Network configuration detection method and device, equipment, storage medium and program product

Abstract

The invention provides a network configuration detection method and device, equipment, a storage medium and a program product. Relates to the technical field of computers. The method comprises the following steps: acquiring a configuration rule base, the type of a first device and a plurality of configured network parameters in the first device, wherein the configuration rule base comprises configuration rules corresponding to the network parameters of a plurality of devices; determining a first configuration rule corresponding to each configured network parameter in a configuration rule base according to the type of the first equipment and the plurality of configured network parameters; detecting the configured network parameters according to the configuration detection model, the plurality of configured network parameters and the plurality of first configuration rules to obtain detection information corresponding to each configured network parameter; and the detection result of the first equipment is determined according to the multiple pieces of detection information, so that the network configuration detection efficiency is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of computer, and particularly relates to a network configuration detection method and device, equipment, a storage medium and a program product. BACKGROUND

[0002] With the development of cloud computing technology and the continuous growth of the scale of enterprise cloud resource pool, the number of internal network devices increases sharply. In order to meet the requirements of different business scenarios, when adjusting the configuration of multiple network devices, the adjusted network configuration needs to be detected to ensure that each network device can run safely and stably.

[0003] In the related art, the network configuration detection is usually performed in an artificial manner, that is, a technical personnel needs to check the configuration files of each network device and uses a detection tool matched with each network device to assist in judgment, and then completes the network configuration detection.

[0004] However, in the above method, the configuration files need to be checked line by line by artificial experience, and different network devices need to use different detection tools, which leads to low efficiency of the configuration detection of the network device. SUMMARY

[0005] The present application provides a network configuration detection method, device, equipment, storage medium and program product, to solve the technical problem of low efficiency of the configuration detection of the network device.

[0006] In a first aspect, the present application provides a network configuration detection method, comprising:

[0007] obtaining a configuration rule library, a type of a first device, and a plurality of configured network parameters in the first device, the configuration rule library comprising configuration rules corresponding to network parameters of a plurality of devices;

[0008] determining, in the configuration rule library, first configuration rules corresponding to each configured network parameter according to the type of the first device and the plurality of configured network parameters;

[0009] detecting the configured network parameters according to a configuration detection model, the plurality of configured network parameters and the plurality of first configuration rules, to obtain detection information corresponding to each configured network parameter;

[0010] determining a detection result of the first device according to the plurality of detection information.

[0011] In a possible implementation manner, the configuration rule library is obtained, comprising:

[0012] obtaining configuration files corresponding to network parameters of a plurality of devices;

[0013] The multiple configuration files are parsed to obtain multiple configuration rules.

[0014] The multiple configuration rules are vectorized, and a configuration rule library is determined according to the multiple vectorized configuration rules.

[0015] In a possible implementation, according to the configuration detection model, the multiple configured network parameters, and the multiple first configuration rules, the configured network parameters are detected to obtain detection information corresponding to each configured network parameter, including:

[0016] The association relationship of the multiple configured network parameters is determined.

[0017] According to the association relationship, the multiple configured network parameters are segmented to obtain multiple network parameter sets, and the network parameter set includes multiple network parameters having an association relationship.

[0018] According to the configuration detection model, the multiple network parameter sets, and the multiple first configuration rules, detection information corresponding to each network parameter set is determined.

[0019] In a possible implementation, according to the configuration detection model, the multiple network parameter sets, and the multiple first configuration rules, detection information corresponding to each network parameter set is determined, including:

[0020] For any one network parameter set, the configured network parameter set and the first configuration rule are integrated according to a preset prompt template to obtain an integrated network parameter set and first configuration rule.

[0021] The integrated network parameter set and the first configuration rule are input into the configuration detection model to obtain configuration information of the network parameter set and a detection result of configuration detection on the network parameter set.

[0022] According to the configuration information of the network parameter set and the detection result of configuration detection on the network parameter set, detection information corresponding to each network parameter set is determined.

[0023] In a possible implementation, according to the multiple detection information, a detection result of the first device is determined, including:

[0024] The multiple detection information is spliced to obtain multiple spliced detection information.

[0025] According to the configuration detection model and the multiple spliced detection information, a detection result of the first device is determined, and the detection result of the first device is used to indicate a dependency relationship between each configured network parameter of the first device.

[0026] In a possible implementation, after determining the detection result of the first device according to the configuration detection model and the plurality of detection information after splicing, the method comprises:

[0027] According to the detection result of the first device, the detection state of each configured network parameter is determined, and the detection state can be a normal detection state or an abnormal detection state;

[0028] When the detection state is an abnormal detection state, an abnormal reason of the target network parameter is obtained, and a configuration modification suggestion of the target network parameter is determined according to the abnormal reason.

[0029] In a possible implementation, after determining the detection result of the first device according to the plurality of detection information, the method further comprises:

[0030] The newly added or modified configuration rule is obtained;

[0031] The newly added or modified configuration rule is verified to obtain a verification result;

[0032] When the verification result is a verification pass, the configuration rule library is updated.

[0033] In a second aspect, the present application provides a network configuration detection device, comprising: an obtaining module, a first determining module, a detection module and a second determining module, wherein,

[0034] The obtaining module is configured to obtain a configuration rule library, a type of a first device, and a plurality of configured network parameters in the first device, and the configuration rule library comprises a plurality of configuration rules corresponding to network parameters of a plurality of devices;

[0035] The first determining module is configured to determine, according to the type of the first device and the plurality of configured network parameters, a first configuration rule corresponding to each configured network parameter in the configuration rule library;

[0036] The detection module is configured to detect the configured network parameters according to a configuration detection model, the plurality of configured network parameters and the plurality of first configuration rules, to obtain detection information corresponding to each configured network parameter;

[0037] The second determining module is configured to determine a detection result of the first device according to the plurality of detection information.

[0038] In a possible implementation, the obtaining module is specifically configured to:

[0039] Obtain a plurality of configuration files corresponding to network parameters of a plurality of devices;

[0040] The plurality of configuration files are parsed to obtain a plurality of configuration rules;

[0041] The plurality of configuration rules are vectorized, and a configuration rule library is determined according to the plurality of vectorized configuration rules.

[0042] In a possible implementation, the detection module is specifically configured to:

[0043] determine the association relationship of the plurality of configured network parameters;

[0044] segment the plurality of configured network parameters according to the association relationship to obtain a plurality of network parameter sets, wherein each network parameter set includes a plurality of network parameters that have an association relationship;

[0045] determine detection information corresponding to each network parameter set according to the configuration detection model, the plurality of network parameter sets, and the plurality of first configuration rules.

