Abstract: Methods, systems, and techniques for facilitating identification of electronic data exfiltration. A message transmission log and screenshot metadata are obtained. A screenshot corresponding to the screenshot metadata is matched to a sent electronic message, such as an email, having a file attachment represented in the message transmission log to generate an event. The screenshot metadata indicates that the screenshot was captured prior to when the message transmission log indicates the electronic message was sent. An anomaly score is determined for the sent electronic message is determined by applying unsupervised machine learning, such as by applying an isolation forest, to score the sent electronic message relative to a baseline. The anomaly score meeting or exceeding an anomaly threshold is treated as potentially being indicative of electronic data exfiltration.

Abstract: Methods, systems, and techniques for facilitating identification of electronic data exfiltration. A message transmission log and screenshot metadata are obtained. A screenshot corresponding to the screenshot metadata is matched to a sent electronic message, such as an email, having a file attachment represented in the message transmission log to generate an event. The screenshot metadata indicates that the screenshot was captured prior to when the message transmission log indicates the electronic message was sent. An anomaly score is determined for the sent electronic message is determined by applying unsupervised machine learning, such as by applying an isolation forest, to score the sent electronic message relative to a baseline. The anomaly score meeting or exceeding an anomaly threshold is treated as potentially being indicative of electronic data exfiltration.

Abstract: Provided is a computer implemented method including receiving a digital communication; analyzing said communication using natural language processing to identify any semantic reference to one or more digital artifacts; and identifying and locating the one or more digital artifacts. In some embodiments one or more digital artifacts are not specifically identified in the digital communication. In some embodiments one or more digital artifacts are not specifically included in the digital communication. Related apparatus, systems, techniques, and articles are also described.

Abstract: Provided is a computer implemented method including receiving a digital communication; analyzing said communication using natural language processing to identify any semantic reference to one or more digital artifacts; and identifying and locating the one or more digital artifacts. In some embodiments one or more digital artifacts are not specifically identified in the digital communication. In some embodiments one or more digital artifacts are not specifically included in the digital communication. Related apparatus, systems, techniques, and articles are also described.

Abstract: An exercise glove, comprising: a palm portion; a dorsal portion; a knuckles portion; and a fingers portion; wherein said palm portion comprises two layers configured to slide against one another with low friction, but engage with high friction the hand of a user and an item to be gripped. Additionally, the dorsal portion and the knuckles portion are connected at a first seam; wherein said first seam runs substantially along a back of a hand of a user; and caused the exercise glove to be secured to the hand.