Anti-wall-jumping control automation test method and system based on multi-dimensional identification rules

Abstract

This application provides an automated testing method and system for circumvention control based on multi-dimensional identification rules. The method includes acquiring the configuration information of the network system under test and generating a rule verification list based on the configuration information; the rule verification list is used to mark specific test indicators of the network system under test; generating a test case set based on the rule verification list; performing scenario simulation based on the test case set and extracting the circumvention system response dataset during the scenario simulation; performing full-dimensional analysis based on the circumvention system response dataset to obtain a test report; the test report includes rule vulnerabilities, performance bottlenecks, and optimization suggestions; generating an optimized test case set based on the rule vulnerabilities in the test report, performing iterative testing until preset indicators are met, and adjusting parameters based on the configuration information of the network system under test according to the performance bottlenecks and optimization suggestions. This application solves the limitations of existing circumvention identification technologies through the above solution.

Description

Technical Field

[0001] This invention relates to the field of network communication technology, and in particular to an automated testing method and system for circumvention control based on multi-dimensional identification rules. Background Technology

[0002] In the field of cybersecurity, circumvention systems are key technological components for maintaining network perimeter security and ensuring the effective implementation of regulatory policies. To ensure their protective effectiveness, comprehensive and accurate automated testing and evaluation schemes are necessary. However, current automated testing technologies for circumvention systems reveal systemic shortcomings when dealing with increasingly complex and varied network penetration behaviors, making it difficult to scientifically evaluate the overall capabilities of these systems.

[0003] The main shortcomings of existing technical solutions are reflected in the following aspects: First, there are significant limitations in the breadth and adaptability of testing scenarios. Mainstream testing methods often design test cases for known, fixed-pattern circumvention tools (such as VPNs using specific protocols), resulting in singular and rigid simulation scenarios. Faced with constantly evolving network penetration technologies, such as the mixed use of multiple proxy protocols, the splitting and reassembling of communication tunnels, and the use of virtual network devices to spoof traffic characteristics, existing testing solutions lack effective simulation and coverage capabilities. This leads to outdated test scenarios that fail to reflect the full picture of circumvention technologies in real-world network environments, leaving the effectiveness of anti-circumvention systems unverified against new or composite circumvention methods.

[0004] Secondly, the depth and scope of testing and verification are severely lacking. Most existing tests only focus on the final result of whether the anti-circumvention system "successfully blocks" attacks, which is a superficial functional verification. The testing process fails to delve into the core identification rules inherent in the system, such as the comprehensive judgment logic based on multiple dimensions like network address, behavioral patterns, device fingerprints, and communication protocol characteristics. Due to the lack of specialized testing on the completeness and accuracy of the rules themselves, it is difficult to discover and locate logical vulnerabilities, feature coverage blind spots, or conflicts within the rule set. This makes it so that even if the system can block some known threats, its rule foundation remains fragile and can be bypassed by carefully crafted traffic.

[0005] Secondly, there is a lack of testing for dynamic countermeasures and continuous protection capabilities. Real-world circumvention behavior is significantly adversarial and dynamic, such as frequently changing connection nodes and adjusting protocol interaction parameters in real time to evade feature matching. Existing testing schemes are mostly static or short-term tests, which cannot effectively simulate this continuous and dynamically changing evasion behavior. Therefore, it is impossible to evaluate the real-time response capability, state maintenance capability, and protection stability of the circumvention system under long-term operation and continuous detection pressure. The system's protection effectiveness in dynamic countermeasure scenarios has become a blind spot in testing.

[0006] Finally, there are shortcomings in the design for system reliability and environmental suitability testing. A mature anti-circumvention system not only needs a high detection rate of circumvention behavior but also an extremely low false positive rate for normal business operations. Existing tests lack a fine-grained design for the boundary scenarios between "normal" and "circumvention" behaviors, making it difficult to accurately verify the system's false positive level in complex network traffic. In addition, tests are often conducted in a single or ideal network environment, failing to fully consider and adapt to the differences in latency, jitter, and background noise in different network environments such as public networks, private networks, and mobile access networks. This leads to doubts about the universality of test conclusions, and the system may become incompatible after actual deployment. Summary of the Invention

[0007] This application provides an automated testing method and system for circumvention control based on multi-dimensional recognition rules, in order to solve the limitations of existing circumvention recognition technologies.

[0008] In a first aspect, this application provides an automated testing method for circumvention control based on multi-dimensional recognition rules, the method comprising: Obtain the configuration information of the network system to be tested, and generate a rule verification list based on the configuration information; the rule verification list is used to mark the specific test indicators of the network system to be tested. A test case set is generated based on the rule verification list; Scenario simulation is performed based on the test case set, and the response dataset of the circumvention system is extracted during the scenario simulation; the scenario simulation includes injecting circumvention scenario features; A comprehensive analysis of the circumvention system's response dataset was conducted to obtain a test report, which included rule vulnerabilities, performance bottlenecks, and optimization suggestions. Based on the rule vulnerabilities identified in the test report, an optimized test case set is generated and iteratively tested until preset indicators are met. Then, the configuration information of the network system under test is adjusted according to the performance bottlenecks and optimization suggestions.

