Paper Title
XSS/SQL Vulnerability Scanner Tool - (Sentinel)
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Abstract
The objective of this paper is to archive Sentinel, a Python-based CLI gadget developed for the automatic identification of Cross-Site Scripting (XSS) and SQL Injection (SQLi) vulnerabilities in the web applications. Proceeding with ParamSpider for parameter detection, Sentinel gets boosted in scanning capacity to provide a much broader spectrum of the existing vulnerabilities. The research starts with a general part on XSS and SQLi vulnerabilities. They are explained why they are significant and how often they affect web applications. Available automated vulnerability scanning tool's unlimitedness is described at first and it is followed by the introduction of Sentinel. The paper fully explores the built of Sentinel, file's structure, and major features, expressing the purpose of individual parts in the scanning. Instructions for use will be displayed thus consumers can use the product for XSS and SQLi vulnerabilities detection. The results of samples obtained from websites which are at elevated risk have been used as reliable proof that the tool is accurate in identifying and reporting vulnerabilities. Sentinel's performance is evaluated in comparison to existing scanning tools, and factors like accuracy, clarity, and ease of use are measured. Evaluation results serve as a basis for future improvements and research directions and, therefore, indicate that Sentinel is a smart choice, given its high flexibility as a web security tool. In the end, Sentinel proves to be a precious ally in the cybersecurity ammunition, providing security professionals and developers with a useful tool which makes it easy to scan and fix the possible non-secure parts of the web applications before the hackers attack the system.
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How To Cite (APA)
Anumandla Dhanush, Ch Arun Teja, Mariserla Manisha, & Ruth (May-2024). XSS/SQL Vulnerability Scanner Tool - (Sentinel). INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(5), d137-d145. https://ijnrd.org/papers/IJNRD2405318.pdf
Issue
Volume 9 Issue 5, May-2024
Pages : d137-d145
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Paper Reg. ID: IJNRD_221313
Published Paper Id: IJNRD2405318
Downloads: 000122001
Research Area: Computer Science & TechnologyÂ
Author Type: Indian Author
Country: Sangareddy, Telangana, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2405318.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2405318
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