Compare the Top Fuzz Testing Tools that integrate with Docker as of July 2025

This a list of Fuzz Testing tools that integrate with Docker. Use the filters on the left to add additional filters for products that have integrations with Docker. View the products that work with Docker in the table below.

What are Fuzz Testing Tools for Docker?

Fuzz testing tools are automated software tools used to detect bugs and vulnerabilities in computer systems. They generate large amounts of random input data to test the robustness of a system. These tools are commonly used in software development to enhance the quality and security of a product. Fuzz testing tools can be applied to various types of systems, including web applications, mobile apps, and operating systems. They have become an essential part of the testing process in modern software development due to their ability to uncover hidden flaws that traditional testing methods may miss. Compare and read user reviews of the best Fuzz Testing tools for Docker currently available using the table below. This list is updated regularly.

  • 1
    Etheno

    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
  • 2
    Ffuf

    Ffuf

    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
  • 3
    Jazzer

    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
  • 4
    Wfuzz

    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
  • 5
    Echidna

    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
  • 6
    Mayhem Code Security
    Thousands of autonomously generated tests run every minute to pinpoint vulnerabilities and guide rapid remediation. Mayhem takes the guesswork out of untested code by autonomously generating test suites that produce actionable results. No need to recompile the code, since Mayhem works with dockerized images. Self-learning ML continually runs thousands of tests per second probing for crashes and defects, so developers can focus on features. Continuous testing runs in the background to surface new defects and increase code coverage. Mayhem delivers a copy/paste reproduction and backtrace for every defect, then prioritizes them based on your risk. See all the results, duplicated and prioritized by what you need to fix now. Mayhem fits into your existing build pipeline and development tools, putting actionable results at your developers' fingertips. No matter what language or tools your team uses.
  • 7
    Mayhem

    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.
  • 8
    Code Intelligence

    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.
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