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:
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 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.
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:
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 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:
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 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:
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:
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.