Alternatives to Fuzzbuzz
Compare Fuzzbuzz alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Fuzzbuzz in 2026. Compare features, ratings, user reviews, pricing, and more from Fuzzbuzz competitors and alternatives in order to make an informed decision for your business.
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1
Global App Testing
Global App Testing
Global App Testing (GAT) enables tech teams to conduct testing across 189+ countries with a network of over 60,000 professional testers, using real devices and environments. By leveraging the GAT platform, you can streamline your testing process, boost release quality, and accelerate time-to-market while optimizing budget efficiency. The platform is fully integrated to seamlessly work with your existing DevOps or CI/CD tools. Whether you need ongoing QA support or additional resources to manage peak release cycles, GAT’s integration-driven approach allows you to manage your entire testing workflow—from test initiation to results analysis—without leaving your familiar tools like GitHub, Jira, and TestRail. With our integrated platform, both unscripted exploratory testing and scripted functional test execution can be embedded into your CI/CD and SDLC processes, ensuring perfect alignment with your automation testing tools. -
2
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 -
3
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 -
4
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. -
5
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 -
6
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 -
7
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 -
8
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 -
9
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 -
10
CI Fuzz
Code Intelligence
CI Fuzz ensures robust and secure code with test coverage up to 100%. Use CI Fuzz from the command line or in the IDE of choice to generate thousands of test cases automatically. CI Fuzz analyzes code as it runs, just like a unit test, but with AI support to efficiently cover all paths through the code. Uncover real bugs in real-time and say goodbye to theoretical issues and false positives. Find real issues with all the information needed to quickly reproduce and fix them. Test your code with maximum code coverage and automatically detect typical security-relevant bugs like injections and remote code executions automatically in one go. Get fully covered to deliver the highest quality software. Conduct real-time code analysis with CI Fuzz. Take unit tests to the next level. It employs AI for comprehensive code path coverage and the automatic generation of thousands of test cases. Maximize pipeline performance that doesn't compromise software integrity.Starting Price: €30 per month -
11
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 -
12
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 -
13
BFuzz
RootUp
BFuzz is an input-based fuzzer tool that takes HTML as an input, opens up your browser with a new instance, and passes multiple test cases generated by domato which is present in the recurve folder of BFuzz, more over BFuzz is an automation that performs the same task repeatedly and it doesn't mangle any test cases. Running BFuzz will ask for the option of whether to fuzz Chrome or Firefox, however, this will open Firefox from recurve and create the logs on the terminal. BFuzz is a small script that enables you to open the browser and run test cases. The test cases in recurve are generated by the domato generator and contain the main script. It contains additional helper code for DOM fuzzing.Starting Price: Free -
14
Mayhem
ForAllSecure
Advanced fuzzing solution that combines guided fuzzing with symbolic execution, a patented technology from CMU. Mayhem is an advanced fuzz testing solution that dramatically reduces manual testing efforts with autonomous defect detection and validation. Deliver safe, secure, reliable software with less time, cost, and effort. Mayhem’s unique advantage is in its ability to acquire intelligence of its targets over time. As Mayhem’s knowledge grows, it deepens its analysis and maximizes its code coverage. All reported vulnerabilities are exploitable, confirmed risks. Mayhem guides remediation efforts with in-depth system level information, such as backtraces, memory logs, and register state, expediting issue diagnosis and fixes. Mayhem utilizes target feedback to custom generate test cases on the fly -- meaning no manual test case generation required. Mayhem offers access to all of its test cases to make regression testing effortless and continuous. -
15
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 -
16
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 -
17
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 -
18
APIFuzzer
PyPI
APIFuzzer reads your API description and step-by-step fuzzes the fields to validate if your application can cope with the fuzzed parameters, and it does not require coding. Parse API definition from a local file or remote URL. JSON and YAML file format support. All HTTP methods are supported. Fuzzing of the request body, query string, path parameter, and request header is supported. Relies on random mutations and supports CI integration. Generate JUnit XML test report format. Send a request to an alternative URL. Support HTTP basic auth from the configuration. Save the report of the failed test in JSON format into the pre-configured folder.Starting Price: Free -
