System, method, and computer program for a computer attack response service
As described herein, a system, method, and computer program provide a computer attack response service. In use, a notification is received that a transfer of at least one electronic file to a computing device has been detected as a potential incoming threat to the computing device. Responsive to the receiving the notification, at least one honeypot is created. Additionally, data within the at least one electronic file is accessed, using the at least one honeypot. Responsive to accessing the data within the at least one electronic file, activity associated with the incoming threat is monitored.
1. A non-transitory computer-readable media storing computer instructions which when executed by one or more processors of a device cause the device to:
receive a notification that a transfer of at least one electronic file to a computing device has been detected as a potential incoming threat to the computing device;
responsive to the receiving the notification, create at least one honeypot;
simulate user activity within the at least one honeypot, wherein a state of the at least one honeypot is updated based on the simulated user activity and wherein the state includes a timestamp indicating a last user activity simulated on the honeypot;
access data within the at least one electronic file, using the at least one honeypot;
responsive to accessing the data within the at least one electronic file, monitor activity occurring within the at least one honeypot as a result of accessing the data within the at least one electronic file; and
process the activity occurring within the at least one honeypot as a result of accessing the data within the at least one electronic file, using a machine learning model, to classify the potential incoming threat as one of expected behavior or unexpected behavior.
2. The non-transitory computer-readable media of claim 1 , wherein the potential incoming threat is detected using at least one of a firewall or antivirus software.
3. The non-transitory computer-readable media of claim 1 , wherein the potential incoming threat is detected by the computing device.
4. The non-transitory computer-readable media of claim 1 , wherein the potential incoming threat is detected by a local network to which the computing device is connected.
5. The non-transitory computer-readable media of claim 1 , wherein the at least one electronic file is transferred as an attachment to an electronic mail message.
6. The non-transitory computer-readable media of claim 1 , wherein the at least one honeypot is at least one virtual machine.
7. The non-transitory computer-readable media of claim 1 , wherein the at least one honeypot is connected to a sandbox simulating a computing system.
8. The non-transitory computer-readable media of claim 1 , wherein the at least one honeypot includes the machine learning model.
9. The non-transitory computer-readable media of claim 1 , wherein when the machine learning model classifies the potential incoming threat as the expected behavior, then further comprising:
release the at least one honeypot.
10. The non-transitory computer-readable media of claim 1 , wherein when the machine learning model classifies the potential incoming threat as the unexpected behavior, then further comprising:
storing the activity occurring within the at least one honeypot as a result of accessing the data within the at least one electronic file in a data structure.
11. The non-transitory computer-readable media of claim 10 , wherein when the machine learning model classifies the potential incoming threat as the unexpected behavior, then further comprising:
issuing an alert to a security team.
12. The non-transitory computer-readable media of claim 11 , wherein the alert is issued based on an analysis of the activity occurring within the at least one honeypot as a result of accessing the data within the at least one electronic file with historical information stored in the data structure.
13. The non-transitory computer-readable media of claim 1 , wherein the user activity that is simulated within the at least one honeypot includes one or more of:
a login process,
creating files, or
deleting files.
14. The non-transitory computer-readable media of claim 1 , wherein the user activity is simulated to keep the at least one honeypot in a live state.
15. The non-transitory computer-readable media of claim 1 , wherein the user activity is simulated according to a profile of a user associated with the computing device.
16. The non-transitory computer-readable media of claim 1 , wherein the activity occurring within the at least one honeypot that is monitored includes at least one of:
events,
executed functions, or
data accesses.
17. A method, comprising:
at a computer system:
receiving a notification that a transfer of at least one electronic file to a computing device has been detected as a potential incoming threat to the computing device;
responsive to the receiving the notification, creating at least one honeypot;
simulating user activity within the at least one honeypot, wherein a state of the at least one honeypot is updated based on the simulated user activity and wherein the state includes a timestamp indicating a last user activity simulated on the honeypot;
accessing data within the at least one electronic file, using the at least one honeypot;
responsive to accessing the data within the at least one electronic file, monitoring activity occurring within the at least one honeypot as a result of accessing the data within the at least one electronic file; and
processing the activity occurring within the at least one honeypot as a result of accessing the data within the at least one electronic file, using a machine learning model, to classify the potential incoming threat as one of expected behavior or unexpected behavior.
18. A system, comprising:
a non-transitory memory storing instructions; and
one or more processors in communication with the non-transitory memory that execute the instructions to:
receive a notification that a transfer of at least one electronic file to a computing device has been detected as a potential incoming threat to the computing device;
responsive to the receiving the notification, create at least one honeypot;
simulate user activity within the at least one honeypot, wherein a state of the at least one honeypot is updated based on the simulated user activity and wherein the state includes a timestamp indicating a last user activity simulated on the honeypot;
access data within the at least one electronic file, using the at least one honeypot;
responsive to accessing the data within the at least one electronic file, monitor activity occurring within the at least one honeypot as a result of accessing the data within the at least one electronic file; and
process the activity occurring within the at least one honeypot as a result of accessing the data within the at least one electronic file, using a machine learning model, to classify the potential incoming threat as one of expected behavior or unexpected behavior.
19. The system of claim 18 , wherein the one or more processors are located on at least one of: a server in a cloud, a local network to which the computing device is connected, or the computing device.