When ChatGPT goes rogue: exploring the potential cybersecurity threats of AI-powered conversational chatbots

ChatGPT has garnered significant interest since its release in November 2022 and it has showcased a strong versatility in terms of potential applications across various industries and domains. Defensive cybersecurity is a particular area where ChatGPT has demonstrated considerable potential thanks to its ability to provide customized cybersecurity awareness training and its capability to assess security vulnerabilities and provide concrete recommendations to remediate them. However, the offensive use of ChatGPT (and AI-powered conversational agents, in general) remains an underexplored research topic. This preliminary study aims to shed light on the potential weaponization of ChatGPT to facilitate and initiate cyberattacks. We briefly review the defensive usage of ChatGPT in cybersecurity, then, through practical examples and use-case scenarios, we illustrate the potential misuse of ChatGPT to launch hacking and cybercrime activities. We discuss the practical implications of our study and provide some recommendations for future research

AI based Login System using Facial Recognition

With rapid growth in the application of AI, Access Control Systems are walking in a new technology lane. Powered by deep learning technologies or cognitive analytics, login pages can implement more secure, efficient, and easy to use authentication systems. Face Detection and Recognition is emerging as preferred solution to enable secure verification and authentication in login systems. Moreover, Facial Recognition has been applied in many fields from unlocking smartphones through built in camera of smartphones to identification of suspected people by the law enforcement organizations. The goal of this research paper is to provide an easier authentication system using Face Detection and Recognition instead of using usernames and passwords. This paper mainly analyzes the application of Face detection systems to authenticate and login users It presents the prototype system implemented with the usage of a Flask server, requesting face recognition services from Amazon\u27s Rekognition. The prototype receives images of the user instead of his username and password. The received image is analyzed by AWS\u27s Face recognition tools and the ID of the face is sent as a response along with the confidence level of the algorithm used to analyze the face. The prototype is tested with eight different faces and the system authenticate users with 100% accuracy and navigate them to their respective feeds