WEBSHELL detection method and device, equipment and storage medium
A detection method and detection model technology, applied in the field of network security, can solve the problems of lag, the detection method of requesting data, the detection rate is not high, and the false alarm rate is high.
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Embodiment 1
[0052] Please refer to figure 1 , figure 1 A flow chart of a WEBSHELL detection method provided in this embodiment; the method mainly includes:
[0053] Step s110, after the client sends the request data to the server, obtain the response data fed back by the server to the client according to the request data;
[0054] Wherein, the request data refers to the data in the request information packet initiated by the client to the server, including: request line, request header, request body and so on. Response data refers to the data in the response information packet from the server to the client, including: response line, response header, response body, etc. In this embodiment, the response data refers to the server receiving the request data and sending the request data to the client according to the request data. The feedback response data, that is, the request data and the response data in this embodiment are data correspondingly generated in a complete interaction.
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Embodiment 2
[0062] Since the request data sent by the client to the server also contains certain WEBSHELL feature data, in order to improve the detection accuracy, WEBSHELL feature recognition can be carried out based on the request data and response data at the same time, so as to realize the two-way detection when the client interacts with the server. In order to more accurately identify WebShell. Correspondingly, in addition to the above steps, the following steps can be further performed: obtaining request data. Specifically, step s110 in Embodiment 1 can be adjusted to: obtain the request data sent by the client to the server and the server send the request data to the client according to the request data. correspondingly, step s120 specifically includes: identifying service traffic WEBSHELL features according to the request data and response data. Then the model recognition result includes two parts, that is, the request recognition result and the response recognition result.
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Embodiment 3
[0097] In the second embodiment above, there is no limitation on the types of features specifically identified in each model (which may include a request detection model, a response detection model, and an interaction model). set up. In order to deepen the understanding of the feature recognition process under various models, several ways of implementing feature recognition are introduced in this embodiment.
[0098] Optionally, a request data feature identification method of a request detection model is as follows:
[0099] (1) Input the request data into the request detection model;
[0100] (2) The request detection model performs WEBSHELL identification on the request data according to the pre-set dangerous request characteristics; among them, the dangerous request characteristics include: specifying dangerous function calls, specifying dangerous commands, specifying special characters, specifying characteristics of well-known backdoors, specifying request traffic At lea...
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