Detecting threats to datacenter based on analysis of anomalous events
Some embodiments provide a method for detecting a threat to a datacenter. The method receives a set of connections between a set of DCNs in the datacenter over a particular time period. The set of DCNs includes at least a first DCN at which a first anomalous event was detected. The method analyzes a set of detected anomalous events to identify additional anomalous events detected at other DCNs in the set of DCNs during the particular time period. Based on the first anomalous event and identified additional anomalous events, the method determines whether the anomalous events indicate a threat to the datacenter.
1. A method for detecting a threat to a datacenter, the method comprising:
receiving a set of connections between a set of DCNs in the datacenter over a particular time period, the set of DCNs including at least a first DCN at which a first anomalous event was detected;
analyzing a set of detected anomalous events to identify additional anomalous events detected at other DCNs in the set of DCNs during the particular time period; and
based on the first anomalous event and identified additional anomalous events, determining whether the anomalous events indicate a threat to the datacenter using at least a graph of a time-constrained set of remote service connections.
2. The method of claim 1 , wherein the threat is a lateral movement threat in which an attacker accesses an initial DCN and moves between the DCNs of the set of DCNs in the datacenter.
3. The method of claim 2 , wherein the attacker uses remote service connections to move between the DCNs, wherein the set of connections comprises remote service connections.
4. The method of claim 1 , wherein determining whether the anomalous events indicate a threat to the datacenter comprises determining whether the first anomalous event is related to the additional anomalous events.
5. The method of claim 1 , wherein determining whether the anomalous events indicate a threat to the datacenter comprises analyzing previous data to determine whether connections similar to the connections between the set of DCNs have occurred previously.
6. The method of claim 1 , wherein determining whether the anomalous events indicate a threat to the datacenter comprises determining whether any of the events is of a particular type often occurring during a lateral movement threat.
7. The method of claim 1 further comprising generating an alert for presentation to a network administrator when the anomalous events indicate a threat to the datacenter.
8. The method of claim 1 further comprising:
automatically generating a set of firewall rules when the anomalous events indicate a threat to the datacenter; and
configuring a plurality of network elements in the datacenter to implement the automatically generated firewall rules.
9. The method of claim 1 , wherein the method is performed by a threat detector of an analysis appliance that receives and analyzes a plurality of flow attribute sets from a plurality of host computers in the datacenter.
10. The method of claim 9 , wherein the set of detected anomalous events comprises a plurality of different types of anomalous events detected by a plurality of different detectors of the analysis appliance.
11. The method of claim 9 , wherein the analysis appliance also receives contextual attribute sets from the host computers and maps the contextual attribute sets to the flow attribute sets, wherein a plurality of different detectors also use the contextual attribute sets to detect the anomalous events.
12. A non-transitory machine-readable medium storing a program which when executed by at least one processing unit detects a threat to a datacenter, the program comprising sets of instructions for:
receiving a set of connections between a set of DCNs in the datacenter over a particular time period, the set of DCNs including at least a first DCN at which a first anomalous event was detected;
analyzing a set of detected anomalous events to identify additional anomalous events detected at other DCNs in the set of DCNs during the particular time period; and
based on the first anomalous event and identified additional anomalous events, determining whether the anomalous events indicate a threat to the datacenter using at least a graph of a time-constrained set of remote service connections.
13. The non-transitory machine-readable medium of claim 12 , wherein the threat is a lateral movement threat in which an attacker accesses an initial DCN and uses remote service connections to move between the DCNs of the set of DCNs in the datacenter, wherein the set of connections comprises remote service connections.
14. The non-transitory machine-readable medium of claim 12 , wherein the set of instructions for determining whether the anomalous events indicate a threat to the datacenter comprises a set of instructions for determining whether the first anomalous event is related to the additional anomalous events.
15. The non-transitory machine-readable medium of claim 12 , wherein the set of instructions for determining whether the anomalous events indicate a threat to the datacenter comprises a set of instructions for analyzing previous data to determine whether connections similar to the connections between the set of DCNs have occurred previously.
16. The non-transitory machine-readable medium of claim 12 , wherein the set of instructions for determining whether the anomalous events indicate a threat to the datacenter comprises a set of instructions for determining whether any of the events is of a particular type often occurring during a lateral movement threat.
17. The non-transitory machine-readable medium of claim 12 , wherein the program further comprises a set of instructions for generating an alert for presentation to a network administrator when the anomalous events indicate a threat to the datacenter.
18. The non-transitory machine-readable medium of claim 12 , wherein the program further comprises sets of instructions for:
automatically generating a set of firewall rules when the anomalous events indicate a threat to the datacenter; and
configuring a plurality of network elements in the datacenter to implement the automatically generated firewall rules.
19. The non-transitory machine-readable medium of claim 12 , wherein:
the program is a threat detector module of an analysis appliance that receives and analyzes a plurality of flow attribute sets from a plurality of host computers in the datacenter; and
the set of detected anomalous events comprises a plurality of different types of anomalous events detected by a plurality of different detectors of the analysis appliance.
20. An electronic device comprising:
a set of processing units; and
a non-transitory machine-readable medium storing a program which when executed by at least one processing unit detects a threat to a datacenter, the program comprising sets of instructions for:
receiving a set of connections between a set of DCNs in the datacenter over a p articular time period, the set of DCNs including at least a first DCN at which a first anomalous event was detected;
analyzing a set of detected anomalous events to identify additional anomalous events detected at other DCNs in the set of DCNs during the p articular time period; and
based on the first anomalous event and identified additional anomalous events, determining whether the anomalous events indicate a threat to the datacenter using at least a graph of a time-constrained set of remote service connections.