Incremental Security Policy Validation Using Infrastructure As Code

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Solution Overview

Problem

Existing security policy validation processes in multi-tenant environments often miss semantic validations, leading to potential misconfigurations in production environments, which can result in security or availability exceptions, especially in complex deployments with dispersed configuration knowledge across manual run books and institutional knowledge.

Innovation Solution

Implementing an incremental validation system that uses information from an infrastructure as code repository to create a test environment identical to the production environment, allowing for the validation of security policy updates before deployment, ensuring that security and availability postures are validated during the Continuous Delivery pipeline.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If post deployment verification is performed by various services, then security policies can be validated in production environment, but there is risk of misconfiguration leading to security exceptions or availability exceptions

Engineering Contradiction:

Improvesecurity policy validation reliabilityVSAvoidsecurity exceptions and availability exceptions

Core Design Contradiction:

ReliabilityVSObject-affected harmful factors

Solution Approach 1:

The system performs preliminary semantic validation of security policies in a test environment before deploying to production. By validating policies against the infrastructure as code repository and generating test environments that mirror production, the system catches misconfigurations before they reach the production environment, preventing security and availability exceptions while maintaining reliable validation.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system creates a protective layer by implementing incremental validation that tests security policies in a controlled test environment before production deployment. This cushioning mechanism allows misconfigurations to be detected and corrected in advance, preventing them from causing harmful effects in the production environment while maintaining validation reliability.

Inventive Principle:

Principle #11Beforehand cushioning (Prior cushioning)

2Productivity

If syntactic validation only is applied during code generation, then code can be deployed quickly, but semantic validations are missed leading to potential misconfigurations

Engineering Contradiction:

Improvecode deployment speedVSAvoidsecurity policy correctness

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The validation process is segmented into two distinct phases: syntactic validation during code generation for quick feedback, and semantic validation in a test environment before production deployment. This segmentation allows the system to maintain fast code generation through syntactic checks while ensuring correctness through subsequent semantic validation against the infrastructure as code repository, resolving the contradiction between speed and reliability.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system performs preliminary semantic validation in a test environment before production deployment. By conducting semantic validation as a preliminary action before the final production release, the system ensures policy correctness without blocking the initial fast syntactic validation and code generation process, thus maintaining both productivity and reliability.

Inventive Principle:

Principle #10Preliminary action

3Measurement precision

If test environment is created identical to production environment, then validation accuracy is improved, but system complexity and resource requirements increase

Engineering Contradiction:

Improvevalidation accuracyVSAvoidtest environment complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system creates a simplified copy of the production environment by using the infrastructure as code repository to generate test environments that mirror production configurations. This copying approach enables accurate semantic validation by replicating production semantics without requiring a full production clone, thus improving validation accuracy while controlling complexity through automated code-based environment generation.

Inventive Principle:

Principle #26Copying

Data Source

PatentUS20240289259A1Incrementally Validating Security Policy Code Using Information From An Infrastructure As Code Repository

Publication Date: 2024.08.29 SALESFORCE INC

AI summary

In an example, an apparatus may include a validation module configured to identify a security policy update from a security as code repository, wherein the identified security policy update is a candidate for deployment to a production environment having a plurality of attributes defined by an infrastructure as code repository; identify, from the plurality of attributes and using the infrastructure as code repository, individual attributes that correspond to the identified security policy update, wherein the identified individual attributes are identical to a subset of the plurality of attributes; generate a test environment based on the identified individual attributes; following deployment of the identified security policy update to the test environment, check for security exceptions or availability exceptions using the test environment; and output validation results based on a result of the checking.