Intell-dragonfly: A Cybersecurity Attack Surface Generation Engine Based On Artificial Intelligence-generated Content Technology

TL;DR

Intell-dragonfly leverages AI-generated content technology, specifically ChatGPT, to automatically generate diverse, personalized attack surfaces, enhancing cybersecurity threat simulation and defense strategies.

Contribution

This paper introduces a novel AI-based attack surface generation engine that improves authenticity, diversity, and applicability over traditional methods.

Findings

Enhanced accuracy in attack surface generation

Greater diversity and personalization of attack scenarios

Improved applicability in real network environments

Abstract

With the rapid development of the Internet, cyber security issues have become increasingly prominent. Traditional cyber security defense methods are limited in the face of ever-changing threats, so it is critical to seek innovative attack surface generation methods. This study proposes Intell-dragonfly, a cyber security attack surface generation engine based on artificial intelligence generation technology, to meet the challenges of cyber security. Based on ChatGPT technology, this paper designs an automated attack surface generation process, which can generate diversified and personalized attack scenarios, targets, elements and schemes. Through experiments in a real network environment, the effect of the engine is verified and compared with traditional methods, which improves the authenticity and applicability of the attack surface. The experimental results show that the ChatGPT-based method has significant advantages in the accuracy, diversity and operability of attack surface generation. Furthermore, we explore the strengths and limitations of the engine and discuss its potential applications in the field of cyber security. This research provides a novel approach to the field of cyber security that is expected to have a positive impact on defense and prevention of cyberthreats.