Container software security detection system and method based on content difference

Abstract

The present invention provides a container software security detection system and method based on content difference, including identification and classification nodes, data acquisition nodes and security analysis nodes, and the three nodes work together by exchanging data; identification and classification nodes: complete and User interaction, basic image identification for all input images to be detected, image classification, sending data acquisition tasks, etc.; data acquisition node: download the corresponding container image according to the issued data acquisition task, and download the completed container Image extracts the corresponding container image layer data; security analysis node: According to the extracted container image layer data, non-basic image layer data is identified, and the security analysis is performed on the non-basic image layer data. While ensuring the effectiveness of the detection, the present invention does not need to actually run the image, which greatly saves computing and storage resources, and can realize full security detection of a large number of images in the public warehouse in a relatively short period of time with limited resources.

Description

technical field [0001] The present invention relates to the technical field of container software security detection, in particular, to a container software security detection system and method based on content difference. Background technique [0002] Container software applications based on virtualization technology are becoming more and more common. The container form mainly represented by Docker carries various enterprise-level virtualization applications common in various cloud centers. Among them, Docker Hub is its official storage warehouse, which contains various users in the community. There are 18 million application images in the database, and users need to download such images from the warehouse as long as they use and deploy related applications. The vulnerability of such container images has become the focus of attack and defense. In particular, the lack of security configuration exposes serious security vulnerabilities such as privacy leakage and unauthorized ...

AI Technical Summary

Problems solved by technology

[0004] In view of the prior art mentioned above, the inventor believes that the general problem of this type of method is that it needs to consume a lot of resources (storage, bandwidth) to download a large number of images to the local test environment, and it needs to consume a lot of computing resources and time costs for performing detection

Therefore, it is difficult to apply to large-scale container software security detection

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