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: Systems, methods, and computer-readable media for detecting sensor deployment characteristics in a network. In some embodiments, a system can run a capturing agent deployed on a virtualization environment of the system. The capturing agent can query the virtualization environment for one or more environment parameters, and receive a response from the virtualized environment including the one or more environment parameters. Based on the one or more environment parameters, the capturing agent can determine whether the virtualization environment where the capturing agent is deployed is a hypervisor or a virtual machine. The capturing agent can also determine what type of software switch is running in the virtualized environment.

Abstract: Embodiments of a method and system are disclosed. One embodiment of a method for signaling an interrupt in an I2C system that includes a master I2C device and at least one slave I2C device that are connected by an SDA line and an SCL line is disclosed. The method involves, at the slave I2C device, pulling the SDA line low to signal an interrupt and at the slave I2C device, releasing the SDA line in response to either the SCL line having been pulled low or the expiration of a predetermined time period, whichever occurs first. In an embodiment, the predetermined time period is 1 ms.

Abstract: A virtualized computing system including software sensors captures network data from one or more traffic flows the sensors. The captured network data from a given sensor indicates one or more traffic flows detected by the given sensor. The received captured network data is analyzed to identify, for each respective sensor, a first group of sensors, a second group of sensors, and a third group of sensors. All traffic flows observed by the first group of sensors are also observed by the second group of sensors. All traffic flows observed by the second group of sensors are also observed by the third group of sensors. A location of each respective sensor relative to other sensors within the virtualized computing system is determined based upon whether the respective sensor belongs to the first group of sensors, the second group of sensors, or the third group of sensors.

Abstract: Methods, systems, and computer readable media are provided for determining, in a virtualized network system, a relationship of a sensor relative to other sensors. In a virtualized computing system in which a plurality of software sensors are deployed and in which there are one or more traffic flows, captured network data is received from the plurality of sensors, the captured network data from a given sensor of the plurality of sensors indicating one or more traffic flows detected by the given sensor. The received captured network data is analyzed to identify, for each respective sensor, a first group of sensors, a second group of sensors, and a third group of sensors, wherein all traffic flows observed by the first group of sensors are also observed by the second group of sensors, and all traffic flows observed by the second group of sensors are also observed by the third group of sensors.

Abstract: An example method can include receiving a traffic report from a sensor and using the traffic report to detect intra-datacenter flows. These intra-datacenter flows can then be compared with a description of historical flows. The description of historical flows can identify characteristics of normal and malicious flows. Based on the comparison, the flows can be classified and tagged as normal, malicious, or anomalous. If the flows are tagged as malicious or anomalous, corrective action can be taken with respect to the flows. A description of the flows can then be added to the description of historical flows.

Abstract: Managing a network environment to identify spoofed packets is disclosed. A method includes analyzing, via a first capture agent, packets processed by a first environment in a network associated with a first host, and analyzing, via a second capture agent, packets processed by a second environment in the network associated with a second host. The method includes collecting the first data and the second data at a collector and generating a topological map of the network and a history of network activity associated with the first environment and the second environment. The method includes extracting network data from a packet and comparing the extracted network data with stored network data in the database. When the comparison indicates that the extracted network data does not match the stored network data (i.e., the reported source does not match an expected source for the packet), determining that the packet is a spoofed packet.

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 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: A method includes analyzing, via a first capturing agent, packets processed in a first environment associated with a first host to yield first data. The method includes analyzing, via a second capturing agent, packets processed by a second environment associated with a second host to yield second data, collecting the first data and the second data at a collector to yield aggregated data, transmitting the aggregated data to an analysis engine which analyzes the aggregated data to yield an analysis. Based on the analysis, the method includes identifying first packet loss at the first environment and second packet loss at the second environment.

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 example method includes calculating latency bounds for communications from two sensors to a collector (i.e., maximum and minimum latencies). After the collector receives an event report from the first sensor and an event report form the second sensor, the collector can determine, using the latency bounds, whether one event likely preceded the other.

Abstract: A method includes capturing first data associated with a first packet flow originating from a first host using a first capture agent deployed at the first host to yield first flow data, capturing second data associated with a second packet flow originating from the first host from a second capture agent deployed on a second host to yield second flow data and comparing the first flow data and the second flow data to yield a difference. When the difference is above a threshold value, the method includes determining that the second packet flow was transmitted by a component that bypassed an operating stack of the first host or a packet capture agent at the device to yield a determination, detecting that hidden network traffic exists, and predicting a malware issue with the first host based on the determination.

Abstract: Systems, methods, and computer-readable media are provided for de-duplicating sensed data packets in a network. As data packets of a particular network flow move through the network, the data packets can be sensed and reported by various sensors across the network. An optimal sensor of the network can be determined based upon data packets reported by the various sensors. Data packets sensed and reported by the optimal sensor can be preserved for network analysis. Duplicative data packets of the particular network flow sensed and reported by other sensors of the network can be discarded to save storage capacity and processing power of network-flow analysis tools. Analysis of the particular network flow can be performed based upon the data packets sensed by the optimal sensor and non-duplicative data packets of the particular network-flow sensed by other sensors of 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: A method includes capturing first data associated with a first packet flow originating from a first host using a first capture agent deployed at the first host to yield first flow data, capturing second data associated with a second packet flow originating from the first host from a second capture agent deployed outside of the first host to yield second flow data and comparing the first flow data and the second flow data to yield a difference. When the difference is above a threshold value, the method includes determining that a hidden process exists and corrective action can be taken.

Abstract: Systems, methods, and computer-readable media for detecting sensor deployment characteristics in a network. In some embodiments, a system can run a capturing agent deployed on a virtualization environment of the system. The capturing agent can query the virtualization environment for one or more environment parameters, and receive a response from the virtualized environment including the one or more environment parameters. Based on the one or more environment parameters, the capturing agent can determine whether the virtualization environment where the capturing agent is deployed is a hypervisor or a virtual machine. The capturing agent can also determine what type of software switch is running in the virtualized environment.

Abstract: Systems, methods, and non-transitory computer-readable storage media for synchronizing timestamps of a sensor report to the clock of a device. In one embodiment, the device receives a report from a sensor of a node. The report can include a network activity of the node captured by the sensor and a first timestamp relative to the clock of the node. The device can then determine a second timestamp relative to the clock of the collector indicating receipt of the report by the device and from the sensor at the node. The device can also determine a delta between the first timestamp and the second timestamp, and a communication latency associated with a communication channel between the device and the sensor. Next, the device can adjust the delta based on the communication latency, and generate a third timestamp based on the adjusted delta.

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 managing compromised sensors in multi-tiered virtualized environments. A method includes determining a lineage for a process within the network and then evaluating, through knowledge of the lineage, the source of the command that initiated the process. The method includes capturing data from a plurality of capture agents at different layers of a network, each capture agent of the plurality of capture agents configured to observe network activity at a particular location in the network, developing, based on the data, a lineage for a process associated with the network activity and, based on the lineage, identifying an anomaly within the network.