Twistlock Ltd.

Palo Alto Networks, Inc.

Itay Abramowsky

Dima Stopel

Liron Levin

John Morello

Michael Velbaum

Michael Kletselman

Ami Bizamcher

Isaac Schnitzer

A system and method for cloud native virtual machine (VM) runtime protection. The method includes creating a normal behavior model for a cloud native VM by training a machine learning model using a training data set including training activities performed by the cloud native VM, the cloud native VM being configured to provide at least one service, wherein the normal behavior model defines at least one capability of each service based on a set of capabilities for respective known services stored within a library of service-to-capability mappings, wherein each capability of a service indicates a plurality of discrete behaviors required by the service; and monitoring an execution of the cloud native VM to detect a deviation from the normal behavior model, wherein the deviation is caused by at least one abnormal behavior of one of the services that is not among the discrete behaviors defined in capabilities for the service.

Cloud native virtual machine runtime protection

A system and method for cloud native discovery and protection. The method includes discovering instances of a plurality of cloud assets in a cloud native environment based on a plurality of application programming interface (API) endpoints in the cloud native environment, wherein the plurality of API endpoints is identified based on cloud credentials for each of the plurality of cloud assets; determining at least one cloud asset instance that lacks active security protection based on a configuration of at least one entity deployed in the cloud native environment; and reconfiguring at least a portion of the cloud native environment with respect to the at least one cloud asset instance that lacks active security protection.

Cloud native discovery and protection

A system and method for cloud native virtual machine (VM) runtime protection. The method includes creating a normal behavior model for a cloud native VM by training a machine learning model using a training data set including a plurality of training activities performed by the cloud native VM, the cloud native VM being configured to provide at least one service, wherein the normal behavior model defines at least one capability of each of the at least one service, wherein each capability of a service indicates a plurality of discrete behaviors required by the service; and monitoring an execution of the cloud native VM to detect a deviation from the normal behavior model, wherein the deviation is caused by at least one abnormal behavior of one of the at least one service that is not among the discrete behaviors defined in the at least one capability for the service.

A system and method for cloud native discovery and protection. The method includes identifying a plurality of cloud assets in a cloud native environment based on cloud credentials for each of the plurality of cloud assets; determining at least one cloud asset instance that lacks active security protection based on a configuration of at least one of: each of the at least one cloud asset, and at least one security solution deployed in the cloud native environment, wherein each cloud asset instance is an instance of one of the plurality of cloud assets; and reconfiguring at least a portion of the cloud native environment with respect to the at least one cloud asset instance that lacks active security protection.

Growing community of inventors

Herzliya, Israel

Itay Abramowsky