Fireeye, Inc.

Balbix, Inc.

Vineet Kumar

Alexander Otvagin

Arsen Movsesyan

Rajarshi Gupta

Vinay Sridhara

Gaurav Banga

Nikita Borodulin

According to one embodiment, a system featuring one or more processors and memory that includes monitoring logic. During operation, the monitoring logic is configured to monitor for and detect a notification message that is directed to a destination other than the monitoring logic and identify an event associated with a change in state of a data store associated with the file system to occur. The notification message, at least in part, triggers a malware analysis to be conducted on an object associated with the state change event.

System and method for triggering analysis of an object for malware in response to modification of that object

Approaches for analyzing risk of security breaches to a network. Agents gather, from multiple sources across the network, analysis data that identifies one or more habitable nodes and one or more opaque nodes. Habitable nodes each possess a computing environment conducive to installation of at least one of agent, while opaque nodes do not. An enterprise risk model is generated for the network using the analysis data. The enterprise risk model models a risk of security breaches to assets of the network from both authorized and unauthorized users of the network based on attributes of the habitable nodes and the opaque nodes of the network. The enterprise risk model may model both the present and the future risk to the enterprise, enabling, resources, such as time and money, to be best allocated in a scientific and methodical manner to improve the risk profile of the enterprise network.

Comprehensive modeling and mitigation of security risk vulnerabilities in an enterprise network

Approaches for enforcing security constraints against a network without impacting business workflows. A network is programmatically divided into a set of restrictive subnetworks without human intervention. One or more agents, executing on a plurality of nodes of the network, enforce security constraints by requiring a process, which requests access to an asset stored on a node of the network, to possess a security credential associated with a particular restrictive subnetwork to which the node belongs for access to the asset to be granted. The set of restrictive subnetworks may be determined based upon an enterprise risk model that models both the present and the future risk to the enterprise.

Mitigation of security risk vulnerabilities in an enterprise network

According to one embodiment, a system featuring one or more processors and memory that includes monitoring logic. In operation, the monitoring logic monitors for a notification message that identifies a state change event that represents an activity has caused a change in state of a data store associated with a storage system. The notification message triggers a malware analysis to be conducted on an object associated with the state change event.

A modularized architecture using vertical partitioning of a database is configured to store object metadata and processing results of one or more objects analyzed by a state machine, such as an analysis engine of a malware detection system. The database may include data structures, such as one or more master blocks, state sub-blocks, and state co-tables, as well as state transition queues. The modularized architecture may organize the database as one or more stages of the state machine, such that each stage corresponds to a module of the state machine, wherein the module generates results that are stored in its associated state co-table, which then provides information for a next stage. Each next stage may have a dependency on the one or more prior stages that provide input for execution of the next stage module. Dependency logic associated with each stage may determine whether the dependency is satisfied and, if so, may insert an action request into the state transition queue for the next stage to invoke an action associated with that stage.

Modular architecture for analysis database

A malware detection system may be configured to enhance analysis of an object when determining whether results for a previously analyzed object may be applied to the object. The enhanced analysis may employ context factors pertaining to an environment within which the objects operate. If an object identifier (ID) of the object matches the object ID of the previously analyzed object, but one or more of the context factors differ, then the results from the previously analyzed object may not be applied to the object and the object is subjected to further analysis, e.g., behavioral analysis. Yet if the context factors do not differ, then the object may be deemed a duplicate of the previously analyzed object, such that a result (such as an alert or 'no action') of the previously analyzed object may be applied to the object.

Determining duplicate objects for malware analysis using environmental/context information

A modularized architecture using vertical partitioning of a database is configured to store object metadata and processing results of one or more objects analyzed by a state machine, such as an analysis engine of a malware detection system. The database may include a plurality of data structures, such as one or more master blocks, state sub-blocks, and state co-tables, as well as state transition queues. The modularized architecture may organize the database as one or more stages of a state machine, wherein each stage includes a state sub-block, a state co-table and a state transition queue. The modularized architecture may further organize the database such that each stage corresponds to an action, i.e., module, of the state machine on the object. The module may process the data structures of its corresponding stage such that a state sub-block receives information from its state transition queue, wherein the module generates results that are stored in its associated state co-table, which then provides information for a next stage.

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San Jose, CA, United States of America

Vineet Kumar