Normalyze, Inc.

Netskope, Inc.

Ajay Agrawal

Yang Zhang

Krishna Narayanaswamy

Ravishankar Ganesh Ithal

Nimish Salve

The disclosed technology receives a control input identifying a sampling criterion for classifying a data store storing a set of data objects in a computing environment as corresponding to a target data type and deploys one or more scanners configured to select a representative subset of data objects, from the set of data objects, based on the sampling criterion. A scanner result generated by the one or more scanners is received that represents detected instances, in the representative subset of data objects, of one or more pre-defined data patterns of the target data type. A classification result is generated based on a comparison of the number of detected instances of the one or more pre-defined data patterns to a threshold. The classification result represents a classification of the data store as having correspondence to the target data type. A computing action is performed based on the classification result.

Data scan sampling control for data discovery and posture management

A computer-implemented method includes detecting occurrence of an event in a cloud environment, obtaining an indication of an identity associated with the event, obtaining an indication of a usage time stamp representing usage time of a privilege in association with the identity for the event, and classifying the privilege into a classification group selected from a plurality of predefined classification groups. Each respective classification group groups a respective set of privileges defined in the cloud environment. The method includes obtaining a grant time stamp representing a grant time of at least one privilege, in the respective set of privileges in the classification group, to the identity and, based on the usage time stamp and the grant time stamp, generating an excessive privilege determination that indicates the classification group includes at least one excessive privilege. The method includes performing a computing action based on the excessive privilege determination.

Cloud data attack surface tracking using graph-based excessive privilege detection

The technology disclosed relates to analysis of security posture of a cloud environment. A computing system is configured to automatically discover a plurality of databases in the cloud environment and configure an orchestration engine to deploy a plurality of log analyzer microservices on the plurality of databases. Each log analyzer microservice, of the plurality of log analyzer microservices, is configured to scan a respective database log that represents database activities on a respective database of the plurality of databases. Analysis results are received from the plurality of log analyzer microservices. The analysis results represent detection of at least one of a performance criterion or a security criterion in one or more databases of the plurality of databases. An action signal representing the analysis results is generated.

Database log analyzer in a cloud environment using microservice orchestration

The technology disclosed relates to resource activity management in a cloud environment. A computer-implemented method includes detecting a plurality of virtual networks in the cloud environment and deploying a plurality of sensors in the plurality of virtual networks using an orchestration engine of the cloud environment. Each sensor, of the plurality of sensors, includes an executable package configured to execute in a respective virtual network, of the plurality of virtual networks, independent of other sensors, of the plurality of sensors, to manage activities in the respective virtual network. The method includes identifying an activity management task to be performed in a particular virtual network of the plurality of virtual networks, sending a task command representing the activity management task to the sensor deployed in the particular virtual network, and receiving an execution result representing execution of the activity management task by the sensor deployed in the particular virtual network.

Virtual private cloud resource activity management

The technology disclosed relates to endpoint data loss prevention (DLP). In particular, the technology disclosed relates to enforcing data loss prevention policies at an endpoint without needing to perform content sensitivity scan at the endpoint.

Endpoint data loss prevention (DLP)

The technology disclosed relates to analysis of security posture of a cloud environment. In particular, the disclosed technology relates to a system and method that detects a triggering criterion and, in response to the triggering criterion, automatically discovers a plurality of databases in the cloud environment. An orchestration engine is configured to deploy a plurality of log analyzer microservices on the plurality of databases, each log analyzer microservice, of the plurality of log analyzer microservices, being configured to scan a respective database log that represents database activities on a respective database of the plurality of databases. Analysis results are received from the plurality of log analyzer microservices, the analysis results represent detection of at least one of a performance criterion or a security criterion in one or more databases of the plurality of databases. An action signal representing the analysis results is generated.

Cloud environment database log analyzer with risk signature detection

The technology disclosed presents an improved endpoint data loss prevention (DLP) solution, referred to herein as 'small-footprint endpoint DLP (sf-EDLP),' which enforces security policies at endpoints by relying on previously generated sensitivity metadata, rather than by performing content sensitivity scans at the endpoints. Since content sensitivity scans are computationally intensive and time consuming, sf-EDLP leads to a significantly simpler implementation, reduced runtime computation, and a smaller memory footprint; making it suitable for computationally constrained environments such as modern mobile devices.

Growing community of inventors

Bengaluru, India

Ajay Agrawal