Endpoint detection and response system event characterization data transfer

Patent metadata

Field	Value
Publication number	US-10944761-B2
Application number	US-201815961685-A
Country	US
Kind code	B2
Filing date	Apr 24, 2018
Priority date	Apr 26, 2017
Publication date	Mar 9, 2021
Grant date	Mar 9, 2021

Abstract

An endpoint computer system monitors data relating to a plurality of events occurring within an operating environment of the endpoint computer system. The monitoring can include receiving and/or inferring the data using one or more sensors executing on the endpoint computer system. The endpoint computer system can store artifacts used in connection with the plurality of events in a vault maintained on such endpoint computer system. The endpoint computer system, in response to a trigger, identifies and retrieves metadata characterizing artifacts associated with the trigger from the vault. Such identified and retrieved metadata is then provided by the endpoint computer system to a remote server.

First claim

The invention claimed is:

1. A computer-implemented method comprising:
monitoring, by an endpoint computer system, data relating to a plurality of events occurring within an operating environment of the endpoint computer system, the monitoring comprising receiving and/or inferring the data using one or more sensors executing on the endpoint computer system;
storing, for the endpoint computer system, artifacts used in connection with the plurality of events in a tamper resistant, self-contained vault maintained on such endpoint computer system;
identifying and retrieving, by the endpoint computer system in response to a trigger, metadata characterizing artifacts associated with the trigger from the vault; and providing, by the endpoint computer system, the identified and retrieved metadata to a remote server;
wherein the storing of the artifacts in the vault further comprises determining, based on one or more criteria, to retain in the vault a first subset of the artifacts associated with a software-based attack and to exclude from the vault a second subset of the data not associated with a software-based attack.

2. The method of claim 1 , wherein the trigger occurs after expiration of a timer.

3. The method of claim 1 , wherein the trigger occurs after expiration of a pre-determined amount of time.

4. The method of claim 1 , wherein the trigger occurs in response to a determination, on the endpoint computer system, that a file or object comprises malicious software.

5. The method of claim 1 , wherein the trigger occurs in response to receipt of a query originating from a remote computing system.

6. The method of claim 5 further comprising: mitigating an amount of provided identified and retrieved metadata by interpreting the query at the endpoint computer system and focusing on specific data of results that are most likely to be relevant to a subject of the query.

7. The method of claim 1 further comprising: providing, by the endpoint computer system to a remote server, at least a portion of the artifacts and/or events associated with the trigger from the vault.

8. The method of claim 1 further comprising: redacting, by the endpoint computer system, at least a portion of the identified metadata prior to it being provided to the remote server.

9. The method of claim 8 , wherein the redacted identified metadata comprises at least one of: a usernames, IP addresses, filenames, process command lines, URLs, registry key, registry name, registry content, process names, or DNS information.

10. The method of claim 1 , wherein the identified metadata is provided in a space-efficient data structure.

11. The method of claim 10 , wherein the space-efficient data structure is a Bloom filter, HyperLogLog data structure, a Count-Min Sketch, a MinHash data structure, or a T-Digest data structure.

12. The method of claim 1 , wherein the artifacts are a digital item of interest comprising one or more of a file, a program, network connections, registry keys and values, DNS connections, user agent strings, URLs, drivers, services, users, or a system characteristic.

13. The method of claim 1 , wherein the monitoring further comprises receiving and/or inferring at least some of the data using additional data generated external to the endpoint computer system and received by the endpoint computer system by way of a communication interface over a communication network.

14. The method of claim 1 , wherein the events comprise actions occurring on the endpoint computer system and involving one or more of the artifacts on the endpoint computer system and/or wherein the events cornprise a capture of what occurred at a specific point in time relating to at least one artifact.

15. The method of claim 1 , wherein the provided identified and retrieved metadata comprise one or more of one or more times that a particular tile was accessed on the corresponding endpoint computer system, how the particular file was used on the corresponding endpoint computer system, when the particular the was first detected on the corresponding endpoint computer system, location of a registry persistence point, and use of a registry by a software routine to avow itself to persist after a reboot of the corresponding endpoint computing system, registry keys being used for malware persistence to survive reboots, files being created or modified with content that can be directly executed or interpreted for execution, files being downloaded that contain executable or interpretable code, processes being created with excessive or unexpected permissions, users with excessive permissions or users obtaining permissions through non-standard mechanisms, network connections that are used in non-standard ways, network connections that are used in ways that exhibit malicious command and control activities, network connections that are used to exfiltrate files that contain sensitive information, network connections that connect to IP addresses that are considered suspect due to geo-location or reputation, processes that exhibit control over or inject code into other processes, and/or processes that change user ownership during execution.

16. The method of claim 1 , wherein the monitoring of data is performed by one or more sensors that comprise at least one of a kernel mode collector, a removable media sensor, a sensor that collects data about a current state of a computing environment executing on the endpoint computer, a malware detection and/or interdiction process, a user authentication process, or a user authentication re-verification process.

17. The method of claim 1 further comprising: monitoring the data according to a first set of data collection criteria; determining, based on the monitoring that a heightened level of alert is necessary; and in response to the determined heightened level of alert, monitoring the data according to a second set of data collection criteria which cause a greater amount of data to be monitored than according to the first set of data collection criteria.

18. The method of claim 17 , wherein the determining uses a machine learning component.

19. The method of claim 18 , wherein the machine learning component performs at least one operation selected from determining that the heightened level of alert is necessary, blocking or terminating execution of a process or thread, and determining that the alert level can be lowered back to the first set of data collection criteria.

20. The method of claim 19 , wherein the machine learning component accomplishes the at least one operation by processing data already in the vault to determine that a potentially undesirable event has occurred and/or by processing the monitored data as it is received to determine that a potentially undesirable event is currently occurring.

21. The method of claim 1 further comprising: pruning, for each endpoint system, data within the vault meeting pre-determined deletion criteria.

22. The method of claim 21 , wherein the pre-determined deletion criteria is based on a timestamp or time associated with such data or a size of files or objects within such data.

23. A computer-implemented method comprising:
monitoring, by an endpoint computer system, data relating to a plurality of events occurring within an operating environment of the endpoint computer system, the monitoring comprising (a) receiving and/or inferring the data using one or more sensors executing on the endpoint computer system and (b) receiving and/or inferring at least

Assignees

• Cylance Inc

Inventors

• Strong Homer Valentine
• Permeh Ryan
• Oswald Samuel John

Classifications

• G06F21/552

  involving long-term monitoring or reporting · CPC title

• H04L63/1433

  Vulnerability analysis · CPC title

• H04L63/20

  for managing network security; network security policies in general (filtering policies H04L63/0227) · CPC title

• G06F21/554

  involving event detection and direct action · CPC title

• G06N5/046

  Forward inferencing; Production systems · CPC title