Codified Infrastructure Risk Evaluation and Modification
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Solution Overview
Problem
Existing security and reliability techniques for cloud infrastructure code are rudimentary and struggle to analyze dynamic and heterogeneous scripting languages, leading to security and reliability threats due to risky patterns in infrastructure code and scripts.
Innovation Solution
A system and method that utilizes an AI platform with an identification manager, risk manager, and modifier to identify and evaluate non-native program instructions in source code within a codified infrastructure, assigning risk identifiers and applying selective modifications to mitigate defects, leveraging machine learning models and static code analysis to assess and correct potential vulnerabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing security and reliability techniques are used for cloud infrastructure code, then the analysis process is simple, but the ability to analyze dynamic and heterogeneous scripting languages is insufficient
Solution Approach 1:
The code analysis system is segmented into specialized modules: an identification manager that detects non-native program instructions, a risk manager that evaluates risks using multiple static analysis tools, and a modifier that applies corrections. This segmentation allows each module to specialize in specific aspects of code analysis, improving overall reliability while managing complexity through modular architecture.
Solution Approach 2:
The patent introduces an AI platform as an intermediary layer between the code analysis tools and the codified infrastructure. This intermediary coordinates multiple static analysis tools, manages their outputs, and integrates their findings into a unified risk assessment, enabling comprehensive analysis of heterogeneous scripting languages without requiring direct integration of all tools.
2Measurement precision
If non-native program instructions are identified and evaluated using multiple static analysis tools, then the risk evaluation accuracy is improved, but the processing time increases
Solution Approach 1:
The system performs preliminary actions by identifying non-native program instructions and extracting them before comprehensive risk evaluation. The identification manager pre-processes the code to locate and isolate suspicious instructions, allowing the risk manager to focus analysis resources only on these extracted segments rather than analyzing the entire codebase, thereby reducing processing time while maintaining accuracy.
Solution Approach 2:
The patent applies partial action by using multiple static analysis tools selectively on identified non-native instructions rather than applying all tools to all code. The risk manager evaluates only the extracted non-native program instructions using appropriate tools, avoiding unnecessary analysis of safe code segments and reducing overall processing time while maintaining comprehensive risk evaluation accuracy.
3Reliability
If selective modifications are applied to mitigate defects, then the security and reliability is improved, but the complexity of modifying the codified infrastructure increases
Solution Approach 1:
The modifier component implements self-service by automatically applying corrections to identified defects in the codified infrastructure code. The system autonomously generates and applies modifications to mitigate risks, reducing the need for manual intervention and simplifying the modification process while maintaining high security and reliability standards.
Data Source
AI summary
A system, computer program product, and method are provided for supporting risk evaluation and modification of an executable codified infrastructure. The codified infrastructure is analyzed to identify any non-native program instructions. A selection of the identified non-native program instructions are combined and subjected to a risk evaluation by non-native tools. A risk evaluation result is mapped to corresponding lines of the source code, and a risk identifier is assigned to the corresponding lines of the source code. One or more modifications are selectively applied to the codified infrastructure in correspondence with the assigned risk identifier. The applied modification mitigates any defects in the source code.