Design and Implementation of an AI-Based Vulnerability Management Dashboard for Cybersecurity Operations

Abstract

The rapid growth of digital infrastructure and web-based applications has significantly increased the exposure of organizations to cybersecurity threats and vulnerabilities. Traditional vulnerability management systems often struggle to efficiently handle large volumes of security data, prioritize risks accurately, and provide actionable insights for remediation. This paper presents the design and implementation of an AI-driven Vulnerability Management Dashboard aimed at enhancing the efficiency, accuracy, and usability of vulnerability analysis in modern enterprise environments. The proposed system integrates standardized vulnerability assessment techniques, particularly the Common Vulnerability Scoring System (CVSS), with intelligent data processing and context-aware filtering mechanisms to enable effective vulnerability prioritization. The dashboard provides real-time visibility into vulnerabilities through an intuitive interface supporting tracking, severity visualization, AI-assisted search, role-based access control, and task assignment workflows. The system is developed using React, Tailwind CSS, Flask, and SQLAlchemy, ensuring scalability, modularity, and secure API communication.