Treffer: Detection of Cross-Site Scripting Vulnerabilities using a Deep Learning Approach.

In this paper, a method is proposed to detect Cross-Site Scripting (XSS) vulnerabilities in website source code. The method employs deep learning techniques, specifically Convolutional Neural Networks (CNNs), for detection. First, the source code (HTML, CSS, and JavaScript) is converted into an image. This image is then fed into the CNN to extract features. The extracted features are subsequently passed to a fully connected neural network that classifies the input code as either vulnerable or benign. To evaluate the performance of the proposed method, a dataset containing both malicious and benign scripts is used. Experimental results demonstrate that the method achieves a promising performance compared to existing approaches. [ABSTRACT FROM AUTHOR]