Best Fuzz Testing Tools for Jira
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Compare the Top Fuzz Testing Tools that integrate with Jira as of June 2025
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This a list of Fuzz Testing tools that integrate with Jira. Use the filters on the left to add additional filters for products that have integrations with Jira. View the products that work with Jira in the table below.
What are Fuzz Testing Tools for Jira?
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 Jira currently available using the table below. This list is updated regularly.
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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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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. -
3
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.
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