Abstract: Embodiments of the technology described herein identify and mitigate phishing attempts by analyzing user input received at the operating system level. Initially, a credential, such as a username or password, is registered with the threat detection system. The technology described herein intercepts user input at the operating system level, generates a hash of the input, and compares it with a hash of a credential being monitored. The technology described herein will perform a threat assessment when a secret entry is detected. The threat assessment may use the application context and the network context as inputs to the assessment. When the threat assessment results in an unknown classification or when the snapshot is otherwise requested, a snapshot is captured to supplement the threat assessment. Based on user settings, the snapshot is consumed by a snapshot phishing machine learning model. Various mitigation actions may be taken when a threat is detected.

Abstract: The technology described herein identifies and mitigates phishing attempts by analyzing user input received at the operating system level. Initially, a credential, such as a username or password, is registered with the threat detection system. The technology described herein intercepts user input at the operating system level, generates a hash of the input, and compares it with a hash of a credential being monitored. A credential entry is detected when a hash for the character string entered matches a hash for a credential being monitored. The technology described herein will perform a threat assessment when a secret entry is detected. The threat assessment may use the application context and the network context as inputs to the assessment. Various mitigation actions may be taken when a threat is detected.

Abstract: Embodiments of the technology described herein identify and mitigate phishing attempts by analyzing user input received at the operating system level. Initially, a credential, such as a username or password, is registered with the threat detection system. The technology described herein intercepts user input at the operating system level, generates a hash of the input, and compares it with a hash of a credential being monitored. The technology described herein will perform a threat assessment when a secret entry is detected. The threat assessment may use the application context and the network context as inputs to the assessment. When the threat assessment results in an unknown classification or when the snapshot is otherwise requested, a snapshot is captured to supplement the threat assessment. Based on user settings, the snapshot is consumed by a snapshot phishing machine learning model. Various mitigation actions may be taken when a threat is detected.

Abstract: The technology described herein identifies and mitigates phishing attempts by analyzing user input received at the operating system level. Initially, a credential, such as a username or password, is registered with the threat detection system. The technology described herein intercepts user input at the operating system level, generates a hash of the input, and compares it with a hash of a credential being monitored. A credential entry is detected when a hash for the character string entered matches a hash for a credential being monitored. The technology described herein will perform a threat assessment when a secret entry is detected. The threat assessment may use the application context and the network context as inputs to the assessment. Various mitigation actions may be taken when a threat is detected.

Abstract: Systems and methods disclosed herein may include receiving from an audio application running on the computing device, a selection of a multimedia endpoint device. The multimedia endpoint device may be connected with the audio application in response to a request from the audio application. An audio stream of the audio application may be separated from a system audio stream. The system audio stream may include a plurality of audio signals generated by system components of the computing device or applications running on the computing device. The plurality of audio signals may be played on a default audio endpoint of the computing device. The separated audio stream of the audio application may be communicated to the selected multimedia endpoint device for playback. Separating the audio stream of the audio application from the system audio stream may be based on an API request from the application.