Secureworks, Inc.

Raul Garcia Calvo

William Parke Bowditch

John M Nicholas

Radoslaw Gasiorek

William Michael King

Tomasz Sarota-Raczek

The present disclosure provides systems and methods for generation of parsing scripts or rules for unstructured or semi-structured system log messages, including systems and methods for identifying and clustering of same or substantially similar system log messages using machine learning. Patterns indicative of the same or substantially similar types system log messages can be generated based on the clustering of the system log messages and calculated similarities of attributes or distances between common features/fields of the system log messages, with the results of the clustering presented for analysis and development or adjustment of parsing scripts.

Systems and methods for generating a system log parser

Systems and methods for identifying attack patterns or suspicious activity can include a profile builder, a primitive creator, and a compromise detector. The profile builder can populate one or more baseline activity profiles for each client of the plurality of clients or entities associated therewith. The primitive creator can create primitives by comparing identified or extracted features to information in the one or more baseline activity profiles. The compromise detector can receive primitives, and based on identified combinations or sequences of primitives, generate compromise events to be provided to clients.

Systems and methods for identifying attack patterns or suspicious activity in client networks

The present disclosure provides systems and methods for classifying or determined whether a request for a user's information is malicious or safe/legitimate. Request information related to a request for a user's information can be received, and one or more screenshots associated with the request can be obtained and provided to a machine learning model. The machine learning model can generate a probability or confidence level that the request is malicious.

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Edinburgh, United Kingdom

Raul Garcia Calvo