Vectra Networks, Inc.

Vectra Ai, Inc.

Nicolas Beauchesne

Karl Matthew Lynn

William Stow Finlayson, Iv

Ryan Prenger

Sohrob Kazerounian

Himanshu Mhatre

David Lopes Pegna

Oliver Kourosh Tavakoli

John Steven Mancini

Sungwook Yoon

Monty Sher Gill

Oskar Ibatullin

Daniel Carlton Hannah

Hsin Chen

Kevin Song-Kai Ni

William Stow Finlayson Iv

Ryan James Prenger

Disclosed is an approach for analyzing attack paths in computer network generated using a software representation that embodies network configuration and policy data for security management. In some embodiments, the approach includes a process to analyze attack paths in a computer network to determine which attack paths might be most productively covered using a corresponding detection signature. In some embodiments, the attack paths are identified using a software representation that embodies network configuration and policy data. The software representation comprises a state machine where different states can be reached using respective transitions or properties. The states correspond to respective entities on the network which may comprise resources that are identifiable for protection in the software representation using crash statements. The software representation can then be stimulated using software analysis tools such to identify sequences of state-to-state transitions that could be used to compromise a protected resource on the computer network.

Method, product, and system for analyzing attack paths in computer network generated using a software representation that embodies network configuration and policy data for security management

Disclosed is an approach for network security management using software representation that embodies network configuration and policy data. In some embodiments, the approach includes a process to generate a software representation of what is possible based on a network configuration and policy data. The software representation comprises a state machine where different states can be reached using respective transitions or properties why are possible as determined based on the network configuration and policy data. The states correspond to respective entities on the network which may comprise resources that are identifiable for protection. The software representation can then be stimulated to identify sequences of state-to-state transitions which may in turn be processed to generate corresponding detection signatures for use in monitoring the network.

Method, product, and system for network security management using software representation that embodies network configuration and policy data

Disclosed is an approach for generating detection signatures based on analysis of a software representation of what is possible in a computer network based on network configuration data and network policy data. In some embodiments, the process includes maintaining a plurality of detection signature templates, generation of detection signatures (detection signature instances) using respective detection signature templates that are selected based on the analysis of the software representation. In some embodiments, detection signatures templates are of different type and may be deployed at different locations based on their respective type(s), such as at source, destination.

Method, product, and system for generating detection signatures based on attack paths in a computer network identified using a software representation that embodies network configuration and policy data for security management using detection signature templates

Disclosed is an approach for analyzing a computer network to identify attack paths using a software representation that embodies network configuration and policy data for security management. The software representation comprises a state machine where different states can be reached using respective transitions or properties which are possible as determined based on the network configuration and network policy data. The states correspond to respective entities on the network which may comprise resources that are identifiable for protection in the software representation using crash statements. The software representation can then be stimulated using software analysis tools such as fuzzers to identify sequences of state-to-state transitions that could be used to compromise a protected resource on the computer network.

Method, product, and system for analyzing a computer network to identify attack paths using a software representation that embodies network configuration and policy data for security management

Disclosed is an improved method, system, and computer program product for identifying malicious payloads. The disclosed approach identifies potentially malicious payload exchanges which may be associated with payload injection or root-kit magic key usage.

Method and system for detecting malicious payloads

Disclosed is an improved approach for identifying security risks and breaches in a network by applying machine learning methods that learn resource access patterns in the network. Specifically, by observing the access pattern of the network entities (e.g. accounts, services, and hosts) from authorization requests/responses, the model through unsupervised learning, organizes the entity relationships into an ensemble of hierarchical models. The ensemble of hierarchical models can then be leveraged to create a series of metrics that can be used to identify various types of abnormalities in the access of a resource on the network. For instance, by further classifying the access request for a resource using abnormality scores into detection scenarios, the model is able to detect both an abnormality and the type of abnormality and include such information in a corresponding alarm when a security breach happens.

Method, product, and system for maintaining an ensemble of hierarchical machine learning models for detection of security risks and breaches in a network

Disclosed is an improved approach for detecting potentially malicious activity on a network. The present improved approach generates a multi-dimensional activity model based on captured network activity. Additional network activity is captured, and relative activity values are determined therefor. Determination of whether the additional network activity corresponds to potentially malicious activity is obtained by fitting the relative activity values of the additional network activity to the multi-dimensional relative activity model.

Privileged account breach detections based on behavioral access patterns

Disclosed is an improved method, system, and computer program product for detecting hosts and connections between hosts that are being used as relays by an actor to gain control of hosts in a network. It can further identify periods of time within the connection when the relay activities occurred. In some embodiments, the invention can also chain successive relays to identify the true source and true target of the relay.

Malicious relay and jump-system detection using behavioral indicators of actors

Disclosed is an improved approach for identifying suspicious administrative host activity within a network. Network traffic is examined to learn the behavior of hosts within a network. This provides an effective way of determining whether or not a host is performing suspicious activity over an administrative protocol.

Method and system for detecting suspicious administrative activity

An approach for detecting network threats is disclosed, that may involve receiving network traffic, plotting the network traffic in a n-dimensional feature space to form a network map, generating a client signature at least by placing new client points in the map, setting a threshold, and generating an alarm if one or more client activity points exceed the threshold. In some embodiments, the network map and the client signature are updated using sliding windows and distance calculations.

Method and system for detecting threats using passive cluster mapping

A bot detection engine to determine whether hosts in an organization's network are performing bot-related activities is disclosed. A bot detection engine can receive network traffic between hosts in a network, and/or between hosts across several networks. The bot engine may parse the network traffic into session datasets and discard the session datasets that were not initiated by hosts in a given network. The session datasets may be analyzed and state data may be accumulated. The state data may correspond to actions performed by the hosts, such as requesting a website or clicking ads, or requesting content within the website (e.g. clicking on a image which forms a HTTP request/response transaction for the image file).

Method and system for detecting bot behavior

Disclosed is an improved approach to implement a system and method for detecting insider threats, where models are constructed that is capable of defining what constitutes the normal behavior for any given hosts and quickly find anomalous behaviors that could constitute a potential threat to an organization. The disclosed approach provides a way to identify abnormal data transfers within and external to an organization without the need for individual monitoring software on each host, by leveraging metadata that describe the data exchange patterns observed in the network.

System for detecting threats using scenario-based tracking of internal and external network traffic

An approach for detecting network attacks using metadata vectors may initially involve receiving network communications or packets, extracting metadata items from the packets. The metadata items describe the communications without requiring deep content inspection of the data payload or contents. The communications may be clustered into groups using the metadata items. If a cluster exceeds a threshold, an alarm may be generated.

Method and system for detecting threats using metadata vectors

A host identification engine receives network traffic from a network and uses one or more artifact extractors to extract artifact data items that can identify a host. The artifact data items can be stored in a host signature database. Network addresses to which the hosts correspond can be stored in a network address database. A mapping table can be implemented to match the data in the signature database and network database to generate durable host identification data that can accurately track hosts as they use different identification data and/or move between hosts.

Method and system for generating durable host identifiers using network artifacts

A system and method for detecting malicious relay communications is disclosed. Network communications can be received and analyzed using such network components as a network switch. The received traffic can be parsed into sessions. Relay metadata can be extracted from the sessions and further be used to categorize the sessions into one or more types of relay metadata behaviors. Once a significant amount of sessions are detected an alarm may be triggered and/or alarm data may be generated for analysis by network security administrators.

Growing community of inventors

Miami Beach, FL, United States of America

Nicolas Beauchesne