VULNERABILITY RATING ENGINE

Abstract: the present disclosure relates to systems and methods for determining comprehensive and asset vulnerability ratings using models such as artificial intelligence (ai) and machine learning (ml) models. these models can identify relevant attributes, optimize attribute values, and determine logical relationships between attributes. the term “model” encompasses various types of ai and ml models, including neural networks, language models, multimodal models, and others. models can be trained using supervised learning with labeled data to predict or classify new data items. the models can be locally hosted, cloud-managed, or accessed via apis, and can be implemented in electronic hardware such as computer processors.

Inventor(s): Elad Ben Akoune, Roy Berland, Tal Peled

CPC Classification: G06F21/577 ({Assessing vulnerabilities and evaluating computer system security})

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