Abstract
This paper presents a method for automating web application testing using the ChatGPT API, designed to help ethical hackers identify vulnerabilities. The goal of the research is to develop an approach that improves the efficiency and accuracy of pentesting, focusing on the automation of processes that are traditionally performed manually. The proposed method is based on the capabilities of the GPT model to generate test requests and analyze server responses, which allows detecting potential vulnerabilities without the need for detailed analysis of the source code. The presented results demonstrate the advantages of using GPT models for generating complex test scenarios and analyzing web application responses, which helps identify potential threats. The results of the experiments showed an increase in the accuracy of vulnerability detection by 15-20% and a reduction in testing time by 35% compared to traditional methods. The proposed approach is promising for implementation in the practice of ethical hacking and cyber security.
Published Version
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