The author of the article consider information components of research on the development of forensic science as an applied science of solving computer crimes from the point of view of providing services for the analysis of problem situations. The paper presents the history of studying and researching the problem of identifying fake information, its classification and grouping into seven main categories. Content labeling system development views are analyzed to restore characteristic/traditional on-line news segmentation. Theoretical and practical discourses are studied, such as scenarios and concepts of unreliability, marking the disinformation field, creating a technology for detecting “news fakes”. The practical significance is that the generalization of the data obtained can be useful in creating artificial intelligence systems that will be able to recognize a possible infovirus and automatically prevent misinformation. The article presents the history of studying and researching the problem of identifying fake information, its classification and grouping into seven main categories. Social, financial and technical aspects of possible consequences are formulated, and their bipolarity is described in terms of positive prospects and negative impacts. The goal is to attract the attention of a wide range of users to the problem of detecting fake messages, news, and Internet portals in mostly significant time periods, in this particular case during the development of the COVID-2019 coronavirus pandemic.