WEBHUNTER: Web-Based Vulnerability Scanner System

Authors

  • Tan Bo Jan Universiti Tun Hussein Onn Malaysia
  • Sofia Najwa Ramli Universiti Tun Hussein Onn Malaysia

Keywords:

WEBHUNTER, Vulnerability Scanner, Signature-Based Detection, SQL Injection (SQLi), Cross-Site Scripting (XSS), Cross-Site Request Forgery (CSRF), AI Assistant

Abstract

WEBHUNTER is a web-based vulnerability scanner that addresses the increasing demand for secure web applications in today’s digital landscape. Existing automated tools such as OWASP ZAP, Intruder, and Invicti often lack user-friendliness, consume significant system resources, require complex configurations, and provide limited interactive support. To overcome these challenges, WEBHUNTER provides an automated, user-friendly, and lightweight vulnerability assessment system that uses signature-based detection to efficiently identify known attack patterns. WEBHUNTER automatically detects common web application vulnerabilities, including SQL Injection (SQLi), Cross-Site Scripting (XSS), and Cross-Site Request Forgery (CSRF). The system generates detailed vulnerability reports incorporating Common Vulnerabilities and Exposures (CVE) references to provide clear security findings, impact analysis, and recommended mitigations. Additionally, WEBHUNTER integrates CometChat to offer live support and a real-time AI assistant via OpenAI to help users resolve issues quickly. WEBHUNTER’s development aligns with recognized cybersecurity standards such as the OWASP Web Security Testing Guide (WSTG), OWASP Top 10, ISO/IEC 27001 Information Security, and the MITRE Common Weakness Enumeration (CWE) to ensure compliance with accepted best practices. Through this system, web developers and security testers conduct vulnerability assessments in a more accessible, automated, and efficient way without requiring extensive security expertise. The implementation of WEBHUNTER helps organizations reduce the likelihood of cyberattacks, enhance web application security, and strengthen overall cybersecurity practices.

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Published

06-07-2026

Issue

Section

Articles

How to Cite

TAN, B. J., & RAMLI, S. N. (2026). WEBHUNTER: Web-Based Vulnerability Scanner System. Applied Information Technology And Computer Science, 7(1), 1229-1249. https://publisher.uthm.edu.my/periodicals/index.php/aitcs/article/view/21925