The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Apr. 07, 2026

Filed:

Oct. 04, 2024
Applicant:

Netskope, Inc., Santa Clara, CA (US);

Inventors:

Xinjun Zhang, San Jose, CA (US);

Zhenxin Zhan, Fremont, CA (US);

Ghanashyam Satpathy, Bangalore, IN;

Hung-Ming Chen, Kaohsiung, TW;

Dong Guo, San Jose, CA (US);

Assignee:

Netskope, Inc., Santa Clara, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 21/56 (2013.01); G06F 21/53 (2013.01); G06F 21/64 (2013.01);
U.S. Cl.
CPC ...
G06F 21/565 (2013.01); G06F 21/53 (2013.01); G06F 21/64 (2013.01);
Abstract

A cloud-based network security system (NSS) is described. The NSS uses a sandbox to safely open and extract information about a PDF file and uses machine learning algorithms to analyze the information to predict whether the PDF file contains malware. Specifically, dynamic information about the PDF file is captured while it is open in the sandbox. Static information is extracted from the PDF file as well. The dynamic and static information is input to an AI or machine learning model trained to provide an output indicating a prediction of whether the PDF file contains malware. A verdict engine uses the output from the AI or machine learning model to classify the document as malicious or clean. Security policies can then be applied based on the classification.


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