AI for Penetration Testing: Enhancing Cybersecurity Through Intelligent Automation

Abstract

Penetration testing is a critical component of cybersecurity, aimed at identifying vulnerabilities in systems before malicious actors can exploit them. Traditional penetration testing methods are often time-consuming, labor-intensive, and limited by human expertise. This paper explores the application of Artificial Intelligence (AI) in penetration testing, highlighting its potential to automate vulnerability detection, optimize attack simulations, and improve overall efficiency. Through case studies and examples, we demonstrate how AI-driven tools can enhance the accuracy and scalability of penetration testing. The paper concludes with a discussion of challenges and future directions for AI in this domain.