Network threat prediction and blocking
A firewall monitors network activity and stores information about that network activity in a network activity log. The network activity is analyzed to identify a potential threat. The potential threat is further analyzed to identify other potential threats that are related to the potential threat, and are likely to pose a future risk to a protected network. A block list is updated to include the potential threat and the other potential threats to protect the protected network from the potential threat and the other potential threats.
1. A method of predicting network threats, the method comprising:
identifying a threat vector from network activity log data using one or more computing devices;
determining, based at least upon relationship data for the threat vector, a first online object having a first type and a second online object having a second type different from the first type, wherein the relationship data identifies a first association between the threat vector and the first online object and a second association between the threat vector and the second online object;
identifying the first online object as a predictive network threat based at least upon the first association between the threat vector and the first online object; and
providing data regarding the threat vector as an identified network threat and the first online object as the predictive network threat to a firewall device using the one or more computing devices, wherein the firewall device blocks network activity associated with the threat vector as the identified network threat and the first online object as the predictive network threat.
2. The method of claim 1 , wherein the first type and the second type are one of: an internet protocol address, a file, a uniform resource locator, and a software application.
3. The method of claim 1 , wherein identifying the threat vector from the network activity log data comprises:
receiving network activity log event data including at least one network event;
sending a request to a reputation management system; and
receiving a response from the reputation management system indicating whether the network event is a threat.
4. The method of claim 3 , wherein the response from the reputation management system contains the results of an investigation conducted by the reputation management system to evaluate whether the network event is a threat.
5. The method of claim 1 , wherein determining the first online object comprises:
sending a request to a relationship management system, the request identifying the threat vector; and
receiving a response from the relationship management system identifying the first online object.
6. The method of claim 5 , further comprising determining a third online object having a third type, wherein the relationship data identifies a third association between the first online object and the third online object.
7. The method of claim 6 , wherein determining the third online object comprises:
sending a subsequent request to the relationship management system, the subsequent request identifying the first online object; and
receiving a response from the relationship management system identifying the third online object.
8. The method of claim 6 , wherein the third online object has no more than three degrees of separation from the threat vector.
9. The method of claim 1 , further comprising adding the threat vector and the first online object to a block list of the firewall device, and operating the firewall device to block network traffic associated with the block list.
10. A computing system comprising:
at least one processing device; and
at least one computer readable storage device storing data instructions that, when executed by the at least one processing device, cause the at least one processing device to:
identify an online element associated with network activity;
determine that the online element is associated with a malicious reputation as an identified threat;
determine, based at least upon relationship data for the online element, a first online object having a first type and a second online object having a second type different from the first type, wherein the relationship data identifies a first association between a threat vector and the first online object and a second association between a threat vector and the second online object;
identify the first online object as a predictive threat based at least upon the first association between the online element and the first online object; and
sending data describing the online element as an identified threat and the first online object as the predictive threat to a firewall so that the firewall can block network activity associated with the online element and the first online object.
11. The computing system of claim 10 , wherein the first type and the second type are one of: an internet protocol address, a file, a uniform resource locator, and a software application.
12. The computing system of claim 10 , wherein determining that the online element is associated with the malicious reputation comprises:
receiving the network activity including at least one network event;
sending a request to a reputation management system; and
receiving a response from the reputation management system indicating whether the network event is a threat.
13. The computing system of claim 12 , wherein the response from the reputation management system contains the results of an investigation conducted by the reputation management system to evaluate whether the network event is a threat.
14. The computing system of claim 10 , wherein determining the first online object comprises:
sending a request to a relationship management system, the request identifying the online element; and
receiving a response from the relationship management system identifying the first online object.
15. The computing system of claim 10 , wherein the computer readable storage device storing data instructions that, when executed by the at least one processing device, cause the at least one processing device to:
determine a third online object having a third type, wherein the relationship data identifies a third association between the first online object and the third online object.
16. The computing system of claim 15 , wherein determining the third online object comprises:
sending a subsequent request to the relationship management system, the subsequent request identifying the third online object; and
receiving a response from the relationship management system identifying the third online object.
17. The computing system of claim 15 , wherein the third online object has no more than three degrees of separation from the online element.
18. A method of predicting network threats, the method comprising:
receiving at a computing device a request including an identifier associated with an online element;
determining that the online element has a malicious reputation based on a comparison between the identifier associated with the online element and data in a reputation database;
sending by the computing device a response indicating that the online element has the malicious reputation as an identified network threat;
receiving at the computing device a request for known relationships to the online element;
searching a relationship database to identify a first online object and a second online object that also have the malicious reputation, using the computing device, the first online object having a first type and the second online object having a second type different from the first type, wherein there is a first association between the first online object and the online element and a second association between a second online object and the online element; and
sending from the computing device one or more identifiers for the first online object and the second online object as predictive network threats.
19. The method of claim 18 , wherein the first association and the second association are each no more than three degrees of separation from the online element.
20. A method of predicting network threats, the method comprising:
identifying a predictive threat based on network activity data, the predictive threat comprising an element;
identifying other predictive threats related to the predictive threat by determining a first relationship between the element and a first online object and a second relationship between the element and a second online object, the first online object having a first type and the second online object having a second type different from the first type; and
providing an update to a block list to a firewall device, wherein the update is configured to cause-the firewall device to add the predictive threat and the other predictive threats to the block list to protect a protected network from the predicted threat and the other predicted threats.