Abstract

Every year, more vulnerabilities are found in software and websites, whether they are found internally in proprietary code or reported officially. These vulnerabilities have a strong probability of being used against users, which could damage systems and lead to data leakage. Injection attacks using a structured query language and header vulnerabilities are among the risks.

When speaking of web-based applications, SQL injection attacks are among the most common vulnerabilities. An organisation or corporation may suffer harm as a result of this type of attack since the attacker can steal sensitive and important information. Nowadays, using ML in many situations shows to be greatly advantageous. It uses to construct a variety of items that function like humans and save time.

This research paper used an algorithm called Extreme Gradient Boosting algorithm from ensemble machine learning methods to classify and detect SQL injection and created a chatbot with it. By using it the user will be able to know about the identified vulnerabilities, the risk, and the mitigation technique.

Keywords: Vulnerabilities, SQL Injection, Machine Learning, XGBoost Algorithm, Chatbot.

Bug Detection Using Artificial intelligence and Cyber Security