GPT-5.5-Cyber built a zlib fuzzing lab in a day
Trail of Bits used the AI assistant GPT-5.5-Cyber to set up a complete zlib fuzzing lab, including toolchains, harnesses, and infrastructure, in a single day. The experiment demonstrated how large language models can significantly accelerate security research workflows by handling routine development tasks.
Background
- Trail of Bits is a respected cybersecurity research and consulting firm known for open-source security tools and deep technical audits.
- "Fuzzing" is an automated software testing technique that feeds random or malformed data to a program to find crashes, vulnerabilities, or unexpected behavior.
- The article title describes a scenario where GPT-5.5-Cyber (presumably an advanced, cybersecurity-specialized AI model) set up a fuzzing lab for zlib (a widely used data compression library) in a single day — a task that would traditionally require significant human effort and specialized expertise.
- zlib is a core, ubiquitous open-source compression library, meaning vulnerabilities in it affect countless systems and applications.
- This exemplifies the growing trend of AI agents autonomously performing complex cybersecurity research and tooling tasks, raising both efficiency promises and new risks.