Pipeline Source-Target Mapping for CI/CD Vulnerability Tracing
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Solution Overview
Problem
In cloud computing environments, it is difficult to map source code to runtime resources and detect vulnerabilities due to the complexity of CI/CD pipelines, leading to challenges in tracing back vulnerabilities and identifying malicious activities between sources and targets.
Innovation Solution
A processor parses pipeline code, replaces variables with corresponding values, and builds a dependency graph to map pipeline run sources and targets, enabling the identification of vulnerabilities and their root causes, and performs remedial actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If pipeline code is executed in cloud infrastructure to perform CI/CD operations, then deployment and update processes are automated, but it becomes difficult to map source code to runtime resources and detect vulnerabilities
Solution Approach 1:
The patent introduces an intermediary system that instruments pipeline code execution to capture and map relationships between source code and runtime resources. This intermediary layer records interactions without disrupting the automated CI/CD process, enabling vulnerability detection while maintaining automation.
Solution Approach 2:
The system creates a copy or representation of the pipeline execution environment and resource interactions. By capturing and storing the mapping data between sources and targets during execution, the system enables later analysis and vulnerability detection without affecting the original automated process.
2Productivity
If pipeline code defines orchestration of CI/CD operations and infrastructure configuration, then deployment efficiency is improved, but tracing back vulnerabilities and identifying malicious activities becomes challenging
Solution Approach 1:
The system implements feedback mechanisms that continuously monitor and record pipeline execution, source-code interactions, and resource usage. This feedback loop captures mapping information that enables later tracing and vulnerability analysis while maintaining efficient automated deployment operations.
Solution Approach 2:
The system performs preliminary instrumentation of pipeline code before execution, establishing tracking and mapping capabilities in advance. This preliminary action enables subsequent vulnerability tracing without impacting the efficiency of the actual deployment operations.
3Measurement precision
If variables in pipeline code are replaced with values corresponding to sources and targets, then mapping accuracy is improved, but the complexity of parsing and analyzing pipeline code increases
Solution Approach 1:
The system segments the pipeline code parsing and variable replacement process into distinct, manageable stages. By breaking down the complex analysis into smaller steps (parsing, variable identification, replacement, validation), the system achieves accurate mapping while keeping each processing stage relatively simple and maintainable.
Data Source
AI summary
According to examples, an apparatus includes a processor that may obtain and parse a pipeline code to determine how variables of the pipeline code relate to each other, and replace the variables in the parsed pipeline code with values to which the variables respectively represent, in which the values correspond to pipeline run sources and pipeline run targets of API calls. The processor may also identify how the pipeline run targets interact with the pipeline run sources of the API calls and build a dependency graph that maps the pipeline run sources with the pipeline run targets. Runtime resources may thus be mapped to source code in a pipeline run to provide visibility into actions carried out by the pipeline. This visibility may be used to determine whether there are security vulnerabilities in the pipeline run sources and/or targets such that the vulnerabilities may be addressed/overcome.