A method comprising operating at least one hardware processor for: receiving, by a radio frequency (RF) receiver, a plurality of training RF transmissions from an RF device, wherein each of said training RF transmissions is temporally associated with operational parameters and ambient parameters of said RF receiver and said RF device; at a training stage, training a machine learning classifier based, at least in part, on a training set comprising: (i) a Carrier Frequency Offset (CFO) value calculated for each of said training RF transmissions, and (ii) labels associated with said operational parameters and said ambient parameters; and at an inference stage, applying said machine learning classifier to determine whether one or more runtime RF transmissions originate from said RF device.