Endpoint-based man in the middle attack detection using machine learning models

摘要

A first node of a networked computing environment initiates each of a plurality of different types of man-in-the middle (MITM) detection tests to determine whether communications between first and second nodes of a computing network are likely to have been subject to an interception or an attempted interception by a third node. Thereafter, it is determined, by the first node, that at least one of the tests indicate that the communications are likely to have been intercepted by a third node. Data is then provided, by the first node, data that characterizes the determination. In some cases, one or more of the MITM detection tests utilizes a machine learning model. Related apparatus, systems, techniques and articles are also described.