Forensic analysis of computing activity

• US 9,967,267 B2
• Filed: 04/15/2016
• Issued: 05/08/2018
• Est. Priority Date: 04/15/2016
• Status: Active Grant

• Current Assignee: Sophos Limited (Sophos Group Ltd.)
• Original Assignee: Sophos Limited (Sophos Group Ltd.)
• Inventors: Ladnai, Beata, Harris, Mark David, Thomas, Andrew J., Smith, Andrew G. P., Humphries, Russell, Ray, Kenneth D.
• Primary Examiner(s): Smithers, Matthew
• Application Number:
  US15/130,244
• Publication Number:
  US 20170302685A1
• Time in Patent Office: 753 Days
• CPC Class Codes: G06F 16/9024 Graphs; Linked lists G06F16/9027 takes precedence
• CPC Class Codes: G06Q 10/063 Operations research, analysis or management
• CPC Class Codes: G06Q 50/26 Government or public services business processes related to the transportation industry G06Q50/40
• CPC Class Codes: H04L 63/1416 Event detection, e.g. attack signature detection
• CPC Class Codes: H04L 63/1425 Traffic logging, e.g. anomaly detection
• CPC Class Codes: H04L 63/1433 Vulnerability analysis
• CPC Class Codes: H04L 63/145 the attack involving the propagation of malware through the network, e.g. viruses, trojans or worms
• CPC Class Codes: H04L 63/20 for managing network security; network security policies in general filtering policies H04L63/0227

Abstract

A data recorder stores endpoint activity on an ongoing basis as sequences of events that causally relate computer objects such as processes and files. When a security event is detected, an event graph may be generated based on these causal relationships among the computing objects. For a root cause analysis, the event graph may be traversed in a reverse order from the point of an identified security event (e.g., a malware detection event) to preceding computing objects, while applying one or more cause identification rules to identify a root cause of the security event. Once a root cause is identified, the event graph may be traversed forward from the root cause to identify other computing objects that are potentially compromised by the root cause.

Claims

1. A computer program product for forensic analysis for computer processes, the computer program product comprising computer executable code embodied in a non-transitory computer readable medium that, when executing on a computing device, performs the steps of:

instrumenting a first endpoint to monitor a number of causal relationships among a number of computing objects, and to record a sequence of events causally relating the number of computing objects;

detecting a security event associated with one of the number of computing objects, wherein detecting the security event includes detecting a potential data leakage;

in response to detecting the security event, traversing an event graph based on the sequence of events in a reverse order from the one of the number of computing objects associated with the security event to one or more preceding ones of the number of computing objects;

applying a cause identification rule to the one or more preceding ones of the number of computing objects and the number of causal relationships while traversing the event graph to identify one of the number of computing objects as a cause of the security event; and

traversing the event graph forward from the cause of the security event to identify one or more other ones of the number of computing objects affected by the cause.

2. The computer program product of claim 1, wherein the computer executable code further performs the steps of taking an action to remediate one or more of the identified computing objects.

3. A method for forensic analysis for computer processes, the method comprising:

instrumenting a first endpoint to monitor a number of causal relationships among a number of computing objects, and to record a sequence of events causally relating the number of computing objects;

detecting a security event associated with one of the number of computing objects, wherein detecting the security event includes detecting a potential data leakage;

in response to detecting the security event, traversing an event graph based on the sequence of events in a reverse order from the one of the number of computing objects associated with the security event to one or more preceding ones of the number of computing objects;

applying a cause identification rule to the one or more preceding ones of the number of computing objects and the number of causal relationships while traversing the event graph to identify one of the number of computing objects as a cause of the security event;

traversing the event graph forward from the cause of the security event to identify one or more other ones of the number of computing objects affected by the cause; and

taking an action to remediate one or more of the identified computing objects.

4. The method of claim 3 wherein the number of causal relationships include one or more of a data flow, a control flow, and a network flow.

5. The method of claim 3 wherein detecting the security event includes detecting a security compromise by applying static analysis to software objects on the first endpoint.

6. The method of claim 3 wherein detecting the security event includes detecting a security compromise by applying behavioral analysis to code executing on the first endpoint.

7. The method of claim 3 wherein detecting the security event includes detecting a hardware change.

8. The method of claim 3 wherein the one or more computing objects include one or more types of computing objects selected from a group consisting of a data file, a process, an application, a registry entry, a network address, and a peripheral device.

9. The method of claim 3 wherein the one or more computing objects include one or more network addresses, the one or more network addresses including at least one of a uniform resource locator (URL), an internet protocol (IP) address, and a domain name.

10. The method of claim 3 wherein the one or more computing objects include one or more peripheral devices, the one or more peripheral devices including at least one of a universal serial bus (USB) memory, a camera, a printer, and a keyboard.

11. The method of claim 3 wherein a number of events within the sequence of events are preserved for a predetermined time window, and further wherein the predetermined time window has a different duration for at least two types of computing objects.

12. The method of claim 3 wherein the one or more computing objects include at least one computing object on a device other than the first endpoint.

13. The method of claim 12 wherein the device includes at least one of a second endpoint and a server.

14. The method of claim 3 wherein the cause identification rule associates the cause with one or more common malware entry points.

15. The method of claim 14 wherein the one or more common malware entry points includes at least one of a word processing application, an electronic mail application, a spreadsheet application, a browser, and a universal serial bus (USB) drive.

16. The method of claim 3 wherein the cause identification rule associates the cause with a combination of a first process invoking a second process and then providing data to the second process.

17. The method of claim 16 wherein the first process invoking the second process includes at least one of a spawning, a hijacking, and a remote launch over a network.

18. The method of claim 16 wherein providing data to the second process includes creating a file for use by the second process.

19. The method of claim 3 further comprising generating the event graph.

20. The method of claim 3, wherein the action to remediate further comprises displaying the identified computing objects to a user.

21. The method of claim 3, where the action to remediate further comprises deleting one or more of the identified computing objects.

22. A system for forensic analysis for computer processes comprising:

a first endpoint;

a data recorder instrumented to monitor a number of causal relationships among a number of computing objects on the first endpoint, and to record a sequence of events causally relating the number of computing objects; and

a processor and a memory disposed on the first endpoint or in communication with the first endpoint, the memory bearing computer code that, when executing on the processor, performs the steps of;

detecting a security event associated with one of the number of computing objects on the first endpoint, wherein detecting the security event includes detecting a potential data leakage;

in response to detecting the security event, traversing an event graph based on the sequence of events in a reverse order from the one of the number of computing objects associated with the security event to one or more preceding ones of the number of computing objects;

applying a cause identification rule to the one or more preceding ones of the number of computing objects and the number of causal relationships while traversing the event graph to identify one of the number of computing objects as a cause of the security event;

traversing the event graph forward from the cause of the security event to identify one or more other ones of the number of computing objects affected by the cause;

examining the identified computing objects affected by the cause; and

remediating compromised examined computing objects.