Best Fuzz Testing Tools

PortSwigger Burp Suite Professional

PortSwigger

Hands-on security testers need the best tools for the job. Tools you have faith in, and enjoy using all day long. The tools that other professionals trust. Burp Suite Professional is the web security tester's toolkit of choice. Use it to automate repetitive testing tasks, then dig deeper with its expert-designed manual and semi-automated security testing tools. Burp Suite Professional can help you to test for OWASP top 10 vulnerabilities, as well as the very latest hacking techniques. Smart automation works in concert with expert-designed manual tools, to save you time. Optimize your workflow, and do more of what you do best. Burp Scanner can navigate and scan JavaScript-heavy single-page applications (SPAs), scan APIs, and enable the prerecording of complex authentication sequences. A toolkit designed and used by professional testers. Utilize features like the ability to record everything you did on an engagement and a powerful search function to improve efficiency and reliability.

Starting Price: $449 per year

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Peach Fuzzer

Peach Tech

Peach is a SmartFuzzer that is capable of performing both generation and mutation-based fuzzing. Peach requires the creation of Peach Pit files that define the structure, type information, and relationships in the data to be fuzzed. It additionally allows for the configuration of a fuzzing run including selecting a data transport (publisher), logging interface, etc. Peach has been under active development since 2004 and is in its third major version. Fuzzing continues to be the fastest way to find security issues and test for bugs. Effective hardware fuzzing with Peach will introduce students to the fundamentals of device fuzzing. Peach was designed to fuzz any type of data consumer from servers to embedded devices. Researchers, corporations, and governments already use Peach to find vulnerabilities in hardware. This course will focus on using Peach to target embedded devices and collect information from the device in the event of a crash.

Starting Price: Free

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Etheno

Crytic

Etheno is an Ethereum-testing, JSON RPC multiplexer, analysis tool wrapper, and test integration tool. It eliminates the complexity of setting up analysis tools like Echidna on large, multi-contract projects. If you are a smart contract developer, you should use Etheno to test your contracts. If you are an Ethereum client developer, you should use Etheno to perform differential testing on your implementation. Etheno runs a JSON RPC server that can multiplex calls to one or more clients. API for filtering and modifying JSON RPC calls. Enables differential testing by sending JSON RPC sequences to multiple Ethereum clients. Deploy to and interact with multiple networks at the same time. Integration with test frameworks like Ganache and Truffle. Run a local test network with a single command. Use our prebuilt Docker container to quickly install and try Etheno. Etheno can be used in many different ways and therefore, has numerous command-line argument combinations.

Starting Price: Free

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Solidity Fuzzing Boilerplate

patrickd

Solidity Fuzzing Boilerplate is a template repository intended to ease fuzzing components of Solidity projects, especially libraries. Write tests once and run them with both Echidna and Foundry's fuzzing. Fuzz components that use incompatible Solidity versions by deploying those into a Ganache instance via Etheno. Use HEVM's FFI cheat code to generate complex fuzzing inputs or to compare outputs with non-EVM executables while doing differential fuzzing. Publish your fuzzing experiments without worrying about licensing by extending the shell script to download specific files. Turn off FFI if you don't intend to make use of shell commands from your Solidity contracts. Note that FFI is slow and should only be used as a workaround. It can be useful for testing against things that are difficult to implement within Solidity and already exist in other languages. Before executing tests of a project that has FFI enabled, be sure to check what commands are actually being executed.

Starting Price: Free

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hevm

DappHub

The hevm project is an implementation of the Ethereum Virtual Machine (EVM) made specifically for symbolic execution, unit testing, and debugging of smart contracts. It is developed by DappHub and integrates especially well with the DappHub tool suite. The hevm command line program can symbolically execute smart contracts, run unit tests, interactively debug contracts while showing the Solidity source, or run arbitrary EVM code. Computations can be performed using a local state set up in a testing harness or fetched on demand from live networks using RPC calls. Run a symbolic execution against the given parameters, searching for assertion violations. One can also specialize specific arguments to a function signature while leaving others abstract. hevm uses an eager approach for symbolic execution, meaning that it will first attempt to explore all branches of the program.

