Security Policy Sandbox Analysis for Faster Root Cause Detection

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Solution Overview

Problem

Existing IT operations face significant challenges in identifying and remediating application connectivity issues in large network infrastructures, particularly for Software as a Service (SaaS) and private applications, due to the complexity and vastness of domains requiring thorough check and analysis, leading to increased mean time to detect and resolve issues.

Innovation Solution

An Application Access Analyzer (AAA) provides an interface for operators to detect and auto-remediate application reachability, connectivity, and access/permission issues, utilizing artificial intelligence and machine learning to analyze user authentication, network health, DNS servers, and security policies, and automatically discover network topology, reducing the mean time to resolve issues.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual troubleshooting methods are used in large network infrastructures, then domain knowledge expertise is required for thorough analysis, but the mean time to detect and resolve issues increases significantly

Engineering Contradiction:

Improvetroubleshooting analysis thoroughnessVSAvoidmean time to detect and resolve issues

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system enables self-service troubleshooting by automatically discovering network topology, analyzing security policies, and identifying root causes without requiring human domain knowledge expertise. The automated analysis engine performs comprehensive checks across multiple domains (network connectivity, DNS resolution, authentication, security policies) and provides actionable remediation recommendations, allowing operators to resolve issues without specialized knowledge while maintaining thorough analysis.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical troubleshooting processes with automated computational analysis. The system uses machine learning models and automated analysis engines to substitute human experts' cognitive processes, automatically gathering data, analyzing security policies, discovering network topology, and identifying root causes, thereby eliminating the time constraint while preserving analysis thoroughness.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Measurement precision

If comprehensive security policy analysis is performed across all network domains, then accurate root cause identification is achieved, but the complexity of the analysis process increases

Engineering Contradiction:

Improveroot cause identification accuracyVSAvoidanalysis process complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system segments the complex analysis process into distinct modular components: network connectivity analysis, DNS resolution analysis, authentication analysis, security policy analysis, and topological correlation analysis. Each module handles a specific domain independently, analyzing relevant data and security policies within that domain, then integrating results to identify root causes. This segmentation reduces overall complexity while maintaining comprehensive analysis accuracy.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces an automated analysis engine as an intermediary between raw network data and human operators. This intermediary component performs the complex security policy analysis, topological correlation, and root cause identification tasks, translating complex multi-domain data into simplified actionable insights. The intermediary absorbs the analytical complexity, presenting only essential findings to operators without requiring them to understand the underlying complex processes.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Productivity

If automated analysis tools are implemented to reduce troubleshooting time, then mean time to resolve issues decreases, but the system requires sophisticated AI and machine learning capabilities

Engineering Contradiction:

Improveissue resolution speedVSAvoidAI and machine learning system requirements

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The automated analysis engine is designed as a universal multi-functional system that performs multiple troubleshooting functions: network connectivity testing, DNS resolution analysis, authentication verification, security policy evaluation, and topological correlation. By consolidating these diverse functions into a single unified platform with integrated machine learning models, the system achieves high productivity without requiring separate complex AI systems for each function, reducing overall system complexity while maintaining fast resolution capabilities.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS12489794B2Security policy analysis

Publication Date: 2025.12.02 PALO ALTO NETWORKS INC

AI summary

Security policy analysis is disclosed. Configuration information, including at least one policy, associated with a live production security appliance, is received. The received configuration information is used to instantiate the policy in a sandbox environment. The sandbox environment is used to evaluate a proposed change to the configuration information, including by building a model using the received configuration information.