Abstract: Systems, methods, and computer-readable media for annotating process and user information for network flows. In some embodiments, a capturing agent, executing on a first device in a network, can monitor a network flow associated with the first device. The first device can be, for example, a virtual machine, a hypervisor, a server, or a network device. Next, the capturing agent can generate a control flow based on the network flow. The control flow may include metadata that describes the network flow. The capturing agent can then determine which process executing on the first device is associated with the network flow and label the control flow with this information. Finally, the capturing agent can transmit the labeled control flow to a second device, such as a collector, in the network.

Abstract: Systems, methods, and computer-readable media for updating configurations in sensors deployed in multi-layer virtualized environments. In some examples, a system can track information of sensors and collectors in the network. In response to determining that a specific collector becomes unavailable (e.g., the specific collector is down, offline or becomes unsupported), the system can determine affected sensors corresponding to the specific collector, determine a new collector among active collectors of the network for each of the affected sensors, and dynamically update configuration and settings of the affected sensors to maintain proper collector-to-sensor mappings and other settings on the affected sensors.

Abstract: Systems, methods, and computer-readable media for annotating process and user information for network flows. In some embodiments, a capturing agent, executing on a first device in a network, can monitor a network flow associated with the first device. The first device can be, for example, a virtual machine, a hypervisor, a server, or a network device. Next, the capturing agent can generate a control flow based on the network flow. The control flow may include metadata that describes the network flow. The capturing agent can then determine which process executing on the first device is associated with the network flow and label the control flow with this information. Finally, the capturing agent can transmit the labeled control flow to a second device, such as a collector, in the network.

Abstract: Systems, methods, and computer-readable media for annotating process and user information for network flows. In some embodiments, a capturing agent, executing on a first device in a network, can monitor a network flow associated with the first device. The first device can be, for example, a virtual machine, a hypervisor, a server, or a network device. Next, the capturing agent can generate a control flow based on the network flow. The control flow may include metadata that describes the network flow. The capturing agent can then determine which process executing on the first device is associated with the network flow and label the control flow with this information. Finally, the capturing agent can transmit the labeled control flow to a second device, such as a collector, in the network.

Abstract: A monitoring device/module monitors a plurality of nodes in a data center network, and determines one or more latency distributions of response times for messages exchanged between pairs of nodes of the plurality of nodes. The network monitoring device determines a network topology, including one or more communication links interconnecting nodes of the plurality of nodes, consistent with the one or more latency distributions. The network monitoring device also determines a representative response time for each communication link based on the one or more latency distributions, and compares a current response time a message exchanged between one pair of nodes to the representative response time for the communication link interconnecting the one pair of nodes. The network monitoring device identifies a network anomaly when the current response time deviates from the representative response time for the communication link interconnecting the one pair of nodes by a threshold amount.

Abstract: Systems, methods, and computer-readable media are provided for generating a unique ID for a sensor in a network. Once the sensor is installed on a component of the network, the sensor can send attributes of the sensor to a control server of the network. The attributes of the sensor can include at least one unique identifier of the sensor or the host component of the sensor. The control server can determine a hash value using a one-way hash function and a secret key, send the hash value to the sensor, and designate the hash value as a sensor ID of the sensor. In response to receiving the sensor ID, the sensor can incorporate the sensor ID in subsequent communication messages. Other components of the network can verify the validity of the sensor using a hash of the at least one unique identifier of the sensor and the secret key.

Abstract: The technology visualizes data flows within a datacenter in an interactive hierarchical network chord diagram. Based on analyzed data describing data flows, a portion of the data flows that originate at the same first endpoint and terminate at the same second endpoint can be grouped. Subsequently, the dataflow monitoring system displays an interactive hierarchical network chord diagram to include a chord with a first endpoint and a second endpoint. The chord represents the grouped portion of data flows that originate at the same first endpoint and terminate at the same second endpoint. Upon receiving a selection of the chord or the first endpoint of the chord, the dataflow monitoring system expands the grouped portion of the data flows into a more granular representation of the network.

Abstract: An approach for detecting anomalous flows in a network using header field entropy. This can be useful in detecting anomalous or malicious traffic that may attempt to “hide” or inject itself into legitimate flows. A malicious endpoint might attempt to send a control message in underutilized header fields or might try to inject illegitimate data into a legitimate flow. These illegitimate flows will likely demonstrate header field entropy that is higher than legitimate flows. Detecting anomalous flows using header field entropy can help detect malicious endpoints.

Abstract: An example method includes detecting, using sensors, packets throughout a datacenter. The sensors can then send packet logs to various collectors which can then identify and summarize data flows in the datacenter. The collectors can then send flow logs to an analytics module which can identify the status of the datacenter and detect an attack.

Abstract: An approach for establishing a priority ranking for endpoints in a network. This can be useful when triaging endpoints after an endpoint becomes compromised. Ensuring that the most critical and vulnerable endpoints are triaged first can help maintain network stability and mitigate damage to endpoints in the network after an endpoint is compromised. The present technology involves determining a criticality ranking and a secondary value for a first endpoint in a datacenter. The criticality ranking and secondary value can be combined to form priority ranking for the first endpoint which can then be compared to a priority ranking for a second endpoint to determine if the first endpoint or the second endpoint should be triaged first.