Starting Price: Free

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Tayt

Crytic

Tayt is a StarkNet smart contract fuzzer. We recommend using a Python virtual environment. When starting you will see the properties to be checked and the external functions used to generate a sequence of transactions. Eventually, if a property is violated a call sequence will be presented with the order of functions to be called, the respective arguments passed, the caller address, and the events emitted. With Tayt, you can test a contract that deploys other contracts.

Starting Price: Free

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ImmuneBytes

Fortify your blockchains with our impeccable audit services for unparalleled security in the decentralized realm. If you're spending sleepless nights worrying about losing funds to hackers, choose from our stack of services, and bid farewell to all your fears. In-depth analysis of the code by industry veterans to detect the vulnerabilities in your smart contract. Our experts secure your blockchain applications by mitigating risks through security design, assessment, audit, and compliance services. Our independent team of prolific penetration testers performs an extensive exercise to detect vulnerabilities and system exploits. We are the torch-bearers of making the space safer for everyone and do it by helping with a complete, systematic analysis to enhance the product's overall security. Recovery of funds is as equally important as a security audit. Have the facility to track user funds with our transaction risk monitoring system and boost users' confidence.

Starting Price: Free

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Google OSS-Fuzz

Google

OSS-Fuzz offers continuous fuzzing for open source software. Fuzz testing is a well-known technique for uncovering programming errors in software. Many of these detectable errors, like buffer overflow, can have serious security implications. Google has found thousands of security vulnerabilities and stability bugs by deploying guided in-process fuzzing of Chrome components, and we now want to share that service with the open source community. OSS-Fuzz aims to make common open source software more secure and stable by combining modern fuzzing techniques with scalable, distributed execution. Projects that do not qualify for OSS-Fuzz can run their own instances of ClusterFuzz or ClusterFuzzLite. Currently, OSS-Fuzz supports C/C++, Rust, Go, Python, and Java/JVM code. Other languages supported by LLVM may work too. OSS-Fuzz supports fuzzing x86_64 and i386 builds.

Starting Price: Free

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Fuzzing Project

Fuzzing is a powerful strategy to find bugs in software. The idea is quite simple, which is to generate a large number of randomly malformed inputs for the software to parse and see what happens. If the program crashes then something is likely wrong. While fuzzing is a well-known strategy, it is surprisingly easy to find bugs, often with security implications, in widely used software. Memory access errors are the errors most likely to be exposed when fuzzing software that is written in C/C++. While they differ in the details, the core problem is often the same, the software reads or writes to the wrong memory locations. A modern Linux or BSD system ships a large number of basic tools that do some kind of file displaying and parsing. In their current state, most of these tools are not suitable for untrusted inputs. On the other hand, we have powerful tools these days that allow us to find and analyze these bugs.

Starting Price: Free

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LibFuzzer

LLVM Project

LibFuzzer is an in-process, coverage-guided, evolutionary fuzzing engine. LibFuzzer is linked with the library under test, and feeds fuzzed inputs to the library via a specific fuzzing entry point (or target function); the fuzzer then tracks which areas of the code are reached, and generates mutations on the corpus of input data in order to maximize the code coverage. The code coverage information for libFuzzer is provided by LLVM’s SanitizerCoverage instrumentation. LibFuzzer is still fully supported in that important bugs will get fixed. The first step in using libFuzzer on a library is to implement a fuzz target, a function that accepts an array of bytes and does something interesting with these bytes using the API under test. Note that this fuzz target does not depend on libFuzzer in any way so it is possible and even desirable to use it with other fuzzing engines like AFL and/or Radamsa.

