Mal4Sight

Our Mal4Sight dataset contains a set of executable files converted into grayscale images for researching image-based malware detection. The dataset includes 16,019 samples, made up of 11,971 malware samples from 35 families and 4,048 benign samples. Each executable file is divided into distinct sections: .text, .data, other and header. Each section is turned into a grayscale image of 256 x 256 pixels, resized from 512px to preserve byte-level structural patterns. The dataset is organised into training, validation, and testing subsets with set splits for both malware and benign samples. All images are stored in PNG format to keep consistent quality. This dataset can be used to train and evaluate machine learning and deep learning models for malware detection. It also supports tasks like feature extraction, pattern analysis, and comparisons of different image-based methods across various malware families.