An Automated Web Vulnerability Scanner for Detecting Common Security Flaws in Modern Web Applications – Volume 12 Issue 5

Due to the high number of sectors utilizing web applications today such as, banking, healthcare, e-commerce and so on, security is the most prominent issue concerning the web applications. Traditional vulnerability testing techniques, such as manual penetration testing, may become time-consuming and expensive; they may also have a very high tolerance that renders them incapable of scaling to the size and complexity of a contemporary web application. A web vulnerability scanner created by us in this paper can prevent these deficiencies. Scanner based on the principles of crawling a web site, traversing links and form fields, submitting forms and reading responses, gathering all input vector by, and then determining all potential XSS -injection points. The trick that the tool applies is to execute attack payloads on target applications and to test their responses to attack the most prevalent web application security vulnerabilities. When a scan is completed, it creates a report in the form of JSON and enumerates the severity, description and location of the vulnerabilities identified. This automated method eliminates most of the manual testing and gives the developers relevant feedback of what they can do to enhance the security of web applications. The scanner is tiny and needs no extra computer hardware thus a great tool to developers, small businesses and schools. Experimentally, the scanner was determined to be capable of effectively identifying the vulnerable states and a practical tool in enhancing web security by experimenting with home-made vulnerable sites. The work is to be seen as a more convenient and efficient solution instead of the traditional security testing technology besides it aids in the fill-up of the hue in the vital security defects of web applications.

This research has developed an automatic web vulnerability scanner for the solving of heightened concern over web application security. The software is mainly focused on finding wide-spread vulnerabilities but also includes many other security checks as well such as SQL Injection (SQLi), Cross-Site Scripting (XXS), Configuration errors and more. The risk-based approach ensures that every identified issue is beaten on its own terms by focussing on the most relevant threats for web applications. The scanner proved to be very effective in case of the quick and accurate identification of the vulnerabilities through the rigorous test in controlled settings. The scanner was found to be more reliable and quicker compared to the traditional manual testing option, and the bonus was that it was less likely to be affected by human error. The tool is designed in modules, and this enables it to be scaled to accommodate a broad scope of web applications, between small websites and more complex ones. The fact that the scanner can produce detailed and structured reports in the form of the JSON format gives the developers actionable data of where the vulnerabilities it identifies are, allowing them to respond immediately, ensuring that their applications become more secure. Although in some cases there were false positives especially when minor misconfigurations were made, the overall performance was impressive ensuring that the tool is useful to developers and security professionals. Moving forward, the scanner indicates that additional developments could be made to the scanner, such as machine learning to detect vulnerabilities more intelligently and cloud compatibility to perform continuous monitoring of the current development environment. This will not only enhance the detection capabilities of the tool but also widen applicability of the tool to newer web technologies and dynamic environments. To sum up, the study provides a powerful, convenient, and affordable web vulnerability scanning tool, which has the potential to become a key component in the current endeavor to secure web-based applications against the more advanced cyber threat.

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