Abstract

The pervasive nature of Wi-Fi networks in both individual and organizational spheres has brought forth unparalleled convenience alongside significant cybersecurity challenges. This paper presents a systematic literature review (SLR) evaluating the contemporary landscape of Wi-Fi penetration testing, with a particular focus on cracking methodologies targeting Wi-Fi Protected Access 2 (WPA2) and Wi-Fi Protected Access 3 (WPA3) protocols. Employing an SLR approach, we synthesized findings from a comprehensive array of academic sources to identify common vulnerabilities, analyze prevalent attack vectors, and assess the efficacy of tools such as Aircrack-ng, Wireshark, and Airgeddon. Our investigation reveals that despite WPA3's advancements, including Simultaneous Authentication of Equals (SAE) and Protected Management Frames (PMF), certain vulnerabilities persist, notably through downgrade attacks, side-channel exploits, and sophisticated social engineering tactics leveraging captive portals. The findings underscore the critical need for continuous security assessments, robust mitigation strategies, and enhanced user awareness to fortify Wi-Fi network defenses against evolving threats. Future research directions are discussed, advocating for the integration of machine learning and deep reinforcement learning to automate and refine penetration testing processes, thereby improving detection accuracy and reducing response times.