[0046] In a possible implementation, the detection module is specifically configured to:

[0047] for any one network parameter set, integrate the configured network parameter set and the first configuration rule according to a preset prompt template to obtain an integrated network parameter set and first configuration rule;

[0048] input the integrated network parameter set and the first configuration rule into the configuration detection model to obtain configuration information of the network parameter set and a detection result of configuration detection on the network parameter set;

[0049] determine detection information corresponding to each network parameter set according to the configuration information of the network parameter set and the detection result of configuration detection on the network parameter set.

[0050] In a possible implementation, the second determination module is specifically configured to:

[0051] splice the plurality of detection information to obtain spliced detection information;

[0052] determine a detection result of the first device according to the configuration detection model and the spliced detection information, wherein the detection result of the first device is used to indicate a dependency relationship between the plurality of configured network parameters of the first device.

[0053] In a possible implementation, the apparatus further includes a first processing module, which is specifically configured to:

[0054] determine a detection state of each configured network parameter according to the detection result of the first device, wherein the detection state can be a normal detection state or an abnormal detection state;

[0055] when the detection state is the abnormal detection state, obtain an abnormal reason of a target network parameter, and determine a configuration modification suggestion of the target network parameter according to the abnormal reason.

[0056] In a possible implementation, the apparatus further includes a second processing module, which is specifically configured to:

[0057] obtain the newly added or modified configuration rule;

[0058] perform a verification process on the newly added or modified configuration rule to obtain a verification result;

[0059] update the configuration rule library when the verification result is a verification pass.

[0060] In a third aspect, the present application provides an electronic device, including: a memory, a processor;

[0061] The memory stores computer execution instructions.

[0062] The processor executes the computer execution instructions stored in the memory, so that the processor executes the first aspect and / or various possible implementation manners of the first aspect.

[0063] In a fourth aspect, the present application provides a computer readable storage medium, which stores computer execution instructions, and the computer execution instructions are used to implement the first aspect and / or various possible implementation manners of the first aspect when executed by a processor.

[0064] In a fifth aspect, the present application provides a computer program product, which includes a computer program, and the computer program is used to implement the first aspect and / or various possible implementation manners of the first aspect when executed by a processor.

[0065] The network configuration detection method, apparatus, device, storage medium and program product provided by the present application obtain a configuration rule library, a type of a first device, and a plurality of configured network parameters in the first device, the configuration rule library including configuration rules corresponding to network parameters of a plurality of devices; according to the type of the first device and the plurality of configured network parameters, determine first configuration rules corresponding to each configured network parameter in the configuration rule library; according to a configuration detection model, the plurality of configured network parameters and the plurality of first configuration rules, detect the configured network parameters to obtain detection information corresponding to each configured network parameter; and according to the plurality of detection information, determine a detection result of the first device. In the above method, the electronic device can realize cross-device rule matching by constructing a configuration rule library compatible with a plurality of devices, replace manual line-by-line checking with the help of the configuration detection model, and comprehensively analyze the detection conclusion of the overall architecture of the network device. Without relying on personal experience and without switching special tools, the network configuration detection process is simplified, effectively solving the problems of low efficiency of configuration detection of network devices and lack of global perspective in single-point analysis in the prior art. On the basis of improving the efficiency of network configuration detection, the automation level and accuracy of network configuration management are improved. Attached Figure Description

[0066] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0067] Figure 1 This application provides an illustration of the application scenario.

[0068] Figure 2 A schematic diagram illustrating the process of a network configuration detection method provided in this application;

[0069] Figure 3 A schematic diagram illustrating the process of determining the configuration modification suggestions provided for this application;

[0070] Figure 4 A schematic diagram illustrating the process of constructing a configuration rule base according to an embodiment of this application;

[0071] Figure 5 A schematic diagram illustrating another network configuration detection method provided in this application embodiment;

[0072] Figure 6 This application provides a schematic diagram of the structure of a network configuration detection device;

[0073] Figure 7 A schematic diagram of the structure of the electronic device provided in this application.

[0074] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0075] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0076] The collection, storage, use, processing, transmission, provision, and disclosure of financial data or user data involved in the technical solution of this application all comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0077] It should be noted that in the embodiments of the present application, some software, components, models and other industry solutions may be mentioned, which should be considered as exemplary, and the purpose is only to illustrate the feasibility of the implementation of the technical solutions of the present application, but it does not mean that the applicant has or will necessarily use the solution.

[0078] Figure 1 The application scenario provided by the present application is shown in the schematic diagram as shown in Figure 1 The electronic device and the terminal device.

[0079] The electronic device and the terminal device can communicate, and the user can send data related to network configuration to the electronic device through the terminal device. After the electronic device obtains the related data, the electronic device can perform configuration detection on the data to obtain the detection result of the network configuration, and complete the network configuration detection operation. The electronic device can be a server, a computer or other device with data processing capability, and the terminal device can be a server, a computer or other device.

[0080] In combination with the above scenario, it can be known that in the prior art, the network configuration detection is usually performed in an artificial manner, that is, the technical personnel need to check the configuration files of each network device and use detection tools matched with each network device to assist in judgment, and then complete the network configuration detection. However, in the above method, the configuration files need to be checked line by line by artificial experience, and different detection tools need to be used for different network devices, which leads to low efficiency of configuration detection of the network device.

[0081] The network configuration detection method, device, equipment, storage medium and program product provided by the application, by obtaining a configuration rule library, the type of a first device and a plurality of configured network parameters in the first device, matching the first configuration rule corresponding to each parameter from the rule library based on the device type and the configured parameters, completing the detection by the configuration detection model combined with the parameters and the rules, and outputting the detection result of the first device. In the above method, the electronic device realizes the rule adaptation of different types of devices from the detection source by constructing a unified rule library integrating the configuration rules of multiple devices, without switching special detection tools for a single device, effectively avoiding the problems of tool fragmentation and poor adaptability in traditional detection. Moreover, the configuration detection model replaces manual line-by-line checking, and the detection conclusion of the overall architecture of the network device is obtained through comprehensive analysis, the consistency of different device detection standards is ensured through standardized detection logic, the network configuration detection process is simplified, the detection omissions and result deviations caused by differences in manual experience are effectively solved, the accuracy and standardization level of network configuration detection are improved, and through the mechanism of segmented detection and global aggregation, complex configurations can be disassembled and analyzed in depth according to function modules, and then the results are comprehensively inferred, so that the overall configuration consistency and health status of the device are globally judged while ensuring the detection granularity, overcoming the defect that the traditional single-point tool cannot find the cross-module strategy contradiction. In addition, the method can be applied to intelligent diagnosis and automation of network configuration in a cross-vendor, large-scale complex cloud network environment, enhancing the adaptability and scalability of the scheme, improving the network configuration management automation level and accuracy on the basis of improving the network configuration detection efficiency.

