Malicious code detection method, data interaction method and related equipment

Abstract

The invention relates to a malicious code detection method, a data interaction method and related equipment. The malicious code detection method comprises the steps of obtaining a to-be-detected code; vectorizing the to-be-detected code to obtain a vector corresponding to the to-be-detected code; performing feature extraction on the vector through a text classification model, and performing classification recognition based on the extracted features to obtain a category recognition result corresponding to the to-be-detected code, wherein the category identification result comprises identified code categories and corresponding category probabilities, and the code categories comprise malicious codes and normal codes; and if the category probability corresponding to the malicious code in the category identification result is greater than a preset threshold, determining that the to-be-detected code is the malicious code. By adopting the method, the malicious code recognition rate can be improved.

Description

technical field [0001] The present application relates to the technical field of information security, in particular to a malicious code detection method, a data interaction method and related equipment. Background technique [0002] Cross Site Scripting (Cross Site Scripting, abbreviated as XSS) attack is a common web application security vulnerability. This type of vulnerability can allow attackers to embed malicious script code into pages that normal users will visit. When normal users visit the page When this happens, it can lead to the execution of embedded malicious script code, thereby achieving the purpose of maliciously attacking users. [0003] XSS vulnerabilities can be divided into three types: local exploitation vulnerabilities, reflection vulnerabilities and storage vulnerabilities according to different attack methods. The local exploit resides in the client-side script itself within the page. Reflective vulnerabilities are somewhat similar to local exploita...

AI Technical Summary

Problems solved by technology

However, this detection method has the problem of being easily evaded, and the recognition rate is low. Hackers can evade detection by inserting characters or completely encoding, such as adding multiple tab keys, adding (space) cha

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