Starting Price: Free

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american fuzzy lop

Google

American fuzzy lop is a security-oriented fuzzer that employs a novel type of compile-time instrumentation and genetic algorithms to automatically discover clean, interesting test cases that trigger new internal states in the targeted binary. This substantially improves the functional coverage for the fuzzed code. The compact synthesized corpora produced by the tool are also useful for seeding other, more labor or resource-intensive testing regimes down the road. Compared to other instrumented fuzzers, afl-fuzz is designed to be practical, it has a modest performance overhead, uses a variety of highly effective fuzzing strategies and effort minimization tricks, requires essentially no configuration, and seamlessly handles complex, real-world use cases, say, common image parsing or file compression libraries. It's an instrumentation-guided genetic fuzzer capable of synthesizing complex file semantics in a wide range of non-trivial targets.

Starting Price: Free

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Honggfuzz

Google

Honggfuzz is a security-oriented software fuzzer. Supports evolutionary, feedback-driven fuzzing based on code coverage (SW and HW-based). It’s multi-process and multi-threaded, there’s no need to run multiple copies of your fuzzer, as Honggfuzz can unlock the potential of all your available CPU cores with a single running instance. The file corpus is automatically shared and improved between all fuzzed processes. It’s blazingly fast when the persistent fuzzing mode is used. A simple/empty LLVMFuzzerTestOneInput function can be tested with up to 1mo iteration per second on a relatively modern CPU. Has a solid track record of uncovered security bugs, the only (to date) vulnerability in OpenSSL with the critical score mark was discovered by Honggfuzz. As opposed to other fuzzers, it will discover and report hijacked/ignored signals from crashes (intercepted and potentially hidden by a fuzzed program).

Starting Price: Free

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Ffuf

Ffuf is a fast web fuzzer written in Go. You can also practice your Ffuf scans against a live host with different lessons and use cases either locally by using the Docker container or against the live-hosted version. Provides virtual host discovery (without DNS records). In order to tell Ffuf about different inputs to test out, a wordlist is needed. You can supply one or more wordlists on the command line, and in case you wish (or are using multiple wordlists) you can choose a custom keyword for them. You can supply Ffuf with multiple wordlists (remember to configure a custom keyword for them though). The first word of the first wordlist is tested against all the words from the second wordlist before moving along to test the second word in the first wordlist against all the words in the second wordlist. In short, all of the different combinations are tried out. There are quite a few different ways to customize the request.

Starting Price: Free

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ToothPicker

Secure Mobile Networking Lab

ToothPicker is an in-process, coverage-guided fuzzer for iOS. It was developed to specifically target iOS's Bluetooth daemon and to analyze various Bluetooth protocols on iOS. As it is built using FRIDA, it can be adapted to target any platform that runs FRIDA. This repository also includes an over-the-air fuzzer with an exemplary implementation to fuzz Apple's MagicPairing protocol using InternalBlue. Additionally, it contains the ReplayCrashFile script that can be used to verify crashes the in-process fuzzer has found. This is a very simple fuzzer that only flips bits and bytes of inactive connections. No coverage, no injection, but nice as a demo and stateful. Runs just with Python and Frida, no modules or installation are required. ToothPicker is built on the codebase of frizzer. It is recommended to set up a virtual Python environment for frizzer. Starting from the iPhone XR/Xs, PAC has been introduced.

Starting Price: Free

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afl-unicorn

Battelle

afl-unicorn lets you fuzz any piece of binary that can be emulated by Unicorn Engine. If you can emulate the code you’re interested in using the Unicorn Engine, you can fuzz it with afl-unicorn. Unicorn Mode works by implementing the block-edge instrumentation that AFL’s QEMU mode normally does into Unicorn Engine. Basically, AFL will use block coverage information from any emulated code snippet to drive its input generation. The whole idea revolves around the proper construction of a Unicorn-based test harness. The Unicorn-based test harness loads the target code, sets up the initial state, and loads in data mutated by AFL from disk. The test harness then emulates the target binary code, and if it detects that a crash or error occurred it throws a signal. AFL will do all its normal stuff, but it’s actually fuzzing the emulated target binary code. Only tested on Ubuntu 16.04 LTS, but it should work smoothly with any OS capable of running both AFL and Unicorn.

