Modern businesses heavily depend on web applications, while these platforms consistently serve as the main focus for cybercriminals. Current research demonstrates the necessity of advanced vulnerability discovery techniques to protect sensitive information. Research on vulnerability scanners includes a review of static analysis methods, dynamic scanning methods, and automated framework integration, which this paper summarizes. The research shows that static analysis tools cover all code fully but generate many false alerts; thus, static testing and dynamic methods both have limitations in covering web application vulnerabilities effectively. The merger of information from various scanners as part of automated penetration testing frameworks produces superior detection accuracy as well as elevated recall and improved F-measures. Additional research must concentrate on developing more advanced methods for integration techniques combined with adaptive machine learning and artificial intelligence to minimize the number of incorrect alerts.