View source for Code42 Software, Inc. (20250016192). SYSTEM FOR MANAGING SECURITY RISKS WITH GENERATIVE ARTIFICIAL INTELLIGENCE

=SYSTEM FOR MANAGING SECURITY RISKS WITH GENERATIVE ARTIFICIAL INTELLIGENCE=


==Organization Name==

[[:Category:Code42 Software, Inc.|Code42 Software, Inc.]]


[[Category:Code42 Software, Inc.]]

==Inventor(s)==

[[:Category:Christopher Michael Montgomery of Blaine MN (US)|Christopher Michael Montgomery of Blaine MN (US)]][[Category:Christopher Michael Montgomery of Blaine MN (US)]]

[[:Category:Peter John Lindquist of St. Paul MN (US)|Peter John Lindquist of St. Paul MN (US)]][[Category:Peter John Lindquist of St. Paul MN (US)]]

[[:Category:Thomas Anthony Lindquist of Minnetonka MN (US)|Thomas Anthony Lindquist of Minnetonka MN (US)]][[Category:Thomas Anthony Lindquist of Minnetonka MN (US)]]

[[:Category:Andrew Moravec of Hugo MN (US)|Andrew Moravec of Hugo MN (US)]][[Category:Andrew Moravec of Hugo MN (US)]]

[[:Category:Robert Juncker of Lakeville MN (US)|Robert Juncker of Lakeville MN (US)]][[Category:Robert Juncker of Lakeville MN (US)]]

==SYSTEM FOR MANAGING SECURITY RISKS WITH GENERATIVE ARTIFICIAL INTELLIGENCE==


This abstract first appeared for US patent application 20250016192 titled 'SYSTEM FOR MANAGING SECURITY RISKS WITH GENERATIVE ARTIFICIAL INTELLIGENCE




==Original Abstract Submitted==

a system and method to use generative artificial intelligence to detect potential exfiltration events. a system for exfiltration analysis is configured to receive a plurality of file identifiers of a corresponding plurality of files, the plurality of files related to exfiltration alerts; store information about the plurality of files in a forensic file data store, the forensic file data store used to provide contextual information for a large language model (llm); receive an exfiltration query from a user of the system; and produce a generative output using the llm based on the exfiltration query and the contextual information.



[[Category:H04L9/40]]
[[Category:CPC_H04L63/1433]]