Pipeline Source-Target Dependency Mapping for Cloud Vulnerability Tracing
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Solution Overview
Problem
In cloud computing environments, it is difficult to map source code to runtime resources and identify vulnerabilities due to the complexity of CI/CD pipelines, making it challenging to detect and address security issues and malicious activities effectively.
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
1Productivity
If CI/CD pipelines are used to manage service deployment, then service delivery efficiency is improved, but mapping source code to runtime resources becomes difficult
Solution Approach 1:
The patent introduces an intermediary system that captures and processes pipeline execution data, creating a mapping between source code and runtime resources. This intermediary layer collects information about pipeline runs, extracts resource identifiers, and establishes relationships without disrupting the existing CI/CD workflow, thus resolving the mapping difficulty while maintaining delivery efficiency
Solution Approach 2:
The system creates a virtual copy or representation of the pipeline execution process, capturing metadata and resource associations in a separate data structure. This copy allows analysis and mapping without interfering with the actual pipeline execution, enabling source code to runtime resource tracking while preserving the original deployment efficiency
2Reliability
If pipeline complexity increases to handle more testing stages and workflows, then service quality is improved, but vulnerability detection becomes more challenging
Solution Approach 1:
The patent segments the complex pipeline into individual executable steps, capturing data at each step separately. By breaking down the pipeline workflow into discrete units and tracking resources at each segment, the system maintains visibility into vulnerabilities despite increasing overall pipeline complexity and quality assurance stages
Solution Approach 2:
The system implements feedback mechanisms that continuously monitor pipeline execution and resource usage, providing real-time information about potential vulnerabilities. This feedback loop allows the system to adapt to increasing pipeline complexity while maintaining effective vulnerability detection through continuous observation and analysis
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.