System and method of protecting client computers

1. A method for threat detection and response, the method comprising:

receiving, by a threat response computer, an event report from a threat detector which monitors and analyzes communications between a client computer in an enterprise computing network and a plurality of computers, wherein the threat response computer is separate from the client computer and runs on a threat response platform configured for protecting the enterprise computing network, and wherein the event report includes data identifying a suspicious communication by the client computer as a security event;

in response to the receiving of the event report by the threat response computer, temporarily, automatically, and remotely placing and activating, by the threat response computer, an agent on the client computer, the agent configured to search for potential indications of compromise (IOCs) on the client computer and self-uninstall after sending search result data to the threat response computer;

determining, by the threat response computer, whether the potential IOCs on the client computer indicate evidence of malware on the client computer in the enterprise computing network by:

comparing the potential IOCs on the client computer in the enterprise computing network and IOCs in a database local to the threat response computer, and

using a result of the comparison of the potential IOCs on the client computer in the enterprise computing network with the IOCs in the database local to the threat response computer, determining a probability of an actual malware incursion on the client computer; and

responsive to a result of the determining whether the potential IOCs on the client computer indicate evidence of malware on the client computer comprising a determination that the potential IOCs on the client computer indicate the evidence of malware on the client computer in the enterprise computing network, performing, by the threat response computer, one or more of:

updating the database local to the threat response computer to include the evidence of malware determined by the threat response computer, or

sending an instruction from the threat response computer to configure a firewall in the enterprise computing network.

2. The method according to claim 1 , wherein determining, by the threat response computer, whether the potential IOCs on the client computer indicate evidence of malware on the client computer further comprises:

determining a number of matches between the potential IOCs on the client computer and the IOCs in the database;

presenting the number of matches to a user through a user interface; and

receiving an indication from the user on whether the number of matches is sufficient to indicate evidence of malware on the client computer.

3. The method according to claim 2 , further comprising:

training or tuning a machine learning system of the threat response computer using training data that include the indication from the user.

4. The method according to claim 1 , wherein determining, by the threat response computer, whether the potential IOCs on the client computer indicate evidence of malware on the client computer further comprises:

determining a number of matches between the potential IOCs on the client computer and the IOCs in the database;

determining the probability of an actual malware incursion on the client computer utilizing the number of matches; and

determining whether the probability determined by the threat response computer meets or exceeds a threshold probability.

5. The method according to claim 4 , wherein the threshold probability is set by a user of the threat response computer, a central authority, a network based service, or a machine learning system of the threat response computer, the machine learning system trained on training data that include previous determinations by at least the user of the threat response computer or the central authority.

6. The method according to claim 1 , further comprising:

responsive to the database being updated to include the evidence of malware determined by the threat response computer, re-evaluating, by the threat response computer, previously received event reports from computers in the enterprise computing network.

7. The method according to claim 1 , further comprising:

responsive to the IOCs in the database being re-weighted, re-evaluating, by the threat response computer, previously received event reports from computers in the enterprise computing network.

8. The method according to claim 1 , wherein temporarily, automatically, and remotely placing comprises automatically remotely placing, by the threat response computer, a data collector on the client computer in response to receiving the event report.

9. The method according to claim 8 , wherein the automatically remotely placing is performed by the threat response computer periodically, in response to the event report from the threat detector, or by an explicit command.

10. The method according to claim 1 , wherein the plurality of computers comprise computers outside the enterprise computing network, inside the enterprise computing network, or a combination thereof.

11. A system for threat detection and response, the system comprising:

a processor; and

a non-transitory computer-readable medium storing instructions translatable by the processor for:

receiving, by a threat response computer, an event report from a threat detector which monitors and analyzes communications between a client computer in an enterprise computing network and a plurality of computers, wherein the threat response computer is separate from the client computer and runs on a threat response platform configured for protecting the enterprise computing network, and wherein the event report includes data identifying a suspicious communication by the client computer as a security event;

in response to the receiving of the event report by the threat response computer, temporarily, automatically, and remotely placing and activating, by the threat response computer, an agent on the client computer, the agent configured to search for potential indications of compromise (IOCs) on the client computer and self-uninstall after sending search result data to the threat response computer;

determining, by the threat response computer, whether the potential IOCs on the client computer indicate evidence of malware on the client computer in the enterprise computing network by:

comparing the received potential IOCs on the client computer in the enterprise computing network and IOCs in a database local to the threat response computer, and

using a result of the comparison of the potential IOCs on the client computer in the enterprise computing network with the IOCs in the database local to the threat response computer, determining a probability of an actual malware incursion on the client computer; and

responsive to a result of the determining whether the potential IOCs on the client computer indicate evidence of malware on the client computer comprising a determination that the potential IOCs on the client computer indicate the evidence of malware on the client computer in the enterprise computing network, performing, by the threat response computer, one or more of:

updating the database local to the threat response computer to include the evidence of malware determined by the system, or

sending an instruction from the threat response computer to configure a firewall in the enterprise computing network.

12. The system of claim 11 , wherein determining whether the potential IOCs on the client computer indicate evidence of malware on the client computer further comprises:

determining a number of matches between the potential IOCs on the client computer and the IOCs in the database;

presenting the number of matches to a user through a user interface; and

receiving an indication from the user on whether the number of matches is sufficient to indicate evidence of malware on the client computer.

13. The system of claim 12 , wherein the instructions are further translatable by the processor for:

training or tuning a machine learning component of the system using training data that include the indication from the user.

14. The system of claim 11 , wherein determining whether the potential IOCs on the client computer indicate evidence of malware on the client computer further comprises:

determining a number of matches between the potential IOCs on the client computer and the IOCs in the database;

determining the probability of an actual malware incursion on the client computer utilizing the number of matches; and

determining whether the probability determined by the system meets or exceeds a threshold probability.

15. The system of claim 14 , wherein the threshold probability is set by a user of the system, a central authority, a network based service, or a machine learning component of the system, the machine learning component trained on training data that include previous determinations by at least the user of the system or the central authority.

16. The system of claim 11 , wherein the instructions are further translatable by the processor for:

responsive to the database being updated to include the evidence of malware determined by the system, re-evaluating previously received event reports from computers in the enterprise computing network.

17. The system of claim 11 , wherein the instructions are further translatable by the processor for:

responsive to the IOCs in the database being re-weighted, re-evaluating previously received event reports from computers in the enterprise computing network.

18. The system of claim 11 , wherein the instructions are further translatable by the processor for:

automatically remotely placing a data collector on the client computer in response to receiving the event report.

19. The system of claim 18 , wherein the automatically remotely placing is performed periodically, in response to the event report from the threat detector, or by an explicit command.

20. The system of claim 11 , wherein the plurality of computers comprise computers outside the enterprise computing network, inside the enterprise computing network, or a combination thereof.