Colloquium lecture: 25 June 2025, Yunlei Fu (Tutor: Al Sardy)
HyFuzz: A Hybrid AI-Enhanced Vulnerability Detection Framework
In today’s highly interconnected world, network security is of paramount importance, yet identifying vulnerabilities in systems remains a significant challenge. HTTP (Hypertext Transfer Protocol), the foundation of web communication, is a common target for attackers due to its widespread use and inherent security weaknesses. These vulnerabilities include susceptibility to injection attacks (e.g., SQL injection), cross-site scripting (XSS), and cross-site request forgery (CSRF). Traditional detection methods often fail to address these challenges comprehensively due to their reliance on static rules or limited adaptability. This project proposes an innovative vulnerability detection system specifically targeting HTTP services. By integrating rapid port scanning, detailed service detection, historical vulnerability lookup via the CVE database, and AI-optimised fuzz testing, the system aims to enhance the security analysis of HTTP.
Place: Room 04.137, Martensstr. 3, Erlangen
or
Zoom-Meeting:
https://fau.zoom-x.de/j/68350702053?pwd=UkF3aXY0QUdjeSsyR0tyRWtLQ0hYUT09
Meeting-ID: 683 5070 2053
Kenncode: 647333