The aim of our work is to develop a software that could detect toxicity in the Russian segment of social media. In this paper, we investigated the problem of toxic detection in messages in Russian language. We implemented a set of features using selected vector models, trained some classifiers on the dataset about fourteen thousand annotated messages and compare results. Experiments were conducted with a calculation of accuracy, precision, and recall values. F1 measure reached the value 0.91, accuracy value is 0.87.