Abstract: Systems, methods, and computer-readable media are provided for generating a unique ID for a sensor in a network. Once the sensor is installed on a component of the network, the sensor can send attributes of the sensor to a control server of the network. The attributes of the sensor can include at least one unique identifier of the sensor or the host component of the sensor. The control server can determine a hash value using a one-way hash function and a secret key, send the hash value to the sensor, and designate the hash value as a sensor ID of the sensor. In response to receiving the sensor ID, the sensor can incorporate the sensor ID in subsequent communication messages. Other components of the network can verify the validity of the sensor using a hash of the at least one unique identifier of the sensor and the secret key.

Abstract: An example method includes detecting, using sensors, packets throughout a datacenter. The sensors can then send packet logs to various collectors which can then identify and summarize data flows in the datacenter. The collectors can then send flow logs to an analytics module which can identify the status of the datacenter and detect an attack.

Abstract: An approach for establishing a priority ranking for endpoints in a network. This can be useful when triaging endpoints after an endpoint becomes compromised. Ensuring that the most critical and vulnerable endpoints are triaged first can help maintain network stability and mitigate damage to endpoints in the network after an endpoint is compromised. The present technology involves determining a criticality ranking and a secondary value for a first endpoint in a datacenter. The criticality ranking and secondary value can be combined to form priority ranking for the first endpoint which can then be compared to a priority ranking for a second endpoint to determine if the first endpoint or the second endpoint should be triaged first.

Abstract: An approach for detecting anomalous flows in a network using header field entropy. This can be useful in detecting anomalous or malicious traffic that may attempt to “hide” or inject itself into legitimate flows. A malicious endpoint might attempt to send a control message in underutilized header fields or might try to inject illegitimate data into a legitimate flow. These illegitimate flows will likely demonstrate header field entropy that is higher than legitimate flows. Detecting anomalous flows using header field entropy can help detect malicious endpoints.

Abstract: An example method can include monitoring a network to identify flows between nodes in the network. Once flows have been identified, the flows can be tagged and labelled according to the type of traffic they represent. If a flow represents malicious or otherwise undesirable traffic, it can be tagged accordingly. A request can then be made for a reputation score of an entity which can identify one or more nodes of the network.

Abstract: Systems, methods, and computer-readable media for managing compromised sensors in multi-tiered virtualized environments. In some embodiments, a system can receive, from a first capturing agent deployed in a virtualization layer of a first device, data reports generated based on traffic captured by the first capturing agent. The system can also receive, from a second capturing agent deployed in a hardware layer of a second device, data reports generated based on traffic captured by the second capturing agent. Based on the data reports, the system can determine characteristics of the traffic captured by the first capturing agent and the second capturing agent. The system can then compare the characteristics to determine a multi-layer difference in traffic characteristics. Based on the multi-layer difference in traffic characteristics, the system can determine that the first capturing agent or the second capturing agent is in a faulty state.

Abstract: Systems, methods, and computer-readable media for providing interoperability between nodes in separate networks as part of a federated network. In some embodiments, a system can identify a first cluster of nodes in a first network and a second cluster of nodes in a second network. The system can provide interoperability between the first cluster of nodes and the second cluster of nodes. First analytics for the first cluster of nodes can be generated using first network traffic data gathered based on first network traffic flowing through the first cluster of nodes by a group of sensors implemented in the first network. The second cluster of nodes can access the first analytics for the first cluster of nodes as part of providing the interoperability between the first cluster of nodes in the first network and the second cluster of nodes in the second network.

Abstract: Systems, methods, and computer-readable media for managing compromised sensors in multi-tiered virtualized environments. In some embodiments, a system can receive, from a first capturing agent deployed in a virtualization layer of a first device, data reports generated based on traffic captured by the first capturing agent. The system can also receive, from a second capturing agent deployed in a hardware layer of a second device, data reports generated based on traffic captured by the second capturing agent. Based on the data reports, the system can determine characteristics of the traffic captured by the first capturing agent and the second capturing agent. The system can then compare the characteristics to determine a multi-layer difference in traffic characteristics. Based on the multi-layer difference in traffic characteristics, the system can determine that the first capturing agent or the second capturing agent is in a faulty state.

Abstract: An example method can include monitoring a network to identify flows between nodes in the network. Once flows have been identified, the flows can be tagged and labelled according to the type of traffic they represent. If a flow represents malicious or otherwise undesirable traffic, it can be tagged accordingly. A request can then be made for a reputation score of an entity which can identify one or more nodes of the network.

Abstract: Systems, methods, and computer-readable media for annotating process and user information for network flows. In some embodiments, a capturing agent, executing on a first device in a network, can monitor a network flow associated with the first device. The first device can be, for example, a virtual machine, a hypervisor, a server, or a network device. Next, the capturing agent can generate a control flow based on the network flow. The control flow may include metadata that describes the network flow. The capturing agent can then determine which process executing on the first device is associated with the network flow and label the control flow with this information. Finally, the capturing agent can transmit the labeled control flow to a second device, such as a collector, in the network.