Cyber-net-secx : An Automated Framework For Network Vulnerability Assessment And Exploit Intelligence Integration

• Author(s):

  Harish R | Harish S | Hariharan C | Eshwara K

• Keywords:

  Cybersecurity, Vulnerability Assessment, Nmap, Metasploit, CVE Analysis

• Abstract:

  Network Security Has Become A Critical Concern As Modern Organizations Rely Heavily On Interconnected Systems And Digital Infrastructure. Identifying Vulnerabilities In Network Services Is Essential To Prevent Unauthorized Access, Data Breaches, And System Compromise. Traditional Vulnerability Assessment Processes Often Require Manual Analysis Using Multiple Tools, Which Can Be Time-consuming And Prone To Human Error.This Paper Presents Cyber-Net-SecX, An Automated Framework Designed To Streamline The Process Of Network Vulnerability Assessment. The Proposed System Integrates Network Reconnaissance, Vulnerability Intelligence Extraction, Exploit Feasibility Validation, And Risk Analysis Into A Single Automated Workflow. The Framework Utilizes Nmap For Host Discovery, Port Scanning, And Service Enumeration, While Detected Services Are Correlated With Common Vulnerabilities And Exposures (CVE)entries To Identify Potential Security Weaknesses. To Determine Exploit Feasibility, The System Connects To TheMetasploit Framework UsingRemote Procedure Call (RPC) And Verifies The Availability Of Relevant Exploit Modules. A CVSS-based Risk Analysis Model Is Applied To Evaluate Vulnerability Severity And Classify Risks.The Implementation Generates A Structured Multi-page Security Assessment Report Containing Detected Vulnerabilities, Exploit Intelligence, And Risk Severity Visualization. Experimental Testing In A Controlled Environment Using A Vulnerable Virtual Machine Demonstrates That The Automated Framework Significantly Reduces Manual Analysis Time While Improving Vulnerability Detection Efficiency. The Results Highlight The Effectiveness Of Automated Security Assessment Frameworks In Supporting Modern Cybersecurity Operations.

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Other Details

• Paper id:

  IJSARTV12I3104671

• Published in:

  Volume: 12 Issue: 3 March 2026

• Publication Date:

  2026-03-08

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