[0082] The technical solutions of the application and how the technical solutions solve the above technical problems will be described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of the application will be described below with reference to the drawings.

[0083] Figure 2 A process diagram of a network configuration detection method provided by the application is shown in Figure 2 The method comprises the following steps.

[0084] S201, obtaining a configuration rule library, the type of a first device, and a plurality of configured network parameters in the first device.

[0085] The execution subject of the embodiment of the application can be an electronic device, or a network configuration detection device arranged in the electronic device. The network configuration detection device can be realized by software, or by the combination of software and hardware.

[0086] The configuration rule library comprises a plurality of configuration rules corresponding to the network parameters of the devices.

[0087] The configuration rule base can be a database storing vector form data, which stores configuration rules obtained by processing standard configurations of a large number of network devices. That is, it can be understood that the configuration rule base is used to store configuration rule vectors of network devices of multiple manufacturers.

[0088] Each rule in the configuration rule base describes the specifications or constraints that different types of devices should meet under certain conditions. The configuration rule base is used to provide standardized diagnostic basis and feature support for subsequent intelligent detection. For example, the access control list (ACL) syntax specification of network device A is converted into a vector and stored in the knowledge base.

[0089] The first device can be a network device currently to be configured and detected, that is, the first device can refer to a hardware device with network parameter configuration function, or a virtual network device in a cloud environment, for example, the network device can be a switch, a router, etc.

[0090] The type of the first device is used to identify the manufacturer and model of the first device, that is, the core information of the first device can be {manufacturer A; model B} by the type of the first device, which can quickly filter irrelevant rules in the configuration rule base and avoid detection deviation caused by false matching of general rules.

[0091] The configured network parameter can be a specific item that can be set by the network device during the configuration process, that is, the configured network parameter can refer to network configuration information performed by the user according to actual needs. For example, the configured network parameter can be an Internet Protocol (IP) address configured by the interface, a rule entry in the ACL, etc.

[0092] In some embodiments, the electronic device can obtain the configuration rule base based on the following implementation manner: obtaining configuration files corresponding to network parameters of a plurality of devices; performing parsing processing on the plurality of configuration files to obtain a plurality of configuration rules; performing vectorization processing on the plurality of configuration rules, and determining the configuration rule base according to the plurality of configuration rules after vectorization.

[0093] The configuration file can be a file generated by the network device to record parameter configuration information, that is, the configuration file is the network device configuration rule information of each manufacturer.

[0094] In some embodiments, the electronic device can directly obtain original configuration files from various vendor devices in the target network environment through an automated collection mechanism, which provides a data source for building the configuration rule library. In implementation, the electronic device can be connected to network devices of different vendors in sequence by using the management and control protocols supported by the devices. For each device, the electronic device executes a dedicated command to obtain a complete current running configuration or a start-up configuration, and saves the returned configuration text as an independent configuration file. This step ensures the directness and coverage of the original data.

[0095] The collected configuration files can be any format of text content, i.e., the configuration file formats include but are not limited to pure text command line records (for example,.txt or.cfg), standardized structured data (for example, XML, JSON, etc.), PDF, Word, pictures, etc. This process ensures the diversity and timeliness of the learning source of the rule library.

[0096] In some embodiments, the electronic device can perform data preprocessing on the configuration rule information in the configuration files, i.e., convert non-pure text content into a unified pure text format, and remove irrelevant interference information while retaining the core configuration content. Specifically, the electronic device can recognize the picture content by calling an optical character recognition (OCR) technology, retain only the configuration command line information, and use a document parsing library to process PDF, Word, and other format files to extract the text content and form a standardized pure text.

[0097] After obtaining the pure text content, the obtained pure text can be parsed, which aims to convert unstructured text descriptions or configuration commands into structured configuration rules. For descriptive rule text, natural language processing (NLP) technology can be used to identify key entities and operations, and fill them into a pre-defined structured template. In this way, through the two stages of format unification and structured parsing, the original information with different sources and formats can be converted into standardized structured configuration rules that can be used for vectorization and intelligent diagnosis.

[0098] In some embodiments, the electronic device can perform vectorization conversion on the structured configuration rules obtained after parsing, and convert them into machine-understandable semantic representations. This process aims to realize semantic storage and retrieval of knowledge. Specifically, the core text description of each configuration rule can be input into a pre-trained natural language processing model. The model maps the text into a fixed-length numerical vector in a high-dimensional space, which is called a semantic vector and encodes the semantic information of the configuration rule. In this way, these semantic vectors are stored and indexed in a dedicated vector database, thereby forming a configuration rule library that supports semantic queries.

[0099] In this way, by pure text extraction and vectorization conversion, the processing compatibility problem caused by the various formats of configuration rule texts is solved. For example, the OCR technology can convert the configuration specifications in picture format into pure text, and the BERT model encodes the text semantics into vectors, thereby unifying the storage formats of configuration rules of different manufacturers. This method significantly improves the construction efficiency of the knowledge base and the accuracy of rule retrieval, and provides more accurate domain knowledge support for AI agents.

[0100] In some embodiments, the electronic device can obtain configuration information to be detected sent by the user, which is usually collected from the first device through an automated script, and the configuration information is configuration data of all network parameters of the first device. The specific process is that the electronic device can automatically identify the feature strings (such as prompt, version line, etc.) in the configuration information to determine the type of the first device (for example, the type of the first device is type A). And parse the configuration information to extract all configured network parameters to form a structured network parameter list.

[0101] To realize continuous monitoring of the parameter configuration of each network device, this process can be set as a daily or periodic automatic task, that is, the scheduling system initiates a configuration collection request to each network device in the cloud resource pool at regular intervals, automatically completes configuration pulling, type identification, and parameter extraction, thereby realizing regular and periodic automatic detection of the configuration of the entire network device.

[0102] S202, according to the type of the first device and the plurality of configured network parameters, determining, in the configuration rule library, a first configuration rule corresponding to each configured network parameter.

[0103] In some embodiments, the electronic device can use the type of the first device (for example, the model of the first device) as a filtering condition to quickly narrow down the search range in the configuration rule library and filter out a rule subset related to the type of the device or commonly used. This ensures that the matched rules have basic applicability in syntax and semantics, and for each configured network parameter, the description of the network parameter is converted into a query vector. The conversion process uses the same model as the vectorization processing of the configuration rules when building the rule library to ensure the consistency of the vector space.

[0104] In this way, the electronic device can perform similarity search (for example, calculate the cosine similarity) in the vector space corresponding to the rule subset filtered according to the type of the device to find one or more rule vectors closest to the query vector. Among them, the configuration rule with the highest similarity and the most matched semantics with the query parameter is determined as the first configuration rule corresponding to the network parameter. This process realizes accurate rule mapping based on deep semantic understanding rather than simple keywords.