Starting Price: Free

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Fuzzbuzz

The Fuzzbuzz workflow is very similar to other CI/CD testing workflows. However, unlike other testing workflows, fuzz testing requires multiple jobs to run simultaneously, which results in a few extra steps. Fuzzbuzz is a fuzz testing platform. We make it trivial for developers to add fuzz tests to their code and run them in CI/CD, helping them catch critical bugs and vulnerabilities before they hit production. Fuzzbuzz completely integrates into your environment, following you from the terminal to CI/CD. Write a fuzz test in your environment and use your own IDE, terminal, or build tools. Push to CI/CD and Fuzzbuzz will automatically start running your fuzz tests against your latest code changes. Get notified when bugs are found through Slack, GitHub, or email. Catch regressions as new changes are automatically tested and compared to previous runs. Code is built and instrumented by Fuzzbuzz as soon as a change is detected.

Starting Price: Free

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Sulley

OpenRCE

Sulley is a fuzzing engine and fuzz testing framework consisting of multiple extensible components. Sulley (IMHO) exceeds the capabilities of most previously published fuzzing technologies, commercial and public domain. The goal of the framework is to simplify not only data representation but to simplify data transmission and instrumentation. A pure-Python fully automated and unattended fuzzing framework. Sulley not only has impressive data generation but has taken this a step further and includes many other important aspects a modern fuzzer should provide. Sulley watches the network and methodically maintains records. Sulley instruments and monitors the health of the target, capable of reverting to a known good state using multiple methods. Sulley detects, tracks, and categorizes detected faults. Sulley can fuzz in parallel, significantly increasing test speed. Sulley can automatically determine what unique sequence of test cases triggers faults.

Starting Price: Free

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Radamsa

Aki Helin

Radamsa is a test case generator for robustness testing or fuzzer. It is typically used to test how well a program can withstand malformed and potentially malicious inputs. It works by reading sample files of valid data and generating interestingly different outputs from them. The main selling points of Radamsa are that it has already found a slew of bugs in programs that actually matter, it is easily scriptable, and, easy to get up and running. Fuzzing is one of the techniques to find unexpected behavior in programs. The idea is simply to subject the program to various kinds of inputs and see what happens. There are two parts to this process: getting the various kinds of inputs and how to see what happens. Radamsa is a solution to the first part, and the second part is typically a short shell script. Testers usually have a more or less vague idea of what should not happen, and they try to find out if this is so.

Starting Price: Free

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Jazzer

Code Intelligence

Jazzer is a coverage-guided, in-process fuzzer for the JVM platform developed by Code Intelligence. It is based on libFuzzer and brings many of its instrumentation-powered mutation features to the JVM. You can use Docker to try out Jazzer's autofuzz mode, which automatically generates arguments to a given Java function and reports unexpected exceptions and detected security issues. You can also use GitHub release archives to run a standalone Jazzer binary that starts its own JVM configured for fuzzing.

Starting Price: Free

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FuzzDB

FuzzDB was created to increase the likelihood of finding application security vulnerabilities through dynamic application security testing. It's the first and most comprehensive open dictionary of fault injection patterns, predictable resource locations, and regex for matching server responses. FuzzDB contains comprehensive lists of attack payload primitives for fault injection testing. These patterns, categorized by the attack and where appropriate platform type, are known to cause issues like OS command injection, directory listings, directory traversals, source exposure, file upload bypass, authentication bypass, XSS, HTTP header crlf injections, SQL injection, NoSQL injection, and more. For example, FuzzDB catalogs 56 patterns that can potentially be interpreted as a null byte and contains lists of commonly used methods and name-value pairs that trigger debug modes.

Starting Price: Free

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Google ClusterFuzz

Google

ClusterFuzz is a scalable fuzzing infrastructure that finds security and stability issues in software. Google uses ClusterFuzz to fuzz all Google products and as the fuzzing backend for OSS-Fuzz. ClusterFuzz provides many features to seamlessly integrate fuzzing into a software project’s development process. Fully automatic bug filing, triage, and closing for various issue trackers. Supports multiple coverages guided fuzzing engines for optimal results (with ensemble fuzzing and fuzzing strategies). Statistics for analyzing fuzzer performance, and crash rates. Easy to use web interface for management and viewing crashes. Support for various authentication providers using Firebase. Support for black-box fuzzing, test case minimization, and regression finding through bisection.

