Container mirror image detection method, storage medium, program product and electronic equipment

By parsing the hierarchical structure and file list of container images, performing layer-by-layer comparison and cross-layer tracing, and combining static scanning and dynamic analysis, a risk detection report is generated. This solves the problem of difficulty in identifying deep malicious code in existing technologies and achieves efficient container image security detection.

CN122413428APending Publication Date: 2026-07-17ZHEJIANG E COMMERCE BANK CO LTD
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Patent Information

Application Number
CN202610534487.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-04-21
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

Existing malware detection solutions struggle to accurately identify and locate malware hidden deep within container image layers, exhibiting problems such as large detection blind spots, high false positive rates, and weak source tracing capabilities.

Method used

By parsing the hierarchical structure of the container image, obtaining the file lists corresponding to each layer, comparing them layer by layer, and tracking the information change records of the target files across layers, a risk detection report is generated by combining static scanning, dynamic behavior analysis, and cross-layer dependency analysis.

Benefits of technology

It enables comprehensive analysis of container images, accurately locates risk sources, improves detection accuracy, is applicable to various container image formats and build methods, quickly identifies potential risks, and improves security.

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Abstract

The embodiment of the invention discloses a container mirror image detection method, a storage medium, a program product and electronic equipment, and relates to the technical field of computers. In the specification, the hierarchical structure of the container mirror image is analyzed to obtain file lists corresponding to a plurality of layers, layer-by-layer comparison is further performed according to the file lists of the layers, target files of which information is changed in at least two layers are identified, and information change records of the target files in the whole container mirror image life cycle are constructed. And performing static scanning, dynamic behavior analysis and cross-layer dependency analysis on the container mirror image according to the information change record corresponding to the at least one target file to obtain a risk detection report indicating malicious content included in the container mirror image. According to the container mirror image detection method provided by the invention, the problem of inaccurate positioning of malicious contents in a deep mirror image can be solved, potential risks in the container mirror image can be quickly found and responded, and the safety of the container mirror image is improved.
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