In current times, malefactors chances to succeed in performing a social engineering attack on company usually depends on how much personal information about employees he owns. Thus, search and analysis of public information about company’s employees from social network websites with purpose of protection company from malicious actions is important issue. This article is devoted to methods of identifying user’s online footprint in website of social network VK.com. Prototype of the tool for identifying employees public pages using binary decision trees as classifier is presented. Approach to fully automated gathering of training dataset is described.