A3VS: Automated Authenticated AI-based Vulnerability Scanner for Ethical Security Auditing

Security failures can pose serious risks to organizations, including financial losses and damage to their reputation. This study presents a tool named Automated Authenticated AI-based Vulnerability Scanner (A3VS) built with different "Nmap script" enumerations in Python. This tool automates vulnerability detection, making the process much easier and more efficient. It offers a Graphical User Interface (GUI) and real-time network scanning mechanisms, significantly reducing manual effort for cybersecurity engineers and making it more adaptable and scalable. The existing tools available in the market cannot automate so many "Nmap script" enumerations and are limited to only three to four commands. On the other hand, the proposed tool can accommodate fifty-four different well-known commands of Nmap, and the outcome of the Nmap scripting is more robust and user-friendly. Moreover, to produce the result, we have executed the Nmap script over six different openly available vulnerable systems on the Web. By simplifying the technical complexities and authenticated automated processes, the proposed vulnerability scanner helps the organization to protect their systems and digital assets by strengthening security defense, risk control, and proactive cybersecurity measures. The only limitation of this tool is the execution time. Therefore, in the near future, we will plan to adopt high-performance computing or server-based parallelism to solve these issues.