Fireeye, Inc.

Musarubra US LLC

Fireeye Security Holdings US LLC

Mumtaz Siddiqui

Manju Radhakrishnan

Alexander Otvagin

Deepak Agarwal

A computerized method is described for authenticating access to a subscription-based service to detect an attempted cyber-attack. More specifically, a request is received for a subscription for analysis of objects, which are supplied by a customer to a malware detection system. A customer identifier is assigned to the customer initiating the request for the subscription and a sensor associated with the customer is identified and an identifier of the sensor is associated with the customer identifier. Then, service policy level information pertaining to the subscription is associated with the identifier of the sensor, where the service policy level information includes a set of subscription attributes including object analysis restrictions.

Subscription-based malware detection

A cloud-based system is design with multi-tenancy controls for conducting analytics performed on objects submitted by a subscriber. This system features an analysis monitoring service and an analysis selection services. The analysis monitoring service, operating as a first cloud service, includes logic that is configured to collect metadata associated with an operating state for each of a plurality of clusters and generate cluster selection information. The analysis selection service, operating as a second cloud service and communicatively coupled to the analysis monitoring service, is configured to select a cluster of the plurality of clusters to analyze the object for malware based, at least in part, on the cluster selection information provided from the analysis monitoring service.

Attribute-controlled malware detection

A computerized method is described for authenticating access to a subscription-based service to detect an attempted cyber-attack. More specifically, service policy level information is received by a cloud broker. The service policy level information includes an identifier of a sensor operating as a source of one or more objects for analysis and an identifier assigned to a customer associated with the sensor. Thereafter, a cluster of a plurality of clusters is selected by the cloud broker. The cloud broker is configured to (i) analyze whether one or more objects are associated with an attempted cyber-attack by at least analyzing the sensor identifier to select the cluster based on at least a geographical location of the sensor determined by the sensor identifier and (ii) establish a communication session between the sensor and the cluster via the cloud broker until termination of the communication session.

A computerized method is described for authenticating access to a subscription-based service to detect an attempted cyber-attack. First, a request is received by a subscription review service to subscribe to the subscription-based service. The service is configured to analyze one or more objects for a potential presence of malware representing the attempted cyber-attack. Using service policy level information, the cloud broker selects a cluster from a plurality of clusters to analyze whether the one or more objects are associated with the attempted cyber-attack and establishes a communication session between the sensor and the cluster via the cloud broker. The service policy level information is associated with the customer and is used in accessing the subscription-based service. The service policy level information includes at least an identifier assigned to the customer.

A system featuring a cloud-based malware detection system for analyzing an object to determine whether the object is associated with a cyber-attack. Herein, subscription review service comprises a data store storing subscription information. The subscription information includes identifier for the customer and one or more identifiers each associated with a corresponding customer submitter operable to submit an object to the cloud-based malware detection system for analysis. The first customer submitter receives credentials provided by the subscription review service to establish communications with the cloud-based malware detection system. The first customer submitter includes a first submitter identifier that comprises (i) enforcement logic that enforces compliance with a plurality of requirements of the subscription to the cloud-based malware detection system and (ii) reporting logic that transmits a result of the analysis of the object by the cloud-based malware detection system in determining whether the object is associated with a cyber-attack.

System and method for enforcing compliance with subscription requirements for cyber-attack detection service

A computerized method for authenticating access to a subscription-based service to detect an attempted cyber-attack. The method features operations by the cloud broker that include receiving service policy level information and information based on operational metadata. The service policy level information includes at least subscription attributes to identify one or more performance criterion in analyses conducted on one or more objects submitted by a sensor for malware representing an attempted cyber-attack. The operational metadata includes metadata that pertains to an operating state of one or more clusters of a plurality of clusters of the subscription-based service. The cloud broker, using both the service policy level information and the information based on the operational metadata, selecting a cluster of the plurality of clusters to analyze the one or more objects submitted by the sensor and establishes a communication session between the sensor and the cluster via the cloud broker.

A scalable, threat detection system features computing nodes including a first computing node and a second computing node operating as a cluster. Each computing node features an analysis coordinator and an object analyzer. The analysis coordinator is configured to conduct an analysis of metadata associated with a suspicious object that is to be analyzed for malware, where the metadata being received from a remotely located network device and to store a portion of the metadata within a data store. The object analyzer is configured to retrieve the portion of the metadata from the data store, monitor a duration of retention of the metadata in the data store, and determine whether a timeout event has occurred for the object associated with the metadata based on retention of the metadata within the data store that exceeds a timeout value included as part of the metadata associated with the suspicious object for malware.

Timeout management services

Sensor enrollment management is conducted where features and capabilities for one or more broker computing nodes within the cluster are received by an enrollment service operating within a management system. The enrollment service is configured to receive advertised features and capabilities for computing nodes that are part of a cluster and provide address information associated with the enrollment service to the sensor. Based on information supplied by the sensor, the enrollment service authenticates the sensor, and upon authentication, forwards keying material associated with the sensor to a computing node selected that is selected for supporting communications to the cluster from the sensor. Also, the enrollment service provides a portion of the advertised features and capabilities associated with the computing node to the sensor to enable the sensor to establish a secure communication path with the computing node for malware analysis of suspicious objects within network traffic monitored by the sensor.

System and method for managing sensor enrollment

A computerized method for enforcing compliance to a subscription for object evaluation service by a malware detection system is described. Enforcement logic receives operational metadata from the malware detection system. The operational metadata includes metadata associated with operations performed on objects submitted to the malware detection system by the one or more customers. For each customer, the operational metadata associated with operations performed on data submitted by the customer is analyzed for comparison with a plurality of service attributes associated with the subscription for the customer. Responsive to detecting that the customer is failing to comply with one or more service attributes of the plurality of service attributes, performing, by the enforcement logic, an operation to remedy (i) a failure by the customer in complying with the subscription requirements for the customer or (ii) a failure by the malware detection system in providing the customer with object evaluation service that satisfies the subscription requirements for the customer.

Multi-level control for enhanced resource and object evaluation management of malware detection system

A method to ensure availability of a plurality of computing nodes operating within a cluster that analyzes suspicious objects received from geographically remote sensors for malware is described. Responsive to a change in operability of a cluster, a determination is made whether the change is directed to a broker computing node or an analytic computing node. Where the change is a failover experienced by a broker computing node, a determination is made whether the cluster includes a plurality of broker computing nodes, and if not, an analytic computing node is configured to operate as a second broker computing node. For a takeover event, however, a determination is made whether the cluster includes a plurality of broker computing nodes, and if not, the analytic computing node operates as the second broker computing node. The first broker computing node is subsequently placed into an off-line status until maintenance has completed.

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Fremont, CA, United States of America

Mumtaz Siddiqui