Systems and methods for automated memory and thread execution anomaly detection in a computer network

1. A method for detecting an anomaly in a computer that is part of a population of networked computers, the method comprising:

receiving snapshots from a plurality of computers within the population of computers, wherein individual snapshots include a state of assets and runtime processes of a respective computer;

generating an asset normalization model from the snapshots that serves as a baseline model for detecting an anomaly in the state of assets and runtime processes of a respective computer, wherein detecting an anomaly comprises detecting a behavioral anomaly comprising one or more of changes in code, changes in execution stack and changes in thread execution; and

comparing a snapshot from at least one of the computers to the asset normalization model to determine whether an anomaly is present in a state of static assets and runtime processes of the at least one of the computers.

2. The method of claim 1 , further comprising deploying to the plurality of computers an agent that is configured for one or more of generating a snapshot, transmitting the snapshot, and detecting an anomaly using the asset normalization model.

3. The method of claim 1 , wherein the snapshots comprise code segments that have been encoded using a transform function.

4. The method of claim 3 , wherein the transform function includes a cryptographic hash.

5. The method of claim 1 , wherein changes in code include changes in a code segment, code injection, and code removal.

6. The method of claim 1 , wherein changes in the execution stack include improper code addresses inserted into the call stack.

7. The method of claim 1 , wherein changes in thread execution include improper thread creation, improper thread execution, and improper thread destruction.

8. The method of claim 1 , deriving a statistical model for normal process execution in order to detect changes in runtime process behavior that constitute a behavioral anomaly.

9. The method of claim 1 , further comprising:

searching the assets and runtime processes in order to find unique identifiers and related assets;

adding found unique identifiers to a list of previously found unique identifiers and related assets;

using the list to build a baseline of computer assets which contain these identifiers and related assets to scan during runtime operations in order to generate a snapshot; and

periodically updating the list of unique identifiers as assets and runtime processes are added and removed from a respective computer.

10. The method of claim 1 , further comprising, when an anomaly is detected:

repairing the asset or runtime process associated with the anomaly by removing the asset, replacing the asset, or stopping the runtime process; and

repairing any faults in the execution stack associated with the anomaly.

11. A system for detecting an anomaly in a computer that is part of a population of networked computers, comprising:

a network interface configured to receive snapshots from a plurality of computers within the population of computers, wherein individual snapshots include a state of assets and runtime processes of a respective computer; and

a processor configured to:

generate an asset normalization model from the snapshots that serves as a baseline model for detecting an anomaly in the state of assets and runtime processes of a respective computer, wherein detecting an anomaly comprises detecting a behavioral anomaly comprising one or more of changes in code, changes in execution stack and changes in thread execution; and

compare a snapshot from at least one of the computers to the asset normalization model to determine whether an anomaly is present in a state of static assets and runtime processes of at least one of the computers.

12. The system of claim 11 , wherein the processor is further configured to deploy to the plurality of computers an agent that is configured for one or more of generating a snapshot, transmitting the snapshot, and detecting an anomaly using the asset normalization model.

13. The system of claim 11 , wherein the network interface is configured to receive snapshots that comprise code segments that have been encoded using a transform function.

14. The system of claim 11 , wherein changes in code include changes in a code segment, code injection, and code removal.

15. The system of claim 11 , wherein changes in the execution stack include improper code addresses inserted into the call stack.

16. The system of claim 11 , wherein changes in thread execution include improper thread creation, improper thread execution, and improper thread destruction.

17. The system of claim 11 , wherein the processor is configured to derive a statistical model for normal process execution in order to detect changes in runtime process behavior that constitute a behavioral anomaly.

18. The system of claim 13 , wherein the transform function includes a cryptographic hash.

19. The system of claim 11 , wherein the processor is further configured to:

search the assets and runtime processes in order to find unique identifiers and related assets;

add found unique identifiers to a list of previously found unique identifiers and related assets;

use the list to build a baseline of computer assets which contain these identifiers and related assets to scan during runtime operations in order to generate a snapshot; and

periodically update the list of unique identifiers as assets and runtime processes are added and removed from a respective computer.

20. The system of claim 11 , wherein when an anomaly is detected, the processor is further configured to:

repair the asset or runtime process associated with the anomaly by removing the asset, replacing the asset, or stopping the runtime process; and

repair any faults in the execution stack associated with the anomaly.

21. One or more computer readable storage media storing instructions for detecting an anomaly in a computer that is part of a population of networked computers, the instructions, when executed by a processor, cause the processor to:

receive snapshots from a plurality of computers within the population of computers, wherein individual snapshots include a state of assets and runtime processes of a respective computer;

generate an asset normalization model from the snapshots that serves as a baseline model for detecting an anomaly in the state of assets and runtime processes of a respective computer, wherein detecting an anomaly comprises detecting a behavioral anomaly comprising one or more of changes in code, changes in execution stack and changes in thread execution; and

compare a snapshot from at least one of the computers to the asset normalization model to determine whether an anomaly is present in a state of static assets and runtime processes of the at least one of the computers.

