In 2025, fuzz testing has become an essential practice for ensuring software security and reliability. By identifying vulnerabilities through randomized input testing, fuzzing helps development teams uncover bugs that traditional testing methods—such as static analysis and penetration testing—often miss. With rapid advancements in security tools, let’s explore the top fuzz testing tools of 2025, their key features, benefits, and how they compare.

We’re thrilled to announce the general availability of Spark, an AI Test Agent that lowers the entry barrier to white-box fuzz testing. In this blog, we explain how Spark works and share the main results from its beta testing that prove its effectiveness.

At the 6th de:hub Pitch Night, an event celebrating innovation and digital transformation, Code Intelligence was honored with the prestigious German AI Award. This recognition, awarded by a distinguished jury of industry experts and investors, underscores Code Intelligence’s pivotal role in advancing software security through artificial intelligence.

Fuzz testing is most commonly classified based on its analysis approach. The two main categories of fuzz testing solutions are white-box and black-box fuzzers. In this blog, we explain the difference between approaches as well as their main features.

We are super excited to announce the discovery of a heap-based use-after-free vulnerability in wolfSSL, identified through a fuzz test automatically generated by an AI Test Agent. This marks another milestone in advancing automated security testing and demonstrates the power of AI-driven tools to improve software reliability and safety.