Unified Risk Engine for Application and Infrastructure Code
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Solution Overview
Problem
Current tools use a single-dimension risk approach, failing to effectively detect and prevent security and compliance risks across application and infrastructure code, as they do not consider the interrelated responsibilities of software developers, DevOps, and DevSecOps.
Innovation Solution
A multidimensional risk engine that analyzes application code, infrastructure code, developer behavior, business impact, deployment location, and data sensitivity, correlating these elements to provide a contextual story for detecting and preventing risks before deployment in the cloud.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If single-dimension risk approach is used by separate tools, then tool simplicity is maintained, but risk detection completeness deteriorates
Solution Approach 1:
The patent merges application security scanning, infrastructure security scanning, and compliance checking into a single unified risk assessment system. The system collects data from multiple sources including application code, infrastructure code, and configuration files, then processes them together to generate comprehensive risk scores that reflect both application and infrastructure vulnerabilities in context.
Solution Approach 2:
The risk assessment system is designed to perform multiple functions: it scans application code for vulnerabilities, scans infrastructure code for misconfigurations, checks compliance with security policies, and calculates unified risk scores. This multi-functional approach allows a single tool to replace multiple separate tools while providing more comprehensive risk detection.
2Measurement precision
If multidimensional risk analysis is implemented, then risk detection accuracy is improved, but system complexity increases
Solution Approach 1:
The system segments the risk assessment process into distinct modules: data collection from multiple sources, feature extraction from code and configurations, risk factor identification, compliance checking, and risk score calculation. Each module handles a specific aspect of the analysis, making the overall complex system manageable through clear separation of concerns.
Solution Approach 2:
The patent introduces a central risk assessment engine that acts as an intermediary between various data sources (application code, infrastructure code, configuration files) and the final risk evaluation. This engine standardizes data from different sources, extracts relevant features, and coordinates the complex analysis processes, simplifying the system architecture while maintaining high detection accuracy.
3Reliability
If contextual information from multiple sources is integrated, then risk prioritization effectiveness is improved, but data processing time increases
Solution Approach 1:
The system performs preliminary data processing and feature extraction during the code review process itself, before formal risk assessment is needed. It pre-identifies potential risk factors, pre-extracts features from code and configurations, and pre-validates compliance requirements. This preliminary preparation reduces the time required for actual risk prioritization while maintaining comprehensive analysis.
Data Source
AI summary
A method for unifying risks and remediations associated with entities in application and infrastructure code, including the steps of: defining governance rules; fetching data from more than one source; extracting features from the data in a unified manner; formalizing sub-entities from the extracted features, the formalized sub-entities representing the extracted features in a formal and unified manner; providing a plurality of entities from the formalized sub-entities, matching and unifying sub-entities having common extracted features into single entities of the plurality of entities; aggregating risks and remediations of each of the same sub-entities and assigning the aggregated risks and remediations to the corresponding single entity; and computing risk priority and triggering workflows based on the matched governance rules.