Using advanced language models to enhance cybersecurity education

The Network and Systems Engineering Cyber Security research group is developing an innovative tool to improve student training in reverse engineering and software exploitation. Using advanced language models, the system can automatically generate realistic and unique binary exploitation challenges. This ensures that each student consistently receives a new, tailored, and relevant task.

Background

Understanding offensive cybersecurity techniques is essential for building secure software. To develop these skills, students work with intentionally vulnerable programs to discover and exploit security flaws. However, these challenges are often quickly solved and shared publicly, reducing their effectiveness as a learning tool. The solution? An intelligent system that automatically generates a unique challenge for each student, based on predefined learning objectives. This keeps education current, fair, and engaging—and prevents students from relying on existing solutions.

Objective

The goal of this project is to develop a functional system that can automatically create new binary exploitation challenges for educational use. By leveraging AI technology, assignments can be customized for each individual student—without requiring instructors to manually design new versions. This leads to more efficient teaching and a better learning experience. The project introduces a tool that automates the creation of educational materials.

Want to know more?

Get in touch with Mike Gilhespy: Researcher Network and Systems Engineering Cyber Security, [email protected]