19
OWASP WSFuzzer
OWASP
Fuzz testing or fuzzing is a software testing technique, that basically consists in finding implementation bugs using malformed/semi-malformed data injection in an automated fashion. Let’s consider an integer in a program, which stores the result of a user’s choice between 3 questions. When the user picks one, the choice will be 0, 1, or 2, which makes three practical cases. Integers are stored as a static size variable. If the default switch case hasn’t been implemented securely, the program may crash and lead to “classical” security issues. Fuzzing is the art of automatic bug finding, and its role is to find software implementation faults and identify them if possible. A fuzzer is a program that automatically injects semi-random data into a program/stack and detects bugs. The data-generation part is made of generators, and vulnerability identification relies on debugging tools. Generators usually use combinations of static fuzzing vectors. -
20
Code Intelligence
Code Intelligence
Our platform uses various security techniques, including coverage-guided and feedback-based fuzz testing, to automatically generate millions of test cases that trigger hard-to-find bugs deep within your application. This white-box approach protects against edge cases and speeds up development. Advanced fuzzing engines generate inputs that maximize code coverage. Powerful bug detectors check for errors during code execution. Uncover true vulnerabilities only. Get the input and stack trace as proof, so you can reliably reproduce errors every time. AI white-box testing uses data from all previous test runs to continuously learn the inner-workings of your application, triggering security-critical bugs with increasingly high precision. -
21
Boofuzz
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 -
22
Atheris
Google
Atheris is a coverage-guided Python fuzzing engine. It supports fuzzing of Python code, but also native extensions written for CPython. Atheris is based on libFuzzer. When fuzzing native code, Atheris can be used to catch extra bugs. Atheris supports Linux (32- and 64-bit) and Mac OS X, with Python versions 3.6-3.10. It comes with a built-in libFuzzer, which is fine for fuzzing Python code. If you plan to fuzz native extensions, you may need to build from source to ensure the libFuzzer version in Atheris matches your Clang version. Atheris relies on libFuzzer, which is distributed with Clang. Apple Clang doesn't come with libFuzzer, so you'll need to install a new version of LLVM. Atheris is based on a coverage-guided mutation-based fuzzer (LibFuzzer). This has the advantage of not requiring any grammar definition for generating inputs, making its setup easier. The disadvantage is that it will be harder for the fuzzer to generate inputs for code that parses complex data types.Starting Price: Free -
23
FuzzDB
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 -
24
BlackArch Fuzzer
BlackArch
BlackArch is a Linux pentesting distribution based on ArchLinux. BlackArch Fuzzer provides packages that use the fuzz testing principle. -
25
Defensics Fuzz Testing
Black Duck
Defensics Fuzz Testing is a comprehensive, versatile, automated black box fuzzer that enables organizations to efficiently and effectively discover and remediate security weaknesses in software. The generational fuzzer takes an intelligent, targeted approach to negative testing. Advanced file and protocol template fuzzers enable users to build their own test cases. The SDK allows expert users to use the Defensics framework to develop their own test cases. Defensics is a black box fuzzer, meaning it doesn’t require source code to run. With Defensics, users can secure their cyber supply chain to ensure the interoperability, robustness, quality, and security of software and devices before introducing them into IT or lab environments. Defensics fits nearly any development workflow, whether in a traditional SDL or CI environment. Its API and data export capabilities also enable it to integrate with surrounding technologies, making it a true plug-and-play fuzzer. -
26
Fuzzing Project
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 -
27
beSTORM
Beyond Security (Fortra)
Discover code weaknesses and certify the security strength of any product without access to source code. Test any protocol or hardware with beSTORM, even those used in IoT, process control, CANbus compatible automotive and aerospace. Realtime fuzzing, doesn’t need access to the source code, no cases to download. One platform, one GUI to learn, with over 250+ prebuilt protocol testing modules and the ability to add custom and proprietary ones. Find the security weaknesses before deployment that are most often discovered by external actors after release. Certify vendor components and your own applications in your own testing center. Self-learning software module and propriety software testing. Customization and scalability for any business sizes up or down. Automatically generate and deliver near-infinite attack vectors and document any product failures. Record every pass/fail and hand engineering the exact command that produced each fail.Starting Price: $50,000.00/one-time -
