Twistlock Ltd.

Palo Alto Networks, Inc.

Minimus Ltd

Gutsy.io, Ltd

John Morello

Dima Stopel

Liron Levin

Michael Kletselman

Ami Bizamcher

Itay Abramowsky

Michael Velbaum

Ben Bernstein

Eran Yanay

Isaac Schnitzer

Daniel Shapira

Nitsan Ben Nun

Alon Adler

Nerya Agam

Reut Kravchook

A system and method for vulnerability remediation. A method includes identifying a vulnerable software package among a plurality of software packages based on cybersecurity data indicating a vulnerability; identifying at least one vulnerable software image of a plurality of software images by determining that the at least one vulnerable software image contains the vulnerable software package based on a plurality of files, wherein each of the plurality of software images is built based on a corresponding file of the plurality of files, wherein each file of the plurality of files includes a set of instructions for combining a subset of the plurality of software packages in order to build the corresponding software image of the plurality of software images; and performing at least one remediation action with respect to the at least one vulnerable software image.

Remediating vulnerabilities using software update management platform with integrated threat intelligence

A system and method for method for protecting cloud native environments based on cloud resource access. The method includes determining a mapping of a plurality of cloud assets to a plurality of cloud resources based on resource access data for a cloud native environment, wherein the plurality of cloud assets and the plurality of cloud resources are deployed in the cloud native environment, wherein each of the plurality of cloud assets is mapped to at least one associated cloud resource of the plurality of cloud resources; detecting at least one improper resource access based on the mapping and a cloud access security stream for the cloud native environment, wherein each of the at least one improper resource access deviates from the mapping; and performing at least one mitigation action with respect to the detected at least one improper resource access.

Techniques for protecting cloud native environments based on cloud resource access

A system and method for building software image. A method includes generating a prompt based on an input portion of application-identifying data; prompting a generative artificial intelligence model using the prompt in order to output text indicating a plurality of software packages, wherein each software package is a set of code for performing a plurality of functions of an application; generating a software image recipe based on the output text, wherein the software image recipe is a file including a set of instructions that cause a processing circuitry to build the software image by combining the plurality of software packages when executed; and building the software image by executing the software image recipe via the processing circuitry, wherein the software image causes deployment of a software component when executed, wherein the software component is configured to perform the plurality of functions of the application.

Artificial intelligence-based software image recipe creation and uses thereof

A system and method for software image management. A method includes generating a plurality of software packages, wherein each software package is generated using a respective set of code; building a plurality of software images based on a plurality of files, wherein building each software image further comprises combining a subset of the plurality of software packages according to a corresponding file of the plurality of files, wherein each file includes a set of instructions for combining the subset of the plurality of software packages in order to build the corresponding software image; and storing the plurality of software images in a repository.

Software image update management platform

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 method and system for cyber-security processes mining are provided. The method comprises correlating events received from a plurality of data sources into a plurality of flows, wherein a flow of the plurality of flows is a sequence of events having a same identifier, and wherein at least one of the plurality of data sources is a cyber-security system; correlating the plurality of flows into a plurality of variants, wherein a variant out of the plurality of variants includes one or more flows having the same repeatable pattern; associating the plurality of variants with at least one cyber-security process based on a predefined template defining the cyber-security process; and causing a display of the least one cyber-security process and its plurality of variants.

Systems and methods for security process analysis

A method and system for protecting an application from unsecure network exposure. The method includes identifying an at-risk application, wherein identifying the at-risk application further comprises determining that the application is configured incorrectly; identifying at least one port through which the at-risk application is accessible when the at-risk application is determined to be configured incorrectly; and determining, based on the identified at least one port through which the at-risk application is accessible, whether an exposure vulnerability exists, wherein the exposure vulnerability is an unapproved exposure of at least one of the at least one port to external resources.

Techniques for protecting applications from unsecure network exposure

Techniques for providing contextual forensic data based on user activities. A first method includes identifying a user action in user activity data, wherein the user action is a discrete event initiated by a user, wherein the user action is performed with respect to a portion of a system; and correlating the identified user action with at least one system change, wherein the at least one system change is related to the portion of the system, wherein the at least one system change occurred after the user action. A second method includes taking a first snapshot before a user action occurs, wherein the user action is a discrete event initiated by a user, wherein the first snapshot is taken of at least a portion of a system; and taking a second snapshot after the user action occurs, wherein the second snapshot is taken of the at least a portion of the system.

Providing contextual forensic data for user activity-related security incidents

A host device and methods for efficient distributed security forensics. The method includes creating, at a host device configured to run a virtualization entity, an event index for the virtualization entity; encoding a plurality of events related to the virtualization entity, wherein each event includes a process having a process path; and updating the event index based on the encoded plurality of events.

System and method for distributed security forensics

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 securing execution environments by quarantining software containers. A method includes: determining, based on configuration data for an application stored in the application software container, at least one intended behavior of the application when executed by the application software container; monitoring execution of the application software container in a first execution environment, wherein the monitoring further comprises comparing the execution of the application software container to the at least one intended behavior; detecting an unauthorized action by the application software container when the execution of the application software container is anomalous as compared to the at least one intended behavior; and quarantining the application software container by migrating the application software container from the first execution environment to a second execution environment when the unauthorized action is detected.

Techniques for securing execution environments by quarantining software containers

A plurality of connection patterns is determined based on connectivity data collected by a plurality of agents. Each agent of the plurality of agents is installed on a respective compute node of a plurality of compute nodes. The connectivity data collected by each agent of the plurality of agents includes node-local connectivity data indicating node-local connections for the respective compute node on which the agent is installed. The node-local connections include communications with at least one application entity hosted by the respective compute node. A graph representation that is organized with respect to the at least one application entity hosted by each of the plurality of compute nodes is generated based on the plurality of connection patterns.

Radar visualization of cloud native environments

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.

Growing community of inventors

Baton Rouge, LA, United States of America

John Morello