[0105] For example, the type of the first device A is Type A, and the configured network parameter is {ACL: allow IP address 192.168.1.1 to access}. The electronic device can filter out the rule set suitable for Type A devices or marked as general in the configuration rule library according to the configuration rule library, and take the rule set as the candidate rule pool for this matching. Then, the electronic device can convert the configured network parameter into a high-dimensional query vector by using the pre-trained language model, and perform similarity matching between the high-dimensional query vector and the configuration rule library to obtain the corresponding first configuration rule. For example, the first configuration rule can be {ACL should explicitly allow or deny access traffic of a specific source IP address, and should be located in the correct policy application}.

[0106] In S203, the electronic device can detect the configured network parameters according to the configuration detection model, the plurality of configured network parameters, and the plurality of first configuration rules, to obtain detection information corresponding to each configured network parameter.

[0107] The configuration detection model can be a trained artificial intelligence model with natural language understanding and logical reasoning capabilities. For example, the configuration detection model can be a large language model (LLM). The core function of the configuration detection model is to understand the semantics of network configuration and make compliance judgment and conflict reasoning according to the given rules.

[0108] The detection information can be a structured result obtained by analyzing a single or a group of network parameters. The detection information includes at least two parts: one is a semantic summary of the configuration (i.e., the summarized configuration information), which is used to summarize the function and key parameters; and the other is a diagnostic conclusion based on the first configuration rule (i.e., the detection conclusion corresponding to the group of parameters), which is used to point out the compliance status, existing conflicts or potential problems.

[0109] In some embodiments, the electronic device can detect the configured network parameters according to the configuration detection model, the plurality of configured network parameters, and the plurality of first configuration rules, to obtain detection information corresponding to each configured network parameter, by determining the association relationship of the plurality of configured network parameters, segmenting the plurality of configured network parameters according to the association relationship to obtain a plurality of network parameter sets, and determining the detection information corresponding to each network parameter set according to the configuration detection model, the plurality of network parameter sets, and the plurality of first configuration rules. The network parameter set includes a plurality of network parameters having an association relationship.

[0110] The association relationship can be the internal relationship between the configured network parameters in terms of function and logic. For example, the network parameters belonging to the same physical or logical interface (e.g., IP address) have an interface-level association relationship; and the network parameters serving the same security policy (e.g., ACL rule, route mapping, etc.) have a policy-level association relationship.

[0111] In some embodiments, the electronic device can automatically identify the associations by analyzing the context (e.g., configuration hierarchy, reference relationship, etc.) and semantics (e.g., type of network parameter) of the parameters. Specifically, in terms of syntax and structural context, for example, all parameters at the same configuration hierarchy (e.g., within the same configuration block) are considered to have strong associations; in terms of semantic and functional relevance, for example, network parameters functionally serve the same explicit goal (e.g., belong to the same ACL policy, etc.). In this way, this process can be achieved by parsing the tree structure of the configuration and identifying keywords of parameter types, thereby organizing discrete parameters into logically meaningful groups.

[0112] The set of network parameters can be a set of network parameters with strong association, i.e., the set of network parameters can be understood as a configuration fragment.

[0113] In some embodiments, based on identifying the association between parameters, the operation of performing segmentation processing is performed, i.e., according to the pre-defined functional module type and the hierarchical structure of the configuration, the entire configuration information is divided into multiple independent configuration fragments. The direct result and final output of this division process is multiple sets of network parameters, each of which contains multiple network parameters with a determined association between them, and the parameters between different sets do not have such strong association.

[0114] In this way, by this explicit rule based on module type and hierarchy, the network parameters of the configuration information can be automatically divided into multiple configuration fragments, each of which contains all related network parameters of a complete functional subset, thereby providing structured input for subsequent fine-grained analysis and concurrent diagnosis.

[0115] In some embodiments, the electronic device can determine the detection information corresponding to each set of network parameters based on the configuration detection model, the multiple sets of network parameters, and the multiple first configuration rules, according to the following implementation manner: for any one set of network parameters, the configured set of network parameters and the first configuration rule are integrated according to a preset prompt template to obtain an integrated set of network parameters and first configuration rule; the integrated set of network parameters and the first configuration rule are input into the configuration detection model to obtain configuration information of the set of network parameters and a detection result of configuration detection on the set of network parameters; and the detection information corresponding to each set of network parameters is determined according to the configuration information of the set of network parameters and the detection result of configuration detection on the set of network parameters.

[0116] The preset prompt template can be a pre-configured, structured text framework for standardizing the format of the analysis instruction input to the configuration detection model. The prompt template defines the analysis task, context description, placeholder for input data, and expected output format guide. Its role is to standardize the input of the model, ensuring that the model can clearly understand the need to perform analysis and diagnosis tasks on the configuration fragment as a whole.

[0117] The detection result can be the core diagnostic conclusion output by the configuration detection model after analyzing a set of network parameters (i.e., a configuration fragment). Specific content includes but is not limited to: the compliance status of the configuration fragment (e.g., conforming or violating rules), identified policy conflicts (e.g., conflicting with other configurations), and potential problems (e.g., security vulnerabilities, performance risks).

[0118] In some embodiments, the integration process can be understood as a process in which the electronic device, based on the preset prompt template, structurally assembles all configuration texts contained in a set of network parameters (i.e., a configuration fragment divided according to the association relationship) with the first configuration rule description text matched for the fragment.

[0119] Specifically, the preset prompt template is a well-designed text framework that contains explicit instructions (e.g., please analyze the following configuration fragment), positions for filling in the configuration set to be analyzed, positions for explaining the reference rules, and can pre-configure descriptions of configuration function modules. When integrating, the electronic device can fill in the overall configuration description of the current set of network parameters (i.e., the configuration fragment) and the first configuration rule text corresponding to the fragment into the specified positions of the template. The key to this process is that the input is based on the configuration fragment divided according to the association relationship as a complete semantic unit, ensuring that the task instruction received by the AI model naturally contains the context association information of the parameters, guiding the model to perform overall analysis.

[0120] For example, the integrated description can be "Please analyze the following network configuration fragment: This is an extended access control list (ACL) policy configuration fragment, and the specific configured network parameters are {allow source IP 196.168.1.1 to access target port 80}, and the first configuration rule to be referred to is {standard extended ACL should contain a clear deny-all rule to achieve default denial}. Based on the above information, generate the following content: 1. Configuration information summary: briefly explain the function and key parameters of this fragment; 2. Detection conclusion: judge its compliance according to the rules, and point out whether there are policy conflicts and other problems."