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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 -
29
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 -
30
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 -
31
API Fuzzer
Fuzzapi
API Fuzzer allows to fuzz-request attributes using common pentesting techniques and lists vulnerabilities. API Fuzzer gem accepts an API request as input and returns vulnerabilities possible in the API. Cross-site scripting vulnerability, SQL injection, blind SQL injection, XML external entity vulnerability, IDOR, API rate limiting, open redirect vulnerabilities, information disclosure flaws, info leakage through headers, and cross-site request forgery vulnerability.Starting Price: Free -
32
LLMFuzzer
LLMFuzzer
If you're a security enthusiast, a pentester, or a cybersec researcher who loves to find and exploit vulnerabilities in AI systems, LLMFuzzer is the perfect tool for you. It's built to make your testing process streamlined and efficient. We are working on full documentation. It will cover detailed information about the architecture, different fuzzing strategies, examples, and how to extend the tool.Starting Price: Free -
33
CodeMender
Google DeepMind
CodeMender is an AI-powered agent developed by DeepMind for automatically finding, diagnosing, and patching security vulnerabilities in software code. It combines advanced reasoning abilities (via Gemini Deep Think models) with program analysis tools, static analysis, dynamic analysis, differential testing, fuzzing, and SMT solvers, to identify root causes of flaws, generate high-quality fixes, and validate them to avoid regressions or functional breakage. CodeMender operates by proposing patches that adhere to style rules and structural correctness, and then uses critique and verification agents to check changes and self-correct if issues arise. It can also proactively rewrite existing code using safer APIs or data structures (for example, applying -fbounds-safety annotations to prevent buffer overflows). To date, CodeMender has upstreamed dozens of patches in large open source projects (including ones with millions of lines of code). -
34
Grammatech Proteus
Grammatech
Proteus is an advanced software testing system for automatically finding and fixing vulnerabilities, with no false alarms, aimed at development groups, testing organizations, and cybersecurity teams. It discovers vulnerabilities that could be triggered by potentially malicious files or network inputs, including many common entries in the Common Weakness Enumeration (CWE). The tool supports Windows and Linux native binaries. By integrating and simplifying the use of state-of-the-art tools for binary analysis and transformation, Proteus lowers the costs and increases the efficiency and effectiveness of software testing, reverse engineering, and maintenance. Binary analysis, mutational fuzzing, and symbolic execution without the need for source code, and a professional-grade user interface for result aggregation and presentation. Advanced exploitability reporting and reasoning capability, and deployment in a virtualized environment or on a host system.Starting Price: Free -
35
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 -
36
Wfuzz
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 -
37
WebReaver
Websecurify
WebReaver is an elegant, easy to use and fully-automated, web application security security testing tool for Mac, Windows and Linux, suitable for novice as well as advanced users. WebReaver allows you easily test any web application for a large variety of web vulnerabilities from the sever kinds such as SQL Injection, local and remote file Includes, command Injection, cross-site scripting and expression Injection to the less severe ones such as variety of session and headers problems, information leakage and many more. Automated security testing technologies, such as those, which rely on scanning, fuzzing, sending arbitrary malicious data to detect security defects, can seriously damage the web applications they are used against. Therefore, it is often recommended to perform automated tests only against systems in demo, testing or pre-production environments. -
38
Diffblue Cover
Diffblue
Diffblue Cover analyzes your existing Java program and writes unit regression tests that reflect the current behavior of the code. The CLI tool works 100% autonomously, configuring itself from your Maven or Gradle environment. By bringing automation to the test-writing process, the CLI tool provides a speed boost for organizations that are working towards achieving DevOps goals like CI/CD. Since it fits into a CI pipeline, the CLI tool protects the whole codebase from regressions by shifting testing left. Diffblue Cover's unit regression tests run fast and verify new code changes immediately, helping users detect undesirable changes in the code’s behavior as early as possible, when they're the quickest, easiest, and cheapest to fix. And tests are automatically maintained, saving teams even more time.Starting Price: Free -
39
QualGent
QualGent