22. The computer readable storage media of claim 21 , further comprising instructions that are operable to deploy to the plurality of computers an agent that is configured for one or more of generating a snapshot, transmitting the snapshot, and detecting an anomaly using the asset normalization model.

23. The computer readable storage media of claim 21 , wherein the instructions that are operable to receive comprise instructions that are operable to receive the snapshots that comprise code segments that have been encoded using a cryptographic hash.

24. The computer readable storage media of claim 21 , wherein changes in code include changes in a code segment, code injection, and code removal.

25. The computer readable storage media of claim 21 , wherein changes in the execution stack include improper code addresses inserted into the call stack.

26. The computer readable storage media of claim 21 , wherein changes in thread execution include improper thread creation, improper thread execution, and improper thread destruction.

27. The computer readable storage media of claim 21 , further comprising instructions that are operable to derive a statistical model for normal process execution in order to detect changes in runtime process behavior that constitute a behavioral anomaly.

28. The computer readable storage media of claim 21 , further comprising instructions that are operable to:

search the assets and runtime processes in order to find unique identifiers and related assets;

add found unique identifiers to a list of previously found unique identifiers and related assets;

use the list to build a baseline of computer assets which contain these identifiers and related assets to scan during runtime operations in order to generate a snapshot; and

periodically update the list of unique identifiers as assets and runtime processes are added and removed from a respective computer.

29. The computer readable storage media of claim 21 , wherein when an anomaly is detected, further comprising instructions that are operable to:

repair the asset or runtime process associated with the anomaly by removing the asset, replacing the asset, or stopping the runtime process; and

repair any faults in the execution stack associated with the anomaly.

30. A method for detecting an anomaly in a computer that is part of a population of networked computers, the method comprising:

searching the assets and runtime processes in order to find unique identifiers and related assets;

adding found unique identifiers to a list of previously found unique identifiers and related assets;

using the list to build a baseline of computer assets which contain these identifiers and related assets to scan during runtime operations in order to generate a snapshot;

periodically updating the list of unique identifiers as assets and runtime processes are added and removed from a respective computer;

receiving snapshots from a plurality of computers within the population of computers, wherein individual snapshots include a state of assets and runtime processes of a respective computer;

generating an asset normalization model from the snapshots that serves as a baseline model for detecting an anomaly in the state of assets and runtime processes of a respective computer; and

comparing a snapshot from at least one of the computers to the asset normalization model to determine whether an anomaly is present in a state of static assets and runtime processes of the at least one of the computers.

31. The method of claim 30 , further comprising, when an anomaly is detected:

repairing the asset or runtime process associated with the anomaly by removing the asset, replacing the asset, or stopping the runtime process; and

repairing any faults in the execution stack associated with the anomaly.

32. The method of claim 30 , deriving a statistical model for normal process execution in order to detect changes in runtime process behavior that constitute a behavioral anomaly.

33. The method of claim 30 , wherein the snapshots comprise code segments that have been encoded using a transform function.

34. A system for detecting an anomaly in a computer that is part of a population of networked computers, comprising:

a network interface configured to receive snapshots from a plurality of computers within the population of computers, wherein individual snapshots include a state of assets and runtime processes of a respective computer; and

a processor configured to:

search the assets and runtime processes in order to find unique identifiers and related assets;

add found unique identifiers to a list of previously found unique identifiers and related assets;

use the list to build a baseline of computer assets which contain these identifiers and related assets to scan during runtime operations in order to generate a snapshot;

periodically update the list of unique identifiers as assets and runtime processes are added and removed from a respective computer;

generate an asset normalization model from the snapshots that serves as a baseline model for detecting an anomaly in the state of assets and runtime processes of a respective computer; and

compare a snapshot from at least one of the computers to the asset normalization model to determine whether an anomaly is present in a state of static assets and runtime processes of at least one of the computers.

35. One or more computer readable storage media storing instructions for detecting an anomaly in a computer that is part of a population of networked computers, the instructions, when executed by a processor, cause the processor to:

search the assets and runtime processes in order to find unique identifiers and related assets;

add found unique identifiers to a list of previously found unique identifiers and related assets;

use the list to build a baseline of computer assets which contain these identifiers and related assets to scan during runtime operations in order to generate a snapshot; and

periodically update the list of unique identifiers as assets and runtime processes are added and removed from a respective computer;

receive snapshots from a plurality of computers within the population of computers, wherein individual snapshots include a state of assets and runtime processes of a respective computer;

generate an asset normalization model from the snapshots that serves as a baseline model for detecting an anomaly in the state of assets and runtime processes of a respective computer; and

compare a snapshot from at least one of the computers to the asset normalization model to determine whether an anomaly is present in a state of static assets and runtime processes of the at least one of the computers.