[0121] The above example shows how the integration processing integrates a piece of ACL policy composed of multiple associated rules as a whole semantic unit, combines it with a general compliance rule for such a piece, and guides the large model to conduct a holistic analysis through the framework of the template. After receiving this instruction, the model will understand that the structure of the entire ACL policy needs to be evaluated (not just a single rule), and check whether it ends with a deny-all entry according to the rule. This embodies how the template is used to ensure that the context of the association is passed to the model.

[0122] In some embodiments, the electronic device inputs the instruction generated by the above integration processing into the configuration detection model. Based on its understanding of network semantics and rules, the model conducts a reasoning analysis on the configuration piece as a whole. After the system parses its output, it generates detection information corresponding to the piece, which contains two parts: the configuration information, i.e., the summary of the piece, which describes the function, role and core parameters of the configuration piece as a whole; and the detection result, i.e., the diagnostic conclusion of the configuration piece, which is a diagnostic judgment based on the overall compliance, internal consistency and potential problems of the associated parameter set according to the first configuration rule. The electronic device combines this summary and conclusion to form the final detection information for the network parameter set. This result is directly derived from the overall assessment of the parameter set with associated relationships, achieving the unification of analysis granularity and diagnostic logic.

[0123] For example, based on the above example, the detection information of the configuration piece may be "1. Configuration information summary: This configuration piece is a configuration rule of an extended access control list (ACL), whose core role is to allow the source IP address 196.168.1.1 to access any destination address TCP 80 port (i.e., Web service). 2. Detection conclusion: The configuration piece has compliance defects. According to the requirement that "a standard extended ACL should contain a clear deny-all rule at the end", the current configuration piece is only an independent allow rule, and does not configure the final deny-all rule. This will result in ACL only allowing specified traffic in actual application, while defaulting all other unmatched traffic, which does not meet the security baseline principle of default denial, and has a major security problem."

[0124] In some embodiments, the electronic device can input multiple network parameter sets and multiple first configuration rules into corresponding configuration detection models respectively, and perform the above operations in parallel, thereby determining the detection information corresponding to each network parameter set and improving the efficiency of network configuration detection.

[0125] S204, determining the detection result of the first device according to the multiple detection information.

[0126] The detection result can be a final output of an overall diagnostic report for the first device. The detection result not only summarizes the independent diagnostic conclusions of each configuration segment, but also represents the dependency relationship between configuration parameters across different functional modules, policy conflicts and overall consistency problems within the first device based on the correlation analysis of information of all configuration segments, thereby providing the configuration health status and problem diagnosis from the perspective of the device as a whole.

[0127] In some embodiments, the electronic device can determine the detection result of the first device according to the plurality of detection information based on the following implementation: performing splicing processing on the plurality of detection information to obtain spliced plurality of detection information; and determining the detection result of the first device according to the configuration detection model and the spliced plurality of detection information.

[0128] The detection result of the first device is used to indicate the dependency relationship between the configured network parameters of the first device.

[0129] In some embodiments, the electronic device can sequentially organize the detection information (i.e., the abstract and the detection conclusion) of each configuration segment in a preset structured format. For example, the detection information of each segment can be spliced in turn according to the logical order of the functional modules (for example, interface first, then routing, and then security policy, etc.), or according to the logical level of configuration in the device, to form a comprehensive diagnostic context text with clear structure. This process ensures that all local conclusions and their context are presented completely to the subsequent analysis model.

[0130] For example, a simple splicing format can be: “[segment 1 abstract]; [segment 1 conclusion]. [segment 2 abstract]; [segment 2 conclusion], and so on, until the abstract and conclusion corresponding to the entire configured network parameter set are spliced and completed.

[0131] In some embodiments, the electronic device can input the comprehensive diagnostic context text generated by the above splicing into the configuration detection model together with instructions intended to guide global analysis (for example, the instructions can be “please analyze whether there are cross-module policy conflicts, circular dependencies, etc. based on the diagnostic abstract and conclusion of each configuration segment”).

[0132] The configuration detection model understands the functions described in each segment abstract and correlates the specific problems pointed out in each segment conclusion, thereby reasoning and identifying the configuration dependency relationship and potential conflicts across functional modules. Then, the configuration detection model outputs a detection result of the first device, which is a comprehensive diagnostic report that clearly indicates the overall compliance status of the device, the key cross-module conflicts found, the core problem items and the analysis conclusions of the configuration dependency relationship.

[0133] For example, the summary and conclusion of configuration fragment A (ACL configuration) are: a rule "allow IP address 192.168.1.100 to access port 80" is configured; the conclusion is "syntax correct". The summary and conclusion of configuration fragment B (ACL configuration) are: a rule "deny IP address 192.168.1.100 to access any port" is configured; the conclusion is "syntax correct".

[0134] The configuration detection model identifies that the two rules have a direct logical conflict for the same source IP address (192.168.1.100), and because the rule order or range is not explicitly defined, it may cause the access control policy to be invalid or unpredictable.

[0135] Therefore, the device-level detection result output by the model will clearly indicate: "policy conflict across configuration fragments is found. The access policy for host 192.168.1.100 is contradictory: it allows it to access the Web service (port 80) in one rule, and denies all access in another rule. This may cause confusion in the security policy, and it is recommended to review and unify the policy definition."

[0136] The network configuration detection method, device, equipment, storage medium and program product provided by the present application, by acquiring a configuration rule library, the type of a first device and a plurality of configured network parameters in the first device, matching the first configuration rule corresponding to each parameter from the rule library based on the device type and the configured parameters, completing the detection by a configuration detection model in combination with the parameters and the rules, and outputting the detection result of the first device. In the above method, in the knowledge base construction stage, the configuration rules of multiple manufacturers are extracted into pure text through image recognition and format conversion technology, and are stored in a vector database after vectorization; in the diagnosis and analysis stage, the configuration file to be diagnosed is divided into functional module fragments, each fragment is matched with the corresponding rule in the knowledge base to generate a local diagnosis summary, realizing the configuration verification logic of unified adaptation to devices of different manufacturers, being able to process long text configuration information in segments, significantly reducing the inference time of the large model, and improving the overall processing speed by parallel diagnosis of multiple fragments; and by integrating the local and global diagnosis results, a comprehensive report containing detailed problems and overall logic is generated. The process enhances the inference accuracy of the model through a dynamic knowledge base, balances efficiency and comprehensiveness through segmentation and summarization strategies, and supports unified adaptation to devices of different manufacturers.

[0137] Figure 3 The process diagram for determining the configuration modification suggestion provided by the present application is shown in FIG. 1, and the embodiment, after determining the detection result of the first device according to the configuration detection model and the spliced plurality of detection information, the method for determining the configuration modification suggestion according to the configuration state of the network parameter is described in detail, which comprises: Figure 3 ​

[0138] S301, determining a detection state of each configured network parameter according to a detection result of the first device.

