Abstract: Systems for dynamically detecting and controlling unauthorized events are presented. In some examples, data may be received from one or more computing systems. In some examples, the computing systems may each be associated with an enterprise unit within an enterprise organization. The data may include, in some examples, processed unauthorized activity event data, such as account takeover event data. The data received may be aggregated and analyzed (e.g., using machine learning) to identify potential threats and threat outputs. In some examples, the threat output may include a user interface indicating the threat or potential threat, systems or applications potentially impacted, enterprise units impacted, and the like. Based on the threat output, one or more mitigation actions may be identified and executed. The mitigation actions may include modifying operation of one or more systems, modifying authentication requirements, and the like.

Abstract: Systems for dynamically evaluating and controlling access to applications and systems are presented. In some examples, registration data may be received. In some examples, unauthorized activity data may be received. The unauthorized activity data may be analyzed to identify one or more vulnerable applications. Users of the one or more vulnerable applications may then be identified. Entitlements for the one or more vulnerable applications may be identified and, in particular, entitlements having privileged access may be identified. Users having entitlements with privileged access may be identified and one or more modified authentication requirements may be implemented.

Abstract: Systems for dynamically evaluating and controlling access to applications and systems are presented. In some examples, registration data may be received. In some examples, unauthorized activity data may be received. The unauthorized activity data may be analyzed to identify one or more vulnerable applications. Users of the one or more vulnerable applications may then be identified. Entitlements for the one or more vulnerable applications may be identified and, in particular, entitlements having privileged access may be identified. Users having entitlements with privileged access may be identified and one or more modified authentication requirements may be implemented.

Abstract: Systems for dynamically detecting and controlling unauthorized events are presented. In some examples, data may be received from one or more computing systems. In some examples, the computing systems may each be associated with an enterprise unit within an enterprise organization. The data may include, in some examples, processed unauthorized activity event data, such as account takeover event data. The data received may be aggregated and analyzed (e.g., using machine learning) to identify potential threats and threat outputs. In some examples, the threat output may include a user interface indicating the threat or potential threat, systems or applications potentially impacted, enterprise units impacted, and the like. Based on the threat output, one or more mitigation actions may be identified and executed. The mitigation actions may include modifying operation of one or more systems, modifying authentication requirements, and the like.