Bonn, Germany — November 29, 2022 — Code Intelligence today announced its open-source Command-Line Interface (CLI) tool, CI Fuzz CLI, now allows Java developers to easily incorporate fuzz testing into their existing JUnit setup in order to find functional bugs and security vulnerabilities at scale. CI Fuzz CLI leverages genetic and evolutionary algorithms as well as automated instrumentation to dynamically generate millions of unusual inputs to test applications for unexpected behaviors that may lead to crashes, Denial of Service (DoS) or Zero-Day exploits. 

Fuzz testing, which can be seen as a complementary approach to unit testing, is gaining popularity in the open-source community. Google’s Open-Source-Security (OSS) team recently reported more than 40,500 bugs in 650 open source projects have been detected through fuzz testing. However, fuzz testing remains new to most developers outside the OSS and security community. A recent study among Go developers indicates that less than 12% of all participants use fuzz testing at work, citing a lack of understanding as well as challenges with implementation as key reasons for low adoption. 

Code Intelligence's new open-source tool aims to tackle these challenges by making fuzz testing accessible and usable for all developers directly from their command line or IDE. By introducing new fuzzing capabilities for Java, CI Fuzz CLI enables continuous application security testing directly in the CI/CD process. This is especially valuable to companies with cloud-based products and services who want to develop a mature DevSecOps pipeline.

“With the CI Fuzz CLI, Java developers can now improve the overall security and robustness of their applications with confidence and ease. It takes just three commands to set up and run a fuzz test. The tool comes with ready-to-use integrations for Maven, Gradle and Bazel. With a JUnit setup in place, developers can even run fuzz tests directly from their IDE.”, said Werner Krahe, Product Director at Code Intelligence. “If you’re completely new to fuzzing, I recommend starting with a simple test setup. Use your pre-existing unit tests as a template to run local fuzz tests on small libraries and utils. After a while, you could take it further and apply it to more complex testing setups. Ultimately, fuzz testing will provide the best results when running continuously in your CI/CD.”

“Code Intelligence helps developers ship secure software by providing the necessary integrations to test their code at each pull request, without ever having to leave their favorite environment. It’s like having an automated security expert always by your side,” said Thomas Dohmke, the CEO of GitHub.

Join the Livestream on December 8, 2022

As part of an ongoing effort to educate and support developers to ship secure code, Code Intelligence will broadcast a live stream on December 8, 2022, at 4 pm Central European Time (CET), on the topic of “Beyond Unit Testing: How to Uncover Blind Spots in Your Java Code with Fuzzing”. Save the date:
https://www.code-intelligence.com/webinar/beyond-unit-testing

About Code Intelligence

Founded in 2018 by Sergej Dechand, Khaled Yakdan, and Matthew Smith, Code Intelligence offers an automated software security platform that helps developers ship more secure code. The startup has raised $15.7 from Tola Capital, HTGF, Thomas Dohmke (CEO of GitHub), and others. Code Intelligence is trusted by Google, Deutsche Telekom, Bosch, and CARIAD, among others.

About CI Fuzz CLI

The CI Fuzz CLI is an easy-to-use fuzzing tool developed by Code Intelligence that allows developers to set up and run fuzz tests directly from the command line. The security tool supports Linux, macOS and Windows for multiple programming languages, build systems and testing frameworks such as JUnit. For more information on the CI Fuzz CLI, please visit: https://www.code-intelligence.com/cli-tool

About Fuzz Testing

Fuzz testing is a dynamic testing method for finding functional bugs and security issues in software. During a fuzz test, a program or function under test gets executed with invalid, unexpected, or random inputs to uncover unlikely or unexpected edge cases. Learn more: What is Fuzz Testing?

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