Cyber Risk Monte Carlo Simulation Patent for Financial Loss Characterization

ChangeBridge: Patent Grants - Networking (H04L)

Published March 31st, 2026

Detected March 31st, 2026

Summary

USPTO granted patent US12591753B2 to Zscaler, Inc. on March 31, 2026. The patent covers systems and methods for analyzing cybersecurity monitoring data to determine financial risk using Monte Carlo simulation to characterize potential losses from cyber events. The simulation inputs are based on the organization's industry, size, and current cyber risk posture.

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What changed

USPTO granted patent US12591753B2 to Zscaler, Inc. for methods of determining financial risk based on cybersecurity data. The patent covers obtaining cybersecurity monitoring data from multiple sources including user monitoring; determining current cyber risk posture; and performing Monte Carlo simulation trials using inputs based on industry, organization size, and cyber risk posture to generate a risk distribution curve plotting losses versus probability.

This is a patent grant notice, not a regulatory requirement. No compliance actions are required from regulated entities. Organizations with cybersecurity risk management programs may reference this patent methodology for internal risk quantification purposes.

Source document (simplified)

← USPTO Patent Grants

Determining financial risk based on cybersecurity data for remediation thereof

Grant US12591753B2 Kind: B2 Mar 31, 2026

Assignee

Zscaler, Inc.

Inventors

Michael Turek, Lisa Raymond-Smith, Shanghao Chen, Karthikeyan Thamilarasu, Shriyash Shete, Florian Vogt, Shawn Poh Wei Jian, Gary Symes

Abstract

Systems and methods for analyzing cybersecurity data to determine financial risk include obtaining cybersecurity monitoring data for an organization where the cybersecurity monitoring data is from a plurality of sources including from cybersecurity monitoring of a plurality of users associated with the organization; determining a current cyber risk posture of the organization based on the cybersecurity monitoring data; determining inputs for a Monte Carlo simulation to characterize financial losses of the organization due to a cyber event in a predetermined time period based on (1) an associated industry of the organization, (2) a size of the organization, and (3) the current cyber risk posture of the organization; performing a plurality of trials of the Monte Carlo simulation utilizing the inputs; and displaying a risk distribution curve based on results of the plurality of trials where the risk distribution curve plots a curve of losses versus a probability.