Infrastructure Threat Change Analysis Using Automated Threat Models

The patent replaces manual security threat review processes with an automated system that uses threat models to automatically assess security impacts of infrastructure changes. The system automatically generates threat models, compares them against baseline threat models, and determines security implications without requiring manual analysis, thereby eliminating the bottleneck between security review and change implementation speed.

The patent changes the parameter of security review approach from manual to automated by introducing threat models as a measurable parameter. The system quantifies security impacts by comparing threat model parameters (such as threat likelihood, vulnerability exposure, and security control effectiveness) before and after proposed changes, enabling rapid automated assessment that scales with infrastructure complexity.

The patent segments the security analysis process into discrete components by creating threat models that break down infrastructure environments into manageable elements. Each threat model represents a specific infrastructure component or configuration state, allowing the system to analyze complex environments by combining results from simpler, modular threat model assessments rather than attempting to analyze the entire infrastructure at once.

The patent creates a virtual copy of the infrastructure environment's security state through threat models. Instead of manually analyzing the actual complex infrastructure, the system generates a simplified digital representation (threat model) that captures security-relevant characteristics. This copy can be rapidly manipulated, compared, and analyzed to identify security impacts without exposing analysts to the full complexity of the production environment.

The patent designs the automated threat model generation system to serve multiple functions: it generates threat models for infrastructure changes, compares threat models against baseline versions, identifies security impacts, and provides recommendations. This multi-functional approach consolidates what would otherwise require multiple separate systems into a single unified platform, reducing overall system complexity while maintaining high productivity.

The patent implements feedback mechanisms where the automated system learns from actual security incidents and infrastructure configurations to improve its threat model generation. The system incorporates feedback from security teams about false positives and missed threats, continuously refining its algorithms. This feedback loop reduces the complexity burden by automatically adapting to changing infrastructure patterns without requiring manual reconfiguration of the automated system.