[0139] The detection state can be a detection normal state or a detection abnormal state.

[0140] The detection normal state is used to indicate that the configuration of the network parameter is analyzed to be in line with the relevant rules and no logical conflict with other parameters is found.

[0141] The detection abnormal state is used to indicate that the configuration of the network parameter is identified to have a problem, for example, not in line with the compliance rules, in policy conflict with other parameters, or belong to incomplete / invalid configuration.

[0142] S302, when the detection state is the detection abnormal state, obtaining an abnormal reason of a target network parameter, and determining a configuration modification suggestion of the target network parameter according to the abnormal reason.

[0143] The abnormal reason can be a specific root cause description that leads to the network parameter being determined as the detection abnormal state, which is usually directly derived from the detection result part output by the configuration detection model in the segment diagnosis or global analysis stage. For example, the abnormal reason can be that the ACL rule calls an undefined IP address.

[0144] In some embodiments, the electronic device can locate the target network parameter in the detection abnormal state from the global detection result of the first device and the detection information of each configuration segment. By analyzing and extracting the diagnosis output text associated with the parameter, especially the explicit "non-compliance", "conflict", "missing", "undefined" and other key conclusions and their context, the text information is structured as the abnormal reason of the parameter. For example, from the conclusion "the next hop IP address of this static route points to an unreachable interface", the abnormal reason extracted is "the next hop points to an unreachable interface".

[0145] In some embodiments, the electronic device can generate a specific configuration modification suggestion by reasoning based on the abnormal reason and historical repair cases in the preset policy library (including knowledge graph), that is, map the abnormal reason to an executable configuration operation. For example, define the IP address in the configuration information of the network parameter corresponding to the ACL rule.

[0146] In some embodiments, the electronic device can update the configuration rule library based on the following implementation manner: obtaining a newly added or modified configuration rule; performing verification processing on the newly added or modified configuration rule to obtain a verification result; and when the verification result is verification passed, updating the configuration rule library.

[0147] Specifically, the electronic device obtains the newly added or modified configuration rules, which are usually in the form of text and come from an externally input specification file or an update request submitted by a technician; the new rules are checked, which includes parsing the format, checking the integrity of the logical structure, and verifying whether there is a semantic conflict or repetition with the existing rules in the rule library. After the checking is completed, the corresponding checking result can be obtained to indicate whether the new rule is qualified. When the checking result is that the checking is passed, the electronic device can perform vectorization conversion on the configuration rule that meets the requirements and store it in the vector database, thereby completing the update of the configuration rule library and enabling it to provide the latest basis for subsequent diagnostic analysis.

[0148] The configuration knowledge base supports regular updates (for example, according to the latest configuration specifications published by manufacturers), which can ensure the timeliness of the diagnostic rules and avoid misjudgments caused by specification changes.

[0149] The network configuration detection method, device, equipment, storage medium and program product provided by the present application introduce a configuration detection model and a vectorized configuration rule library to perform segmented diagnosis and global comprehensive analysis on the configuration of the device to be detected, and automatically identify abnormal parameters, analyze abnormal reasons, and generate configuration modification suggestions based on the diagnostic results, while supporting dynamic checking and updating of the configuration rule library. In the above method, the electronic device realizes automatic deep analysis of complex configurations of multiple manufacturers through segmented processing and modeling diagnosis mechanism, can effectively find cross-function module strategy conflicts and compliance problems that are difficult to identify by manual and traditional tools, significantly improves the accuracy and comprehensiveness of network configuration diagnosis; through the intelligent repair suggestion generation based on the diagnostic state and abnormal reason, the traditional long-cycle process of "detection-manual troubleshooting-repair" is compressed into a closed-loop automatic suggestion output, greatly improving the operation and maintenance response efficiency and problem solving accuracy; at the same time, through the dynamic updating mechanism of the configuration rule library, it ensures that the diagnostic basis can evolve continuously with the changes of network specifications and business requirements, and guarantees the long-term applicability and timeliness of the system. This method can adapt to cloud resource pool network environments of different scales and complexities, improve the automation and intelligence level of configuration management, and provide reliable technical support for the safe and stable operation of the network.

[0150] Figure 4 A process schematic diagram of a configuration rule library construction method provided by an embodiment of the present application. Please refer to Figure 4 The method can include:

[0151] The construction process of the configuration rule library starts from obtaining network device configuration rule information from different manufacturers, and the information sources can be various formats of text content including PDF, Word documents, and pictures (S401); data preprocessing is performed on the obtained rule information, and image recognition and format conversion techniques are used to collect and extract the text in different format files into a unified plain text format, and then the plain text content is converted into a numerical vector, i.e., vectorization (S402), and the information data that has been vectorized in the previous step is stored in the vector database, i.e., the configuration rule library (S403);

[0152] The configuration rule library module of the present scheme stores the device configuration rules and other characteristic information of different manufacturers in the vector database. In the network configuration diagnosis process, the module provides actual basis and characteristic rule support, effectively avoids the illusion problem of large language models in AI agents, and thus maximizes the accuracy of configuration diagnosis.

[0153] Figure 5 Another process schematic diagram of the network configuration detection method provided by the embodiments of the present application is provided. Please refer to Figure 5 The method can include:

[0154] The process of network configuration detection starts with configuration information collection, which mainly obtains network configuration information (corresponding to the type of the first device and a plurality of configured network parameters) that needs to be diagnosed. The technician inputs the network configuration information that needs to be diagnosed into the algorithm in an artificial manner. The configuration data can be input into the algorithm in the form of pure text content or a file containing network device configuration data (S501); the algorithm preprocesses the input configuration data, and the core is to extract the effective content in the configuration file (S502). During data preprocessing, the algorithm automatically matches the device with the characteristic information in the configuration knowledge base (corresponding to the configuration rule library) according to the uploaded configuration data. For example, if the operation and maintenance personnel upload the configuration data of a certain model of router, the algorithm will extract the configuration characteristic rules of the same model of router from the configuration knowledge base (S503); integrate the configuration information to be diagnosed and the characteristic information in the configuration knowledge base for standardized processing; then input the standardized data into the large language model for analysis and diagnosis to obtain the summary and diagnosis conclusion of each configuration fragment (S504); output the configuration diagnosis result to obtain the global diagnosis conclusion (S505).

