Vulnerability scanning is a critical component of cybersecurity, enabling organizations to detect and mitigate security threats before they are exploited by malicious actors. This study compares the effectiveness of an Nmap-based vulnerability scanning framework with the for-profit Nessus scanner, focusing on accuracy, efficiency, and performance. The proposed framework leverages intelligent matching algorithms combined with automated scanning techniques to enhance detection capabilities. Experimental results demonstrate that the framework significantly reduces scan time, completing a comprehensive security assessment in just 3 to 4 minutes, whereas Nessus requires approximately 67 minutes for the same process. Despite faster execution, the proposed framework maintains high accuracy, achieving a recall rate of 95% by successfully identifying 37 of the 39 vulnerabilities detected by Nessus. These findings suggest that integrating advanced matching techniques with automated scanning tools not only accelerates the vulnerability assessment process but also maintains a high level of detection reliability, ultimately improving cybersecurity defenses.