API Endpoint Discovery and Normalization for Cloud Security Analytics

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Solution Overview

Problem

Traditional methods of collecting application data for security analytics in cloud-based environments are inefficient, error-prone, and complex due to manual effort, diverse cloud configurations, unique identifiers, and proprietary data formats, which hinder the integration of standard security testing tools and increase the risk of vulnerabilities.

Innovation Solution

An automated system that collects, transforms, and standardizes application data across cloud services using an endpoint discovery module, identifier resolution, and OpenAPI generation, enabling unified security analysis and proactive vulnerability detection.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual methods are used to collect and document each endpoint, then data accuracy can be maintained through human review, but the process becomes exponentially more complex and time-consuming with cloud scale

Engineering Contradiction:
Improvedata accuracyVSAvoidtime to collect endpoints
Core Design Contradiction:
Measurement precisionVSLoss of time

Solution Approach 1:

The patent replaces manual mechanical processes of endpoint identification and documentation with automated computational systems. The automated endpoint identification system uses machine learning models and APIs to systematically discover, collect, and document endpoints across cloud environments, eliminating the need for manual human review while maintaining data accuracy through algorithmic validation and consistency checks.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

2Reliability

If proprietary APS data formats are used, then data security and control are improved, but integration with standard security testing tools becomes difficult

Engineering Contradiction:
Improvedata securityVSAvoidtool integration capability
Core Design Contradiction:
ReliabilityVSAdaptability or versatility

Solution Approach 1:

The patent introduces an intermediary layer that sits between the proprietary APS data format and standard security testing tools. This intermediary component translates and adapts APS data formats into compatible formats for standard tools while maintaining security controls, enabling both data security and tool integration compatibility simultaneously through format conversion and protocol adaptation.

Inventive Principle:
Principle #24Intermediary (Mediator)

3Reliability

If unique identifiers are used for each cloud instance, then instance-specific security requirements are met, but automated testing and configuration transfer between instances become problematic

Engineering Contradiction:
Improveinstance-specific securityVSAvoidautomated testing capability
Core Design Contradiction:
ReliabilityVSExtent of automation

Solution Approach 1:

The patent applies parameter changes by dynamically adjusting identifier handling based on the operational context. The system uses unique identifiers for instance-specific security operations while implementing abstraction layers and parameter substitution techniques that allow automated testing and configuration transfer. The system can switch between using unique instance identifiers and generic placeholder identifiers depending on whether the operation requires instance-specific security or automated portability.

Inventive Principle:
Principle #35Parameter changes

4Reliability

If comprehensive endpoint documentation is created manually, then complete security coverage is achieved, but the complexity increases exponentially with cloud environment scale

Engineering Contradiction:
Improvesecurity coverageVSAvoidsystem complexity
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The patent segments the complex task of comprehensive endpoint documentation into smaller, manageable components. The automated system divides the cloud environment into discrete segments (endpoints, services, instances) and processes each segment independently through standardized identification routines. This segmentation approach maintains complete security coverage while reducing overall system complexity by breaking down the monolithic documentation task into modular, automated steps.

Inventive Principle:
Principle #1Segmentation

Data Source

PatentEP4708093A1APS data collection and modification system and method for analytics
Publication Date: 2026.03.11 CLOUDBLUE LLC
  • EP4708093A1 patent drawingFigure 1
  • EP4708093A1 patent drawingFigure 2
  • EP4708093A1 patent drawingFigure 3

AI summary

Systems and methodologies are provided for the automated collection, transformation, and documentation of API endpoints in cloud environments, streamlining cybersecurity workflows. A discovery module autonomously identifies endpoints accessible by various user roles. An Identifier Normalization Module dynamically adapts unique identifiers to a standardized naming convention for documentation. The system can further include a comparison engine to evaluate and visualize API access across different user roles, facilitating a comprehensive audit and compliance process. Systems and methods enable consistent endpoint mapping, role-based access clarity, and enhanced security posture management through an interactive dashboard, generating insights into the cloud instance's API landscape.