Servicenow, Inc.

Symantec Corporation

Harold Byun

Richard Kenneth Reybok

David Victor Barkovic

Vivian Tero

Anushree Randad

Adam Jackson

Cresta Kirkwood

Lal Narayanasamy

Jeremy Mailen

Pritesh Sharma

Clifford Huntington

Kurt Joseph Zettel, Ii

Ryan Christopher Currier

Michel Abou Samah

Scott Lewis

Sally Kauffman

Sachin Shivarama Nayak

Alan Dale Galindez

James Gavin Erbes

Zhe Wang

Philip Sarin

Himanshu Bari

Patrice Tollenaere

Systems and methods for configuration vulnerability checking and remediation are provided. The systems provided herein identify risk based upon service indications of a particular configuration, such that automated risk analysis may be facilitated.

Systems and methods for automated governance, risk, and compliance

An embodiment may involve transmitting, to a first client device, a representation of a first graphical user interface. The first graphical user interface may define fillable web-based forms. The embodiment may involve receiving, from the first client device, a first submission of the fillable web-based forms. The embodiment may involve transmitting, to a second client device, a representation of a second graphical user interface. The second graphical user interface may allow the second client device to fill out the fillable web-based forms. The embodiment may further involve receiving, from the second client device, a second submission of the fillable web-based forms. The embodiment may further involve determining numerical scores associated with each of the fillable web-based forms. The embodiment may also involve transmitting a representation of a third graphical user interface. The third graphical user interface may show the fillable web-based forms and their respective numerical scores.

Graphical user interface for inter-party communication with automatic scoring

Providing are incident response techniques useful for personas with a variety of experience levels are described. The incident response techniques include a graphical user interface (GUI) for providing a variety of different views for different personas. The graphical user interface may provide a landing page for providing a queue of risk-score prioritized incidents, an incident playbook for providing default or customizable instructions for resolving a particular incident to lesser-experienced personas, an explore container for facilitating efficient navigation of data associated with a particular incident by more-experienced personas, and an activity stream container for providing an overview of activities that have been performed with regard to a particular incident to more-experienced or supervising personas. The explore container may also be integrated with tools for performing actions with the data without leaving the graphical user interface.

Incident response techniques

Systems and methods for configuration vulnerability checking and remediation are provided. The systems provided herein map vulnerability data with compliance data, such that automated compliance indication may be facilitated.

Sensitive file accessing trends can be visually represented. In one embodiment, the present invention includes receiving, in a graphical user interface (GUI), a first user input indicating a selection of one folder from a plurality of folders, and identifying a plurality of sensitive files in the selected folder using one or more data loss prevention policies. In one embodiment access usage data for the sensitive files can be obtained and the number of users accessing the sensitive files within a plurality of time intervals can be determined using the access usage data. Finally, a usage trend representation comprising a visual illustration of the number of users accessing the sensitive files within each of the plurality of time intervals can be displayed to a user.

Graphical user interface including usage trending for sensitive files

A method for calculating a risk score of a data object may include obtaining a severity level associated with a data object. The severity level may be calculated based on presence of confidential information in the data object. The data object may be a file or a folder. The severity level may be calculated using a data loss prevention policy. The method may further include obtaining metadata associated with the data object. The metadata may comprise at least one of access permission data for the data object and access usage data for the data object. The method may further include calculating a risk score for the data object based on the severity level and the metadata associated with the data object.

Method to calculate a risk score of a folder that has been scanned for confidential information

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Belmont, CA, United States of America

Harold Byun