Robust Vulnerability Detection System for SQL Injection Attacks

Robust Vulnerability Detection System for SQL Injection Attacks

Patel Vraj, Patel Dhairya, Pardeshi Parth

Research Scholar, Institute of Information Technology, Krishna School Of Emerging Technology &

Applied Research, KPGU University, Varnama, Vadodara, Gujarat, India

Assistant Professor, Department of Information Technology and Engineering, Krishna School Of Emerging Technology & Applied Research, KPGU University. Varnama, Vadodara, Gujarat, India

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Abstract - This project presents a Python-based SQL Injection Scanner designed to detect potential SQL injection vulnerabilities in web applications. Leveraging the Requests library, the scanner automates the process of sending HTTP requests to targeted web endpoints, while Beautiful Soup facilitates the parsing of HTML content to identify potentially vulnerable input fields. Streamlit is used to create an intuitive and interactive interface, allowing users to enter target URLs, adjust scanning parameters, and visualize detection results in real-time.

The scanner simulates common SQL injection patterns and analyzes server responses to flag suspicious behavior indicative of vulnerabilities. By providing quick feedback through the Streamlit interface, this tool is suitable for security professionals and developers looking to assess the resilience of their applications against SQL injection attacks. Through the integration of Python libraries and real-time reporting, this project demonstrates the effectiveness of automated web vulnerability detection and highlights the importance of secure coding practices