Abstract: A neural dialogue system has been designed to present a conversational user interface for managing security posture of an organization. The neural dialogue system determines intent and extracts entity names from a user input. The neural dialogue system grounds the entity names to an organizational context and maps the intent to a defined functionality related to security posture management for intent realization. Some of these defined functions involve editing the ordered ruleset. When realization of an intent involves editing the ordered ruleset, the neural dialogue system determines various ruleset command sequences that implement the ruleset editing and corresponding impacts on the ordered ruleset (e.g., creation of ruleset anomalies). The dialogue system collects the information retrieved based on the intent and grounded entities, including any ruleset impact assessment, and generates a response.

Abstract: A security configuration gap analysis system described herein infers roles of source and destination entities of a zone in a network at an organization. The system infers the roles by generating feature values from clustering traffic logs and extracting fields from configuration files of the zone and applying rules to the feature values that output a source/destination role pair. The system additionally compares the identified role pair to best practices to identify security services not implemented or correctly implemented at the firewall for the zone.

Abstract: A neural dialogue system has been designed to present a conversational user interface for managing security posture of an organization. The neural dialogue system determines intent and extracts entity names from a user input. The neural dialogue system grounds the entity names to an organizational context and maps the intent to a defined functionality related to security posture management for intent realization. Some of these defined functions involve editing the ordered ruleset. When realization of an intent involves editing the ordered ruleset, the neural dialogue system determines various ruleset command sequences that implement the ruleset editing and corresponding impacts on the ordered ruleset (e.g., creation of ruleset anomalies). The dialogue system collects the information retrieved based on the intent and grounded entities, including any ruleset impact assessment, and generates a response.

Abstract: A security configuration gap analysis system described herein infers roles of source and destination entities of a zone in a network at an organization. The system infers the roles by generating feature values from clustering traffic logs and extracting fields from configuration files of the zone and applying rules to the feature values that output a source/destination role pair. The system additionally compares the identified role pair to best practices to identify security services not implemented or correctly implemented at the firewall for the zone.