Network Security Scanner Using Cybersecurity

Abstract

Network security has become a paramount concern as organizations increasingly depend on interconnected systems for critical operations. Existing approaches to network security assessment are fragmented, relying on multiple standalone tools that operate independently, resulting in inefficient workflows, delayed threat detection, and incomplete vulnerability coverage. This paper presents the design and implementation of a comprehensive, integrated Network Security Scanner that unifies multiple security analysis modules into a single automated platform. The proposed system incorporates host discovery, port scanning, vulnerability detection using CVE databases, SSL/TLS auditing, DNS enumeration, HTTP security analysis, behavioral anomaly detection, authenticated credential scanning, network segmentation verification, and compliance checking against PCI-DSS, NIST, and ISO 27001 standards. A Flask-based web interface with Server-Sent Events (SSE) enables real-time monitoring during scan execution. A risk scoring engine prioritizes vulnerabilities by severity, while a multi-format report generator produces outputs in JSON, HTML, SIEM (CEF), Snort IDS rules, and Ansible playbooks for automated remediation. Experimental evaluation conducted on a controlled test network of ten hosts demonstrated an overall detection accuracy of approximately 94%, with efficient resource utilization averaging 25–35% CPU and approximately 300 MB memory during scans. The system significantly reduces manual effort, improves detection coverage, and supports both expert and non-expert security practitioners in making timely, evidence-based security decisions.