[0155] Wherein, in order to solve the problem of low inference efficiency and large model illusion caused by complex configuration information, the embodiment of the application adopts a segmented diagnosis and summary scheme, which specifically includes: according to the logical correlation and functional modules (such as ACL configuration, interface configuration, etc.) of the configuration instructions, the overall configuration information is divided into several segments; with the help of rules and feature information in the configuration knowledge base, concurrent diagnosis is performed on each segment; the large language model generates a summary of each segment, and the summary content includes configuration role, parameters and main diagnostic conclusions; the diagnostic results and summaries of all segments are spliced and input into the large language model to analyze the logical conflicts and configuration consistency problems across functional modules from a global perspective, forming a global diagnostic result. Through this module, the configuration information compliance diagnosis of network devices of different manufacturers can be realized. This module not only ensures the normal operation of network devices in the resource pool, but also improves the network configuration change efficiency of network operation and maintenance personnel.

[0156] On the basis of large model inference diagnosis, the application adds a configuration knowledge base auxiliary function, which automatically identifies the device manufacturer and model through the input network configuration information, matches the corresponding configuration feature information from the knowledge base, and significantly improves the accuracy of the diagnostic results. Moreover, through the above operation, for network configuration information, both the accurate analysis of the details of each configuration module and the rationality of the overall configuration logic can be achieved. The AI agent finally integrates the segmented diagnosis and global diagnosis results, removes redundant information, supplements the content, and forms a comprehensive and accurate router network configuration diagnosis result. Through the diagnosis report, the operation and maintenance personnel can not only obtain the overall diagnostic result of the configuration information of the network device, but also obtain the diagnostic details of the configuration information of a certain functional module.

[0157] The network configuration detection method, device, equipment, storage medium and program product provided by the application, by providing a network configuration diagnosis algorithm based on an AI agent, through a configuration knowledge base module and a network configuration diagnosis algorithm module, aims to solve the pain points of low network configuration diagnosis efficiency and insufficient accuracy in the prior art. The application can focus on the diagnosis and audit of network device configuration information, and is mainly applied to two types of scenes: one is the regular audit verification of online network device configuration; the second is the audit and verification of the global and local validity and rationality of configuration information when the network configuration is changed. At the same time, it is compatible with the configuration checking requirements of network devices of multiple manufacturers, pre-configures the device configuration knowledge base of different manufacturers, and supports dynamic updating to ensure the timeliness of the configuration rules. In the above method, based on the reasoning ability of the large language model, a configuration information knowledge base module is added: on the one hand, it effectively avoids the illusion problem that may be caused by the large model; on the other hand, combined with the dynamic maintenance mechanism, the timeliness of the configuration rules and feature information is ensured, which provides continuous guarantee for the diagnosis accuracy; and for hundreds of configuration file information, a strategy combining segmented diagnosis and overall diagnosis is proposed, through fine processing of local configuration detail verification and global configuration consistency checking, not only the precise analysis of scattered configuration items is realized, but also the coherence of the overall configuration logic is guaranteed, which significantly improves the accuracy and comprehensiveness of the diagnosis result. In addition, the diagnosis report output by the model has multi-level presentation characteristics: not only the overall diagnosis conclusion of the network configuration is included, but also the diagnosis details of each functional module are presented in detail, which provides a solid decision basis for subsequent configuration optimization and adjustment work, and helps to improve the operation and maintenance efficiency.

[0158] Figure 6 The structure diagram of the network configuration detection device provided by the application is shown in Figure 6 The network configuration detection device 60 provided by the embodiment includes an acquisition module 61, a first determination module 62, a detection module 63 and a second determination module 64, wherein,

[0159] The acquisition module 61 is configured to acquire a configuration rule library, a type of a first device and a plurality of configured network parameters in the first device, and the configuration rule library includes configuration rules corresponding to network parameters of a plurality of devices.

[0160] The first determination module 62 is configured to determine, according to the type of the first device and the plurality of configured network parameters, first configuration rules corresponding to each configured network parameter in the configuration rule library.

[0161] The detection module 63 is configured to detect the configured network parameters according to a configuration detection model, the plurality of configured network parameters and the plurality of first configuration rules, to obtain detection information corresponding to each configured network parameter.

[0162] The second determining module 64 is configured to determine the detection result of the first device according to the plurality of detection information.

[0163] The network configuration detection device provided by the embodiments of the present application can implement the technical solutions shown in the method embodiments, and has similar implementation principles and beneficial effects, which will not be repeated here.

[0164] In a possible implementation, the obtaining module 61 is specifically configured to:

[0165] obtain configuration files corresponding to network parameters of a plurality of devices;

[0166] perform parsing processing on the plurality of configuration files to obtain a plurality of configuration rules;

[0167] perform vectorization processing on the plurality of configuration rules, and determine a configuration rule library according to the plurality of configuration rules after vectorization.

[0168] In a possible implementation, the detecting module 63 is specifically configured to:

[0169] determine an association relationship of a plurality of configured network parameters;

[0170] perform segmentation processing on the plurality of configured network parameters according to the association relationship to obtain a plurality of network parameter sets, wherein each network parameter set includes a plurality of network parameters having an association relationship;

[0171] determine detection information corresponding to each network parameter set according to the configuration detection model, the plurality of network parameter sets, and the plurality of first configuration rules.

[0172] In a possible implementation, the detecting module 63 is specifically configured to:

[0173] for any one network parameter set, perform integration processing on the configured network parameter set and the first configuration rule according to a preset prompt template to obtain an integrated network parameter set and first configuration rule;

[0174] input the integrated network parameter set and the first configuration rule into the configuration detection model to obtain configuration information of the network parameter set and a detection result of configuration detection on the network parameter set;

[0175] determine detection information corresponding to each network parameter set according to the configuration information of the network parameter set and the detection result of configuration detection on the network parameter set.

[0176] In a possible implementation, the second determining module 64 is specifically configured to:

[0177] perform splicing processing on the plurality of detection information to obtain spliced plurality of detection information;

[0178] According to the configuration detection model and the spliced plurality of detection information, a detection result of the first device is determined, and the detection result of the first device is used to indicate a dependency relationship between the configured network parameters of the first device.

[0179] In a possible implementation, the apparatus further includes a first processing module, which is specifically configured to:

[0180] According to the detection result of the first device, a detection state of each configured network parameter is determined, and the detection state can be a normal detection state or an abnormal detection state;

[0181] When the detection state is the abnormal detection state, an abnormal reason of a target network parameter is obtained, and according to the abnormal reason, a configuration modification suggestion of the target network parameter is determined.

[0182] In a possible implementation, the apparatus further includes a second processing module, which is specifically configured to:

[0183] An added or modified configuration rule is obtained;

[0184] The added or modified configuration rule is subjected to a verification process to obtain a verification result;

[0185] When the verification result is a verification pass, the configuration rule library is updated.