QualGent is an AI-powered mobile app quality assurance platform that automates end-to-end testing for iOS and Android applications by using intelligent agents that mimic human testers and run continuously rather than relying on fragile scripted tests or manual QA, helping development teams catch bugs, improve release confidence, and ship faster without expanding QA headcount. Its AI automatically generates comprehensive test plans by linking to your code repo, PRDs, Figma designs, or by accepting plain-English descriptions of what to test, then executes those tests 24/7 on real devices and emulators in parallel with video, logs, and detailed reports, including multi-lingual and cross-platform coverage, while handling dynamic UI changes with self-healing capabilities that reduce maintenance overhead. QualGent integrates into CI/CD pipelines and issue trackers like GitHub, Slack, and Linear, enabling tests to run on every commit and deliver actionable output quickly. -
40
FlowCoder
Omnipacket
FlowCoder is a WYSIWYG programming framework for prototyping, debugging, validation, fuzzing as well as functional, load, and security testing of computer networks. It allows building packets for a variety of network protocols, sending them on the wire, receiving and analyzing incoming network traffic, matching requests with replies, keeping and changing the state and much more. Local execution is the simplest case. All packets sent by FlowCoder originate on a local host. Packets coming back in response are processed there as well. Only FlowCoder IDE components run locally. A flowchart, once created, is shipped for execution to a cloud running multiple instances of the flowchart processor engine. Packets are originated and processed in a cloud. The local user gets back diagnostics and statistical data. Playing MITM in a cloud. Flowchart sees the packets passing between a pair of network end-points, and could modify them at any stack layer. -
41
Loadsy
Loadsy
Run Performance Tests for Digital Products/Services in Minutes Avoid Steep Learning Curve… Design, Run, Save and Automate your Tests with JavaScript Code. • Design threads as complex as you need, simulate diverse and real scenarios simultaneously for your tests with JavaScript code. • Create and run any kind of performance tests with just one tool. • Tests for any platform no matter where it’s hosted, in the cloud, or an on-premise server. • Test continuously with CI/CD integrated tools, automate performance tests. • Get data in real-time, catch and solve blind spots before a user does. • Get a realistic simulation with virtual browsers and simulate hundreds of thousands of users.Starting Price: $0.05/hour/user -
42
Appsurify TestBrain
Appsurify
Appsurify’s patented AI technology determines the areas of an application that have changed after each developer commit and automatically selects and executes just the tests relevant to those changed areas in the CI Pipeline. Appsurify selects and executes only the small subset of tests impacted on a per developer change basis. Optimize CI Pipelines by removing automation testing as a bottleneck and let Builds run faster and more efficiently. Automation Testing and CI Pipelines are slowing productivity by taking too long to complete, delaying important feedback to catch bugs, and pushing release schedules back. With Appsurify, QA & DevOps work is streamlined by allowing focused test execution in only the areas that matter to catch bugs early and keep CI/CD pipelines running smoothly and efficiently. -
43
API Swan
API Swan
Elevate your development process with our robust API solution, and ensure stability, performance, and reliability in every release. Seamless Integration with CI/CD, forging a cohesive development pipeline. API Swan is driven by the mission to forge a software testing platform that stands as the pinnacle of affordability and reliability, designed expressly for engineering teams navigating the early-growth stage startup terrain. Ship products at 10x velocity, and catch more bugs, effortlessly. 24/7 application monitoring for uninterrupted performance. Auto-generates regression tests from network traffic. Cutting-edge automated test case design, seamlessly entwined within your workflow. Effortless automatic documentation of APIs and schemas, saving precious time.Starting Price: $89 per month -
44
BreakingPoint
Keysight Technologies
Enter BreakingPoint. By simulating real-world legitimate traffic, distributed denial of service (DDoS), exploits, malware, and fuzzing, BreakingPoint validates an organization’s security infrastructure, reduces the risk of network degradation by almost 80%, and increases attack readiness by nearly 70%. And with our new TrafficREWIND solution, you'll get even more realistic and high-fidelity validation by adding production network insight into BreakingPoint test traffic configurations. BreakingPoint addresses that by simulating both good and bad traffic to validate and optimize networks under the most realistic conditions. Security infrastructures can also be verified at high-scale, ensuring ease of use, greater agility, and speedy network testing. BreakingPoint validates an organization’s security infrastructure, reduces the risk of network degradation by almost 80%, and increases attack readiness by nearly 70%. -
45
Amikoo
MuukLabs Inc.
