Safeweb - Automated Web Vulnerability Detection and Prevention Using Open Source Tools

  • Unique Paper ID: 193265
  • Volume: 12
  • Issue: 9
  • PageNo: 4667-4672
  • Abstract:
  • Web applications are now increasingly essential in digital services as they are open to access and take complex inputs. At the same time, they are also a victim to security issues such as SQL Injection, Cross-Site Scripting (XSS), Command Injection, Directory Traversal and others through network traffic. To solve these issues, the Paper SafeWeb – An automated platform for scanning web vulnerability and detecting attack. A centralised system that uses role-based access control and automatic methods to discover and analyse security issues Users can scan websites for vulnerabilities, test for SQL Injection, and check network traffic data using this platform. It scans URL parameters, input data, and HTTP requests in an orderly manner. When an attack is detected, it classifies and logs the details such as type of attack, severity, confidence level, attack source IP address, and time of occurrence. The system includes an administrative Security Operations Center (SOC), which monitors and controls the application as well as determines users, blocks malicious IP addresses, and creates reports. SafeWeb is a suitable solution for accessing web security across the world-wide web applications and websites. The documentation provides a clear and pratical information about the vulnerabilities and the tools used in the platform. The platform is clear, simple-structured and easy to understand for the students in finding and solving the web vulnerabilities.

Copyright & License

Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{193265,
        author = {Kasturi Ramya and Kasanneni Navya Sri and Mandava Sai Kamaal and Bejjam Bharath Prakash and Gudivada Durvasi},
        title = {Safeweb - Automated Web Vulnerability Detection and Prevention Using Open Source Tools},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {9},
        pages = {4667-4672},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=193265},
        abstract = {Web applications are now increasingly essential in digital services as they are open to access and take complex inputs. At the same time, they are also a victim to security issues such as SQL Injection, Cross-Site Scripting (XSS), Command Injection, Directory Traversal and others through network traffic. To solve these issues, the Paper SafeWeb – An automated platform for scanning web vulnerability and detecting attack. A centralised system that uses role-based access control and automatic methods to discover and analyse security issues Users can scan websites for vulnerabilities, test for SQL Injection, and check network traffic data using this platform. It scans URL parameters, input data, and HTTP requests in an orderly manner. When an attack is detected, it classifies and logs the details such as type of attack, severity, confidence level, attack source IP address, and time of occurrence. The system includes an administrative Security Operations Center (SOC), which monitors and controls the application as well as determines users, blocks malicious IP addresses, and creates reports. SafeWeb is a suitable solution for accessing web security across the world-wide web applications and websites. The documentation provides a clear and pratical information about the vulnerabilities and the tools used in the platform. The platform is clear, simple-structured and easy to understand for the students in finding and solving the web vulnerabilities.},
        keywords = {Web Security, Vulnerability Scanning, Rule-Based Detection, SQL Injection, Attack Detection and Remediation.},
        month = {February},
        }

Cite This Article

Ramya, K., & Sri, K. N., & Kamaal, M. S., & Prakash, B. B., & Durvasi, G. (2026). Safeweb - Automated Web Vulnerability Detection and Prevention Using Open Source Tools. International Journal of Innovative Research in Technology (IJIRT), 12(9), 4667–4672.

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