Several security tools have been described in recent times to assist security teams; however, the effectiveness and success remain limited to specific devices. Phishing is a type of cyberattack that uses fraudulent emails and websites to obtain personal information from unsuspecting users, such as passwords and credit card numbers. Hackers can gain access to your information through a variety of methods, and the most common of which are king, phishing, spear phishing, social engineering, and dictionary attacks. Each of these techniques is unique, but they all have the same goal: to obtain your personal information. Nevertheless, there is the potential to exploit this problem in terms of security. In this paper, we used the Bash Bunny (BB), a new tool designed to assist military, law enforcement, and penetration tester teams with their work to conduct exfiltration without privilege escalation through T1200, T1052, and T1052.001 techniques in air-gapped networks with effectiveness/success 99.706%.

The integration of artificial intelligence (AI) and the Internet of Things (IoT) in the power generation and distribution industry presents opportunities and challenges, particularly in the area of cybersecurity. Previous studies have explored the potential of AI to enhance cybersecurity in power systems, but limitations in terms of sample size and scope have hindered a comprehensive understanding of the current state of the field. To address this gap, this paper presents a systematic literature review of 30 papers that analyzes and categorizes relevant research based on their focus on threats, solutions, and future trends. The results indicate that 30 articles provide evidence supporting the use of AI and machine learning techniques to significantly enhance cybersecurity in the power sector. However, the study also highlights the need for continuous monitoring, threat intelligence, and risk management to stay ahead of evolving threats. Notably, this paper provides novel insights into the use of cybersecurity measures, blockchain technology, and awareness of the impact of AI in the power sector, with 90% of organizations using cybersecurity measures, 50% employing blockchain technology, 20% experiencing a cyberattack, and 60% being aware of the impact of AI. The study's limitations include a lack of detailed information on the organizations studied, such as their size and location, and the absence of a standardized approach to data collection across the selected papers. Nonetheless, this paper offers a valuable contribution to the field of AI and cybersecurity in the power industry by providing a comprehensive overview of the current state of research and identifying key areas for further investigation.

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