Forescout Technologies, Inc.

Systems, methods, and related technologies for determining a comprehensive risk score or value are described. The risk score determination may include selecting an entity communicatively coupled to a network and determining a cyber-attack likelihood value and a cyber-attack impact value associated with the entity. A cyber-attack risk may then be determined based on the cyber-attack likelihood value and a cyber-attack impact value associated with the entity. An operational failure likelihood value and an operational failure impact value associated with the entity can be determined. An operational failure risk based on the operational failure likelihood value and the operational failure impact value associated with the entity can be determined. A risk value may then be determined for the entity based on the cyber-attack risk and the operational failure risk and the risk value for the entity can be stored.

Systems, methods, and related technologies for device classification are described. In certain aspects, traffic data associated with a device and data from an external system can be accessed. The data can be processed to determine a device classification for the device. An action can be initiated based on the classification.

Systems, methods, and related technologies for classification are described. Network traffic from a network may be accessed and an entity may be selected. One or more values associated with one or more properties associated with the entity may be determined. The one or more values may be accessed from the network traffic. A search query based on the one or more values associated with the one or more properties associated with the entity is determined and performed. A search query result is received and the search query result comprises a plurality of webpages. Data from a webpage of the plurality webpages is accessed. A classification result of the entity is determined, by a processing device, based on the data from the webpage of the plurality of webpages. The classification result is stored.

An intrusion detection method for detecting an intrusion in data traffic on a data communication network parses the data traffic to extract at least one protocol field of a protocol message of the data traffic, and associates the extracted protocol field with a model for that protocol field. The model is selected from a set of models. An assessment is made to determine if a contents of the extracted protocol field is in a safe region as defined by the model, and an intrusion detection signal is generated in case it is established that the contents of the extracted protocol field is outside the safe region. The set of models may comprise a corresponding model for each protocol field of a set of protocol fields.

Disclosed is a method of transparently detecting authentication status of endpoint devices in a network. This method may be used for differentiating guest or rogue endpoints from enterprise endpoints.

Systems, methods, and related technologies for improving classification use multiple classification resources. Network traffic from a network may be accessed and an entity may be selected. One or more values associated with one or more properties associated with the entity may be determined. The one or more values may be accessed from the network traffic. A first classification result of the entity based on accessing one or more local profiles is determined by a processing device. In response to the first classification result meeting a condition, one or more values associated with one or more properties associated with the entity may be sent (e.g., to a cloud based classification resource). A second classification result may be received. The second classification result may be determined based one accessing at least one remote profile. At least one of the first classification result or the second classification result may be stored.

A method, apparatus and product for sub-networks based cyber security. One method comprises detecting a device connecting to a local network which is divided into subnets; determining a usage profile of the device; automatically selecting a subnet to connect the device based on the usage profile; and connecting the device to the selected subnet in the local network. Another method comprises monitoring communication traffic of devices in each of the subnets of a local network; performing anomaly detection to detect an abnormal communication of a device connected to a subnet; blocking the abnormal communication of the device; and removing the device from the subnet and connecting the device to a quarantine subnet of the local network, whereby reducing connectivity of the device with other devices connected to the local network.

Systems, methods, and related technologies for account access monitoring are described. In certain aspects, a login request associated with a device can be analyzed and a score determined. The score and a threshold can be used to determine whether to initiate an action.

An intrusion detection method for detecting an intrusion in data traffic on a data communication network parses the data traffic to extract at least one protocol field of a protocol message of the data traffic, and associates the extracted protocol field with a model for that protocol field. The model is selected from a set of models. An assessment is made to determine if a contents of the extracted protocol field is in a safe region as defined by the model, and an intrusion detection signal is generated in case it is established that the contents of the extracted protocol field is outside the safe region. The set of models may comprise a corresponding model for each protocol field of a set of protocol fields.

A method, apparatus and product for sub-networks based cyber security. One method comprises detecting a device connecting to a local network which is divided into subnets; determining a usage profile of the device; automatically selecting a subnet to connect the device based on the usage profile; and connecting the device to the selected subnet in the local network. Another method comprises monitoring communication traffic of devices in each of the subnets of a local network; performing anomaly detection to detect an abnormal communication of a device connected to a subnet; blocking the abnormal communication of the device; and removing the device from the subnet and connecting the device to a quarantine subnet of the local network, whereby reducing connectivity of the device with other devices connected to the local network.