A novel AI-assisted research system, HTTP Terminator, has successfully identified new HTTP desynchronization techniques by analyzing 30,000 candidate desync vectors. This breakthrough was achieved through the system's ability to generate and test various desync scenarios, ultimately proving the effectiveness of these techniques. Additionally, a human-guided discovery process uncovered a previously unknown zero-day vulnerability in Apache Traffic Server. The zero-day vulnerability poses a significant risk, as it can be exploited by attackers to compromise affected systems. The discovery of these new techniques and the zero-day vulnerability highlights the importance of continuous monitoring and patching of web servers to prevent potential attacks. The fact that HTTP Terminator was able to identify these vulnerabilities using AI-assisted techniques1 demonstrates the potential of artificial intelligence in enhancing web security. This matters to security practitioners because the window for patching vulnerabilities is rapidly shrinking, making it essential to assess exposure immediately.