IP Library › Granted Patent US 12,273,412
Granted Patent B2
US 12,273,412 · App. 18/479,573 · Granted Apr 8, 2025

System and method for analyzing network objects in a cloud environment

Inventors: Shai Keren (Tel Aviv, IL); Daniel Hershko Shemesh (Givat Shmuel, IL); Roy Reznik (Tel Aviv, IL); Ami Luttwak (Binyamina, IL); Avihai Berkovitz (Tel Aviv, IL)
Assignee: Wiz, Inc.
H04L67/10H04L41/046H04L41/5096H04L49/70H04L63/1433
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,273,412
App. No.
18/479,573
Granted
Apr 8, 2025
Kind
B2
Abstract

A method and system for providing textual insights on objects deployed in a cloud environment are provided. The method includes collecting object data on objects deployed in the cloud environment, wherein objects are deployed and operable at different layers of the cloud environment; identifying objects deployed in the cloud environment; constructing a visual representation of the cloud environment, including the identified objects and their relationships; and generating textual insights on the identified objects and their relationships using natural language processing.

Claims (55)

1. A method for filtering network insights from vulnerable network objects having cyber-threats, comprising:

collecting object data on objects deployed in a cloud environment, wherein objects are deployed and operable at different layers of the cloud environment;

identifying objects deployed in the cloud environment;

constructing a representation of the cloud environment, including the identified objects and relationships of the identified objects;

generating network insights on the identified objects and the relationships of the identified objects, wherein network insights are natural-language representations of aspects of the constructed representation of the cloud environment;

tagging the identified objects in the representation for which the insight was generated; and

filtering the network insights based on an insight indicating exposure from an external network.

2. The method of claim 1 , further comprising:

generating an alert based on the network insight.

3. The method of claim 2 , further comprising:

filtering the alert based on the insight indicating exposure of the external network.

4. The method of claim 1 , further comprising:

generating a network graph from the representation of the cloud environment.

5. The method of claim 4 , wherein the network graph includes any one of: a table, a chart, a non-visual data format, a list of objects, and any combination thereof.

6. The method of claim 1 , further comprising:

detecting an anomaly based on the generated network insights.

7. The method of claim 6 , further comprising:

generating an alert based on the detected anomaly.

8. The method of claim 1 , further comprising:

determining that a network object is vulnerable to a cyber-threat based on the insight indicating exposure from an external network.

9. The method of claim 8 , further comprising:

filtering the network insights further based on an insight indicating a cyber-threat vulnerability.

10. A non-transitory computer-readable medium storing a set of instructions for filtering network insights from vulnerable network objects having cyber-threats, the set of instructions comprising:

one or more instructions that, when executed by one or more processors of a device, cause the device to:

collect object data on objects deployed in a cloud environment, wherein objects are deployed and operable at different layers of the cloud environment;

identify objects deployed in the cloud environment;

construct a representation of the cloud environment, including the identified objects and relationships of the identified objects;

generate network insights on the identified objects and the relationships of the identified objects, wherein network insights are natural-language representations of aspects of the constructed representation of the cloud environment;

tag the identified objects in the representation for which the insight was generated; and

filter the network insights based on an insight indicating exposure from an external network.

11. A system for filtering network insights from vulnerable network objects having cyber-threats comprising:

a processing circuitry; and

a memory, the memory containing instructions that, when executed by the processing circuitry, configure the system to:

collect object data on objects deployed in a cloud environment, wherein objects are deployed and operable at different layers of the cloud environment;

identify objects deployed in the cloud environment;

construct a representation of the cloud environment, including the identified objects and relationships of the identified objects;

generate network insights on the identified objects and the relationships of the identified objects, wherein network insights are natural-language representations of aspects of the constructed representation of the cloud environment;

tag the identified objects in the representation for which the insight was generated; and

filter the network insights based on an insight indicating exposure from an external network.

12. The system of claim 11 , wherein the memory contains further instructions which when executed by the processing circuitry further configure the system to:

generate an alert based on the network insight.

13. The system of claim 12 , wherein the memory contains further instructions which when executed by the processing circuitry further configure the system to:

filter the alert based on the insight indicating exposure of the external network.

14. The system of claim 11 , wherein the memory contains further instructions which when executed by the processing circuitry further configure the system to:

generate a network graph from the representation of the cloud environment.

15. The system of claim 14 , wherein the network graph includes any one of:

a table, a chart, a non-visual data format, a list of objects, and any combination thereof.

16. The system of claim 11 , wherein the memory contains further instructions which when executed by the processing circuitry further configure the system to:

detect an anomaly based on the generated network insights.

17. The system of claim 16 , wherein the memory contains further instructions which when executed by the processing circuitry further configure the system to:

generate an alert based on the detected anomaly.

18. The system of claim 11 , wherein the memory contains further instructions which when executed by the processing circuitry further configure the system to:

determine that a network object is vulnerable to a cyber-threat based on the insight indicating exposure from an external network.

19. The system of claim 18 , wherein the memory contains further instructions which when executed by the processing circuitry further configure the system to:

filter the network insights further based on an insight indicating a cyber-threat vulnerability.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 12, 2024
From: KEREN, SHAI; SHEMESH, DANIEL HERSHKO; REZNIK, ROY; LUTTWAK, AMI; BERKOVITZ, AVIHAI
To: WIZ, INC.
Reel/Frame 066736/0031 →
Continuity (5)
Continuation 18478534 · Sep 29, 2023
Continuation 18341134 · Jun 26, 2023
Continuation 17819442 · Aug 12, 2022
Continuation 17109883 · Dec 2, 2020
Related Publication 20240146799A1 · May 2, 2024
References Cited (21)
US 7392539B2 · Brooks · 2008 [cited by examiner]
US 9210185B1 · Pinney Wood · 2015 [cited by examiner]
US 10171300B2 · Eggen · 2019 [cited by examiner]
US 10924347B1 · Narsian · 2021 [cited by examiner]
US 10977587B2 · Khalili · 2021 [cited by examiner]
US 11709944B2 · Salji · 2023 [cited by examiner]
US 20040019803A1 · Jahn · 2004 [cited by applicant]
US 20140157417A1 · Grubel · 2014 [cited by examiner]
US 20160044057A1 · Chenette et al. · 2016 [cited by applicant]
US 20160048556A1 · Kelly · 2016 [cited by examiner]
US 20160359872A1 · Yadav · 2016 [cited by examiner]
US 20160373944A1 · Jain · 2016 [cited by examiner]
US 20170075981A1 · Carlsson · 2017 [cited by examiner]
US 20180024981A1 · Xia · 2018 [cited by examiner]
US 20190095530A1 · Booker · 2019 [cited by examiner]
US 20200252461A1 · Xu · 2020 [cited by examiner]
US 20200267175A1 · Atighetchi et al. · 2020 [cited by applicant]
US 20200322227A1 · Janakiraman · 2020 [cited by examiner]
US 20200374343A1 · Novotny · 2020 [cited by examiner]
US 20200382539A1 · Janakiraman · 2020 [cited by examiner]
US 20230008765A1 · Kazato · 2023 [cited by examiner]