Sergej Dechand, Code Intelligence's CEO, demonstrates how developers can submit new code, which is automatically tested and analyzed for security issues. Sergej explains the process of running tests, assessing findings, and integrating with ticketing systems. You'll also see how to measure code coverage and download reports. It includes all the mentioned use cases with simulating hardware and autogenerated fuzz test setup..

CARIAD has been building one unified software platform for all Volkswagen brands to provide them with reliable software and digital best practices. In recent years, CARIAD and the rest of the automotive software sector faced extensive industry regulation and an array of dangerous and costly vulnerabilities. By introducing feedback-based fuzzing, an advanced white-box testing method that uses self-learning AI to uncover deeply hidden bugs and security vulnerabilities, CARIAD was able to find and fix potentially dangerous issues early in the development process.

The manual effort required to set up dynamic testing methods such as feedback-based fuzzing, presents a major barrier to adoption to many dev teams. CI Spark obliterates this barrier by automating the most labor-intensive parts of AI-powered white-box testing, which is identifying relevant entry points (e.g., an API that handles user data) and developing tests that are tailored to their structure.

In today's fast-paced software environment, third-party code has become irreplaceable. With 96% of codebases containing open-source dependencies, the image is clear: open-source is ubiquitous in the development landscape.

In this webinar excerpt, our colleague Peter Samarin demonstrates how our prototype pollution bug detectors were able to uncover a highly severe CVE in the popular JavaScript library protobufjs. This finding puts affected applications at risk of remote code execution and denial of service attacks.

Our colleagues Peter Samarin, Norbert Schneider and Fabian Meumertzheim recently built a new bug detector enabling our JavaScript fuzzing engine Jazzer.js to identify Prototype Pollution. This work is now bearing its first fruits: As part of our ongoing collaboration with Google’s OSS-Fuzz, Jazzer.js recently uncovered a new Prototype Pollution vulnerability in protobuf.js (CVE-2023-36665). This finding puts affected applications at risk of remote code execution and denial of service attacks.

Learn how AI.powered white-box testing leverages the internal design of the software under test to bugs and vulnerabilities that are off-limits to traditional testing methods.

Join us for a weekly chat about all things fuzzing, live demos, Q&A's, and more.

Building secure and reliable APIs is an essential and challenging endeavor. Traditional API testing approaches perform blackbox testing and test the application through the network. This is both slow and lacks deep insights into how the tested application handles API requests. Also, it happens late in the software development lifecycle as it requires a complete application deployment.

Join us for a weekly chat about all things fuzzing, live demos, Q&A's, and more.