Execution flows of a program can be characterized by a series of execution events. The rates at which these execution events occur for a particular program can be collected periodically, and the execution events statistics can be utilized for both training a machine learning model, and later on for making classification inferences to determine whether a program run contains any abnormality. When an abnormality is encountered, an alert can be generated and provided to supervisory logic of a computing system to indicate that an abnormal program flow has been detected.