Container Base Image Security Evaluation
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Solution Overview
Problem
In container-based virtualization, there is a lack of effective methods to evaluate and manage security risks associated with third-party container base images, particularly when they are shared across different computing environments, leading to potential security deficiencies and challenges in maintaining secure application containers.
Innovation Solution
A system and method that examines target application container configuration data to identify base images, subjects script data to text-based processing for security risk evaluation, and selects a hosting computing environment based on the evaluation results, ensuring secure hosting by differentiating between differently configured but commonly named base images across various environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If container base images are shared across different computing environments, then resource utilization and deployment flexibility are improved, but security risks increase due to potential vulnerabilities in third-party images
Solution Approach 1:
The system performs preliminary security evaluation of container base images by extracting and analyzing script data (such as Dockerfiles) before deployment. The evaluation process checks for security vulnerabilities, outdated packages, and configuration issues in advance, allowing the system to select or modify images prior to use, thus preventing vulnerable images from being deployed while maintaining the flexibility to use shared images across environments.
2Reliability
If manual security evaluation of container base images is performed, then security accuracy is improved, but processing time and operational complexity increase
Solution Approach 1:
The system implements automated self-service security evaluation by automatically extracting script data from container base images and analyzing it against security criteria. The evaluation process is performed autonomously by the system without requiring manual intervention, using automated tools to scan for vulnerabilities, check image signatures, and assess configuration security, thereby maintaining high accuracy while significantly reducing processing time.
3Reliability
If comprehensive security checks are performed on all container components, then security thoroughness is improved, but system complexity and overhead increase
Solution Approach 1:
The system extracts and focuses security evaluation on the most critical components of container base images, particularly script data such as Dockerfiles, package manifests, and configuration files. By concentrating the security analysis on these key elements rather than performing exhaustive checks on all possible components, the system achieves thorough security evaluation of the most vulnerable parts while reducing overall system complexity and overhead.
Data Source
AI summary
Methods, computer program products, and systems are presented. The method computer program products, and systems can include, for instance: examining target application container configuration data to identify one or more target container base image referenced in the target application container configuration: subjecting script data associated to the one or more target container base image to text based processing for evaluation of security risk associated to the one or more container base image, the script data obtained from at least one candidate hosting computing environment; and selecting a hosting computing environment from the at least one computing environment for hosting the target application container, the selecting in dependence on the text based processing.