Cross site scripting is a kind of vulnerability, that typically appeares in web applications. A malicious web user injects a code into the website, that can also be seen by other users. Machine learning methods generate intelligence from experience, they can recognize patterns without being exactly programmed to do so. The aim of the project is to support and fasten the operation of the SOC by automation the detection of XSS payloads. This includes the processing of the related literature, the collection of datasets and the testing of multiple models for recieving the best output for this problem.