Starting Price: Free

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go-fuzz

dvyukov

Go-fuzz is a coverage-guided fuzzing solution for testing Go packages. Fuzzing is mainly applicable to packages that parse complex inputs (both text and binary) and is especially useful for hardening systems that parse inputs from potentially malicious users (anything accepted over a network). go-fuzz has recently added preliminary support for fuzzing Go Modules. If you encounter a problem with modules, please file an issue with details. Data is a random input generated by go-fuzz, note that in most cases it is invalid. The function must return 1 if the fuzzer should increase the priority of the given input during subsequent fuzzing if the input must not be added to the corpus even if it gives new coverage, and 0 otherwise; other values are reserved for future use. The fuzz function must be in a package that go-fuzz can import. This means the code you want to test can't be in package main. Fuzzing internal packages is supported, however.

Starting Price: Free

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Wfuzz

Wfuzz provides a framework to automate web application security assessments and could help you secure your web applications by finding and exploiting web application vulnerabilities. You can also run Wfuzz from the official Docker image. Wfuzz is based on the simple concept that it replaces any reference to the fuzz keyword with the value of a given payload. A payload in Wfuzz is a source of data. This simple concept allows any input to be injected in any field of an HTTP request, allowing it to perform complex web security attacks in different web application components such as parameters, authentication, forms, directories/files, headers, etc. Wfuzz’s web application vulnerability scanner is supported by plugins. Wfuzz is a completely modular framework and makes it easy for even the newest Python developers to contribute. Building plugins is simple and takes little more than a few minutes.

Starting Price: Free

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Fuzzapi

Fuzzapi is a tool used for REST API pentesting and uses API Fuzzer and provides UI solutions for gem.

Starting Price: Free

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Wapiti

Wapiti is a web application vulnerability scanner. Wapiti allows you to audit the security of your websites or web applications. It performs "black-box" scans (it does not study the source code) of the web application by crawling the webpages of the deployed web app, looking for scripts and forms where it can inject data. Once it gets the list of URLs, forms, and their inputs, Wapiti acts like a fuzzer, injecting payloads to see if a script is vulnerable. Search for potentially dangerous files on the server. Wapiti supports both GET and POST HTTP methods for attacks. It also supports multipart forms and can inject payloads in filenames (upload). Warnings are raised when an anomaly is found (for example 500 errors and timeouts). Wapiti is able to make the difference between permanent and reflected XSS vulnerabilities. Generates vulnerability reports in various formats (HTML, XML, JSON, TXT, CSV).

Starting Price: Free

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Echidna

Crytic

Echidna is a Haskell program designed for fuzzing/property-based testing of Ethereum smart contracts. It uses sophisticated grammar-based fuzzing campaigns based on a contract ABI to falsify user-defined predicates or Solidity assertions. We designed Echidna with modularity in mind, so it can be easily extended to include new mutations or test specific contracts in specific cases. Generates inputs tailored to your actual code. Optional corpus collection, mutation and coverage guidance to find deeper bugs. Powered by Slither to extract useful information before the fuzzing campaign. Source code integration to identify which lines are covered after the fuzzing campaign. Interactive terminal UI, text-only or JSON output. Automatic test case minimization for quick triage. Seamless integration into the development workflow. Maximum gas usage reporting of the fuzzing campaign. Support for a complex contract initialization with Etheno and Truffle.

