Published Paper Details:

In today's digital landscape web applications have become an integral part of business operations data management and communication. However the growing dependency on dynamic websites has made them a primary target for cyberattacks particularly SQL Injection (SQLi) one of the most common and severe web security vulnerabilities. SQL injection attacks exploit improper input validation in database-driven applications allowing attackers to manipulate queries retrieve sensitive data or even gain unauthorized system access.This paper presents the design and implementation of a SQL Injection Detection Tool that automates the identification of SQLi vulnerabilities in web applications. The proposed system analyzes input fields and query structures to detect malicious SQL payloads using pattern matching regular expressions and keyword-based anomaly detection. The tool also classifies injection attempts by type generates real-time alerts and provides detailed vulnerability reports for developers. Developed using Python Flask and MySQL the system aims to assist both developers and security analysts by offering a lightweight scalable and user-friendly interface for proactive vulnerability testing. Through experimental evaluation the tool demonstrates high accuracy in identifying SQLi patterns and ensures enhanced web application security. The proposed solution contributes to building safer online environments by emphasizing preventive detection over reactive mitigation aligning with the modern goals of secure software engineering and ethical hacking practices