Cyber recovery forensic kit—application-based granularity

Patent metadata

Field	Value
Publication number	US-12505214-B2
Application number	US-202218046622-A
Country	US
Kind code	B2
Filing date	Oct 14, 2022
Priority date	Oct 14, 2022
Publication date	Dec 23, 2025
Grant date	Dec 23, 2025

Abstract

A forensic kit with a granular infected backup. A forensic engine may evaluate a production system that is infected with malware or other corruption and generate a forensic kit. The forensic kit may include copies of components of the production system that are infected or that are sufficiently related to infected components. The forensic kit may be provided to investigators.

First claim

What is claimed is:

1 . A method comprising:
detecting malware in a production system that includes components; identifying infected components from among the components of the production system; identifying related components of the production system from among the components of the production system that are related to the infected components, wherein the related components may be infected with the malware; and generating a granular infected backup that includes only the infected components and the related components and the malware, and not components of the production system that are both not infected components and not related components.

2 . The method of claim 1 , further comprising triggering a forensic operation upon detecting the malware, wherein the forensic operation is configured to generate the granular infected backup.

3 . The method of claim 1 , wherein the granular infected backup comprises a snapshot of the infected components and the related components.

4 . The method of claim 1 , wherein the components include servers, applications, data, storage devices, storage systems, active directory, networking, or combinations thereof.

5 . The method of claim 1 , further comprising identifying the infected components using a first model that is trained to detect the malware or other corruptions in the components.

6 . The method of claim 5 , further comprising generating a graph representing the components of the production system.

7 . The method of claim 6 , further comprising identifying the infected components in the graph.

8 . The method of claim 7 , further comprising inputting the graph that identifies the infected components into a second model trained to identify the related components to the infected components.

9 . The method of claim 8 , further comprising including the granular infected component in a forensic kit.

10 . The method of claim 9 , further comprising performing a forensic analysis based on the forensic kit and wherein the related components include attack vectors of the malware that do not appear to be infected.

11 . A non-transitory storage medium having stored therein instructions that are executable by one or more hardware processors to perform operations comprising:
detecting malware in a production system that includes components; identifying infected components from among the components of the production system; identifying related components of the production system from among the components of the production system that are related to the infected components, wherein the related components may be infected with the malware; and generating a granular infected backup that includes only the infected components and the related components and the malware, and not components of the production system that are both not infected components and not related components.

12 . The non-transitory storage medium of claim 11 , further comprising triggering a forensic operation upon detecting the malware, wherein the forensic operation is configured to generate the granular infected backup.

13 . The non-transitory storage medium of claim 11 , wherein the granular infected backup comprises a snapshot of the infected components and the related components.

14 . The non-transitory storage medium of claim 11 , wherein the components include servers, applications, data, storage devices, storage systems, active directory, networking, or combinations thereof.

15 . The non-transitory storage medium of claim 11 , further comprising identifying the infected components using a first model that is trained to detect the malware or other corruptions in the components.

16 . The non-transitory storage medium of claim 15 , further comprising generating a graph representing the components of the production system.

17 . The non-transitory storage medium of claim 16 , further comprising identifying the infected components in the graph.

18 . The non-transitory storage medium of claim 17 , further comprising inputting the graph that identifies the infected components into a second model trained to identify the related components to the infected components.

19 . The non-transitory storage medium of claim 18 , further comprising including the granular infected component in a forensic kit.

20 . The non-transitory storage medium of claim 19 , further comprising performing a forensic analysis based on the forensic kit and wherein the related components include attack vectors of the malware that do not appear to be infected.

Assignees

• Dell Products Lp

Inventors

• Ezrielev Ofir
• Shemer Jehuda
• Savir Amihai

Classifications

• G06F2221/033

  Test or assess software · CPC title

• G06F21/568

  eliminating virus, restoring damaged files · CPC title

• G06F21/566 Primary

  Dynamic detection, i.e. detection performed at run-time, e.g. emulation, suspicious activities · CPC title