Starting Price: Free

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syzkaller

Google

syzkaller is an unsupervised coverage-guided kernel fuzzer. Supports FreeBSD, Fuchsia, gVisor, Linux, NetBSD, OpenBSD, and Windows. Initially, syzkaller was developed with Linux kernel fuzzing in mind, but now it's being extended to support other OS kernels as well. Once syzkaller detects a kernel crash in one of the VMs, it will automatically start the process of reproducing this crash. By default, it will use 4 VMs to reproduce the crash and then minimize the program that caused it. This may stop the fuzzing, since all of the VMs might be busy reproducing detected crashes. The process of reproducing one crash may take from a few minutes up to an hour depending on whether the crash is easily reproducible or non-reproducible at all.

Starting Price: Free

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Black Duck

Black Duck, part of the Synopsys Software Integrity Group, is a leading provider of application security testing (AST) solutions. Their comprehensive portfolio includes tools for static analysis, software composition analysis (SCA), dynamic analysis, and interactive analysis, enabling organizations to identify and mitigate security vulnerabilities throughout the software development life cycle. By automating the discovery and management of open-source software, Black Duck ensures compliance with security and licensing standards. Their solutions are designed to help organizations build trust in their software by managing application security, quality, and compliance risks at the speed their business demands. Black Duck empowers businesses to innovate securely and deliver software with confidence.

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Awesome Fuzzing

secfigo

Awesome Fuzzing is a list of fuzzing resources including books, courses, both free and paid, videos, tools, tutorials, and vulnerable applications to practice in order to learn fuzzing and initial phases of exploit development like root cause analysis. Courses/training videos on fuzzing, videos talking about fuzzing techniques, tools, and best practices. Conference talks and tutorials, blogs, tools that help in fuzzing applications, and fuzzers that help in fuzzing applications that use network-based protocols like HTTP, SSH, SMTP, etc. Search and pick the exploits, that have respective apps available for download, and reproduce the exploit by using the fuzzer of your choice. Set of tests for fuzzing engines. Includes different well-known bugs. A corpus, including various file formats for fuzzing multiple targets in the fuzzing literature.

Starting Price: Free

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Boofuzz

Boofuzz is a fork of and the successor to the venerable Sulley fuzzing framework. Besides numerous bug fixes, Boofuzz aims for extensibility. Like Sulley, Boofuzzincorporates all the critical elements of a fuzzer like easy and quick data generation, instrumentation and failure detection, target reset after failure, and recording of test data. Much easier install experience and support for arbitrary communications mediums. Built-in support for serial fuzzing, ethernet- and IP-layer, UDP broadcast. Better recording of test data, consistent, thorough, and clear. Test result CSV export and extensible instrumentation/failure detection. Boofuzz installs as a Python library used to build fuzzer scripts. It is strongly recommended to set up Boofuzz in a virtual environment.

Starting Price: Free

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Compare the Top Fuzz Testing Tools as of April 2025

What are Fuzz Testing Tools?

PortSwigger Burp Suite Professional

Peach Fuzzer

Etheno

Solidity Fuzzing Boilerplate

hevm

Tayt

ImmuneBytes

Google OSS-Fuzz

Fuzzing Project

LibFuzzer

american fuzzy lop

Honggfuzz

Ffuf

ToothPicker

afl-unicorn

Fuzzbuzz

Sulley

Radamsa

Jazzer

FuzzDB

Google ClusterFuzz

go-fuzz

Wfuzz

Fuzzapi

Wapiti

Echidna

syzkaller

Black Duck

Awesome Fuzzing

Boofuzz

Best Fuzz Testing Tools

Compare the Top Fuzz Testing Tools as of April 2025

What are Fuzz Testing Tools?

PortSwigger Burp Suite Professional

Peach Fuzzer

Etheno

Solidity Fuzzing Boilerplate

hevm

Tayt

ImmuneBytes

Google OSS-Fuzz

Fuzzing Project

LibFuzzer

american fuzzy lop

Honggfuzz

Ffuf

ToothPicker

afl-unicorn

Fuzzbuzz

Sulley

Radamsa

Jazzer

FuzzDB

Google ClusterFuzz

go-fuzz

Wfuzz

Fuzzapi

Wapiti

Echidna

syzkaller

Black Duck

Awesome Fuzzing

Boofuzz

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