Considering the widespread diffusion of machine learning techniques to solve several issues, from network security to malware detection, in this paper we propose the adoption of word embeddings aimed to improve the machine learning-based classifiers. Three real-world experiment we perform in order to demonstrate that the proposed method overcomes in terms of performances the mostly used machine-learning algorithms.