[0186] Figure 7 The structure of the electronic device provided in the present application is shown in the figure. As shown in the figure, the electronic device 70 provided in the present embodiment includes at least one processor 71 and a memory 72. Optionally, the electronic device 70 further includes a communication component 73. Wherein, the processor 71, the memory 72 and the communication component 73 are connected through a bus. Figure 7

[0187] In the specific implementation process, the at least one processor 71 executes the computer execution instructions stored in the memory 72, so that the at least one processor 71 executes the above-mentioned method.

[0188] The specific implementation process of the processor 71 can refer to the above-mentioned method embodiment, which has similar implementation principles and technical effects, and will not be described here in detail.

[0189] ​In the above embodiments, it should be understood that the processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method disclosed in combination with the application can be directly embodied as hardware processor execution, or executed by a combination of hardware and software modules in the processor.

[0190] The memory can include a random access memory (RAM), and can also include a non-volatile memory (NVM), such as at least one disk memory.

[0191] The bus can be an industry standard architecture (ISA) bus, a peripheral component (PCI) bus, or an extended industry standard architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of the present application does not limit to only one bus or one type of bus.

[0192] The present application also provides a computer program product, comprising a computer program, which, when executed by a processor, implements the above method.

[0193] The present application also provides a computer readable storage medium, which stores computer execution instructions, and when a processor executes the computer execution instructions, the above method is implemented.

[0194] The above readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0195] An example readable storage medium is coupled to the processor such that the processor can read information from the readable storage medium and can write information to the readable storage medium. Of course, the readable storage medium can also be a part of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processor and the readable storage medium can also exist as discrete components in the device.

[0196] The division of units is only a logical functional division, and in actual implementation, there can be another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interfaces, devices or units, and can be electrical, mechanical or other forms.

[0197] The units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, can be located in one place, or can be distributed on a plurality of network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0198] In addition, the functional units in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit.

[0199] If the functions are realized in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application or the part of the present application that essentially contributes to the prior art or the part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method of each embodiment of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various program code storage media.

[0200] Those skilled in the art can understand that all or part of the steps of the above-mentioned method embodiments can be completed by program instruction related hardware. The foregoing program can be stored in a computer readable storage medium. The program executes to perform the steps of the above-mentioned method embodiments; and the foregoing storage medium includes various media capable of storing program codes, such as ROM, RAM, magnetic disk, or optical disk.

[0201] Finally, it should be noted that other embodiments of the present application will readily occur to those skilled in the art upon consideration of the specification and practice of the present application disclosed herein. The present application is intended to include all such variations as fall within the general scope of the application, and includes the generic principles disclosed and the best mode known to the inventors to be currently practiced as well as variations thereof, without departing from the scope of the present application as defined by the claims. The specification and examples give the best application of the present application as currently known, and together with the description of the application serve to best illustrate the principles of the application. The scope of the application is expressly set forth by the claims.

Claims

1. A network configuration detection method, characterized in that, include: The configuration rule base, the type of the first device, and multiple configured network parameters in the first device are obtained. The configuration rule base includes configuration rules corresponding to the network parameters of multiple devices. Based on the type of the first device and the plurality of configured network parameters, a first configuration rule corresponding to each configured network parameter is determined in the configuration rule base; Based on the configured detection model, the multiple configured network parameters, and the multiple first configuration rules, the configured network parameters are detected to obtain the detection information corresponding to each configured network parameter. The detection result of the first device is determined based on multiple detection information.

2. The method according to claim 1, characterized in that, Obtain the configuration rule base, including: Retrieve the configuration files corresponding to the network parameters of multiple devices; Multiple configuration files are parsed and processed to obtain multiple configuration rules; The multiple configuration rules are vectorized, and the configuration rule library is determined based on the vectorized configuration rules.

3. The method according to claim 1, characterized in that, Based on the configured detection model, the multiple configured network parameters, and the multiple first configuration rules, the configured network parameters are detected to obtain detection information corresponding to each configured network parameter, including: Determine the relationships between the multiple configured network parameters; Based on the association, the multiple configured network parameters are segmented to obtain multiple network parameter sets, which include multiple network parameters that have an association relationship. Based on the configured detection model, the multiple network parameter sets, and the multiple first configuration rules, the detection information corresponding to each network parameter set is determined.

4. The method according to claim 3, characterized in that, Based on the configured detection model, the multiple network parameter sets, and the multiple first configuration rules, the detection information corresponding to each network parameter set is determined, including: For any set of network parameters, the configured set of network parameters and the first configuration rule are integrated according to a preset prompt template to obtain an integrated set of network parameters and the first configuration rule. The integrated network parameter set and the first configuration rule are input into the configuration detection model to obtain the configuration information of the network parameter set and the detection result of the configuration detection of the network parameter set. Based on the configuration information of the network parameter set and the detection results of configuration detection of the network parameter set, the detection information corresponding to each network parameter set is determined.

5. The method according to claim 1, characterized in that, Based on multiple detection information, the detection result of the first device is determined, including: The multiple detection information is spliced ​​together to obtain spliced ​​multiple detection information; Based on the configured detection model and the spliced ​​multiple detection information, the detection result of the first device is determined, and the detection result of the first device is used to indicate the dependency relationship between the network parameters configured by the first device.

6. The method according to claim 5, characterized in that, After determining the detection result of the first device based on the configured detection model and the stitched multiple detection information, the method includes: Based on the detection results of the first device, the detection status of each configured network parameter is determined, and the detection status can be a normal detection status or an abnormal detection status. When the detection state is an abnormal state, the cause of the abnormality of the target network parameters is obtained, and based on the cause of the abnormality, a configuration modification suggestion for the target network parameters is determined.

7. The method according to claim 1, characterized in that, After determining the detection result of the first device based on multiple detection information, the method further includes: Get the newly added or modified configuration rules; The newly added or modified configuration rules are validated to obtain the validation results; When the verification result is successful, the configuration rule base is updated.

8. A network configuration detection device, characterized in that, include: The module comprises an acquisition module, a first determination module, a detection module, and a second determination module, wherein, The acquisition module is used to acquire a configuration rule base, the type of the first device, and multiple configured network parameters in the first device. The configuration rule base includes configuration rules corresponding to the network parameters of multiple devices. The first determining module is configured to determine, based on the type of the first device and the plurality of configured network parameters, a first configuration rule corresponding to each configured network parameter in the configuration rule base; The detection module is used to detect the configured network parameters according to the configured detection model, the plurality of configured network parameters and the plurality of first configuration rules, and to obtain the detection information corresponding to each configured network parameter. The second determining module is used to determine the detection result of the first device based on multiple detection information.

9. An electronic device, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-7.

11. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method described in any one of claims 1-7.

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