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:
Sep. 09, 2025

Filed:

Oct. 31, 2024
Applicant:

Centripetal Networks, Llc, Portsmouth, NH (US);

Inventors:

David K. Ahn, Winston-Salem, NC (US);

Jess P. Parnell, Grayson, GA (US);

Tyler J. Wendell, Holly Springs, NC (US);

Hansaka A. Kodituwakku, Falls Church, VA (US);

Jared Holmberg, Lake Dallas, TX (US);

Daniel Rogers, Ashburn, VA (US);

Cody Michael Baker, Round Hill, VA (US);

Pierre Mallett, Iii, Herndon, VA (US);

Assignee:

Centripetal Networks, LLC, Portsmouth, NH (US);

Attorney:
Int. Cl.
CPC ...
H04L 9/40 (2022.01);
U.S. Cl.
CPC ...
H04L 63/0263 (2013.01); H04L 63/1416 (2013.01); H04L 63/1425 (2013.01);
Abstract

Aspects described herein may relate to cyber threat detection based on threat context and/or threat changes. Cyber threat intelligence (CTI) data may be received from a CTI provider. Endpoint data that indicates evidence that endpoints are cyber threats may be determined based on the CTI data. The endpoint data may be analyzed and/or compared to stored data associated with the endpoint. The analysis and/or comparison may be performed to determine whether evidence that the endpoint is a cyber threat has changed. Based on any changes, dispositions for the endpoint may be determined and sent. The dispositions may change how devices filter network traffic associated with the endpoint. Alternatives to default dispositions may be determined based on a impact of blocking potentially legitimate network traffic to and/or from the endpoints. Machine-learning models may assist in processing and analyzing CTI data, performing threat monitoring, and/or determining feeds that include the dispositions.


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