Amikoo is an AI-powered QA agent toolkit designed to help engineering teams keep pace with AI-accelerated development. Instead of relying on brittle scripts or generic automation, Amikoo learns how your product works—exploring user flows, identifying test coverage gaps, and generating executable Playwright tests that reflect real usage. When code changes, Amikoo detects broken tests and automatically repairs or rebuilds them, keeping your test suite aligned without manual effort. By connecting to tools like GitHub, CI/CD pipelines, and product analytics, it builds the context needed to make accurate testing decisions and reduce false positives. The result is faster releases, more reliable coverage, and a QA process that scales with your team. Built on real-world QA learnings from MuukTest, Amikoo brings together intelligent automation and practical testing expertise in one continuous workflow.Starting Price: $999 per month -
46
Keysight Eggplant
Keysight Technologies
Keysight Eggplant is an AI-powered software testing platform that helps teams automate functional, regression, and performance testing across any system or platform. Built to eliminate repetitive manual testing, it ensures faster releases, broader coverage, and higher-quality applications. With capabilities spanning UI, performance, and mobile app testing, Eggplant allows organizations to validate real user experiences using computer vision and OCR-based automation. It seamlessly integrates into CI/CD pipelines like Jenkins, Azure DevOps, and GitHub for continuous testing at every code check-in. Supporting technologies from legacy GUIs to cloud-native apps, it delivers consistent reliability across complex environments. Trusted by global enterprises and organizations such as NASA, JetBlue, and the US Army, Keysight Eggplant enables smarter testing and better software outcomes. -
47
Devzery
Devzery Technologies
Devzery is an AI-powered platform that revolutionizes API regression testing with codeless automation and seamless CI/CD integration. It enables teams to create, execute, and manage tests effortlessly, reducing manual effort while maximizing coverage. With support for multiple programming languages, Devzery caters to diverse environments, offering intelligent change detection, automated test case updates, and detailed reporting. It ensures comprehensive API validation, including performance and security testing, helping teams deliver robust, high-quality software faster. Perfect for startups and enterprises, Devzery streamlines QA, minimizes risks, and accelerates development timelines.Starting Price: $25 -
48
Kraken CI
Michal Nowikowski
Modern CI/CD, open-source, on-premise system that is highly scalable and focused on testing. Features: - flexible workflow planning using Starlark/Python - distributed building and testing - various executors: bare metal, Docker, LXD - highly scalable to thousands of executors - sophisticated test results analysis - integrated with AWS EC2 and ECS, Azure VM, with autoscaling - supported webhooks from GitHub, GitLab and Gitea - email and Slack notificationsStarting Price: free -
49
Autify
Autify
Autify is an AI-powered test automation platform that helps software teams accelerate testing, reduce manual effort, and enhance software quality. Designed for QA engineers, developers, and test automation teams, Autify provides no-code and low-code automation for web and mobile applications. Its AI-driven features simplify test creation and automatically maintain tests, minimizing test maintenance. Autify enables cross-browser and cross-device testing, ensuring robust application performance across multiple environments. Integrated seamlessly into CI/CD pipelines, Autify supports agile workflows and scalability through cloud execution, helping teams deliver faster, more reliable software releases. -
50
BitBar
SmartBear
The most flexible cloud-based mobile app testing solution. Use any framework to run manual or automated tests on thousands of real devices. With unlimited users and unlimited concurrency, adapting seamlessly to your existing CI/CD processes and tools. The way we build, test and deliver software has fundamentally changed. Continuous Testing and Continuous Delivery are a challenge for most software developers. Today’s developer teams must be agile, flexible, and efficient to deliver better software experiences to customers as fast as possible. Use your existing processes, IDEs, CI/CD tools, and frameworks. Switch them whenever you want to any tool or framework in the market. Unlimited users and unlimited concurrency on thousands of real devices and browsers. Scale up or down as you need. Native support for any DevOps environment: Jenkins, Gradle, JIRA, Slack, TeamCity, Travis. Or use our powerful REST API to integrate with your favorite tools or services.Starting Price: $39 per month
