Utilizing AI for Automated Vulnerability Assessment and Patch Management

Abstract

With the increasing complexity and volume of cyber threats, organizations are continually challenged to maintain the security of their digital assets. Vulnerability assessment and patch management are critical components of any robust cybersecurity strategy, yet traditional approaches often struggle to keep pace with the evolving threat landscape. This article explores the potential of Artificial Intelligence (AI) in revolutionizing these processes through automation, efficiency, and precision. AI-based systems offer a paradigm shift in vulnerability assessment by enabling rapid identification, prioritization, and remediation of vulnerabilities across diverse IT environments. By leveraging machine learning algorithms, these systems can analyze vast amounts of data, including historical attack patterns, system configurations, and threat intelligence feeds, to accurately assess the risk posed by vulnerabilities. Furthermore, AI can provide predictive capabilities, forecasting potential vulnerabilities based on emerging trends and vulnerabilities in similar systems