulnerabilities.
• syzkaller (2015) - An unsupervised coverage-guided kernel fuzzer supporting FreeBSD, Fuchsia, gVisor, Linux, NetBSD, OpenBSD, and Windows.
• Trinity (2012) - A Linux system call fuzzer that generates semi-intelligent random arguments to syscalls, including valid file descriptors, flags, and range-biased values.