[0009] Preferably, the step of generating a rule verification list based on the configuration information includes: Construct a recognition rule model; The configuration information is input into the recognition rule model to map the rules corresponding to the configuration information into testable verification points and generate the rule verification list.

[0010] Preferably, the identification rule model is constructed based on four dimensions: IP, behavior, device, and protocol.

[0011] Preferably, the step of generating a test case set based on the rule verification list includes: Build a scene template library; The test case set is generated based on the rule verification list, the constructed scenario template library, and the scenario-driven algorithm; the test case set includes three categories: unauthorized circumvention, normal access, and ambiguous boundaries.

[0012] Preferably, the scenario template library includes basic proxies, VPN tunnels, virtual environments, encrypted tunnels, hybrid evasion, and boundary scenarios.

[0013] Preferably, the test case set is sorted according to the probability of scenario occurrence, rule weight, and security risk level to complete the priority.

[0014] Preferably, the step of performing scenario simulation based on the test case set and extracting the circumvention system response dataset during the scenario simulation includes: Build a multi-protocol simulation engine; The test case set is executed according to the security risk level corresponding to the test case set, and during the execution process, circumvention scenario features are injected for dynamic circumvention scenarios to extract the circumvention system response dataset when the network system under test responds to circumvention.

[0015] Preferably, the step of performing a full-dimensional analysis based on the circumvention system response dataset includes: Construct a three-layer verification model; The three-layer verification model is used to perform a full-dimensional analysis of the response dataset of the circumvention system to statistically analyze the identification accuracy, false negative rate, and false positive rate, and to generate the test report.

[0016] Preferably, the three-layer verification model is constructed based on three levels: rule matching, protection actions, and performance and stability.

[0017] Secondly, this application also provides an automated testing system for circumvention control based on multi-dimensional recognition rules. The system is applicable to any of the methods described above, and includes: The rule parsing and modeling module is configured to obtain the configuration information of the network system to be tested and generate a rule verification list based on the configuration information; the rule verification list is used to mark the specific test indicators of the network system to be tested. The scenario generation and test case design module is configured to generate a test case set based on the rule verification list; the test case set is sorted according to the scenario occurrence probability, rule weight, and security risk level priority. A high-fidelity simulation and execution module is configured to perform scenario simulation based on the test case set and extract the circumvention system response dataset during the scenario simulation process; the scenario simulation includes injecting circumvention scenario features. A multi-dimensional verification and analysis module is configured to perform a full-dimensional analysis based on the response dataset of the circumvention system to obtain a test report; the test report includes rule vulnerabilities, performance bottlenecks, and optimization suggestions. An iterative optimization module is configured to generate an optimized test case set based on the rule vulnerabilities in the test report, perform iterative testing until preset indicators are met, and adjust the configuration information of the network system under test according to the performance bottleneck and the optimization suggestions.

[0018] As described above, this application provides an automated testing method and system for circumvention control based on multi-dimensional identification rules. The method includes acquiring configuration information of the network system under test and generating a rule verification list based on the configuration information. The rule verification list is used to annotate specific test indicators of the network system under test. A test case set is generated based on the rule verification list. Scenario simulation is performed based on the test case set, and a circumvention system response dataset is extracted during the scenario simulation. The scenario simulation includes injecting circumvention scenario features. A full-dimensional analysis is performed based on the circumvention system response dataset to obtain a test report. The test report includes rule vulnerabilities, performance bottlenecks, and optimization suggestions. An optimized test case set is generated based on the rule vulnerabilities in the test report, and iterative testing is performed until preset indicators are met. The configuration information of the network system under test is then adjusted based on the performance bottlenecks and the optimization suggestions. This application solves the limitations of existing circumvention identification technologies through the above solution. Attached Figure Description

[0019] To more clearly illustrate the technical solution of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a flowchart of the automated testing method for circumvention control based on multi-dimensional recognition rules in this application; Figure 2 This is a schematic diagram of the multi-dimensional recognition rule model in this application; Figure 3 This is a schematic diagram of the automated testing system for circumvention control based on multi-dimensional recognition rules, as described in this application. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] It should be noted that the brief descriptions of terms in this application are only for the convenience of understanding the embodiments described below, and are not intended to limit the embodiments of this application. Unless otherwise stated, these terms should be understood in their ordinary and common meaning.

[0023] It should be noted that, in this application, the terms "exemplary" or "for example" are used to indicate that something is being described as an example, illustration, or illustration. Any embodiment or design described as "exemplary" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or design solutions. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0024] Figure 1 This is a flowchart of the automated testing method for circumvention control based on multi-dimensional recognition rules in this application.

[0025] Figure 2 This is a schematic diagram of the multi-dimensional recognition rule model in this application.

[0026] See Figure 1 as well as Figure 2 As can be seen, this embodiment provides an automated testing method for circumvention control based on multi-dimensional recognition rules, the method including: S1, obtain the configuration information of the network system to be tested, and generate a rule verification list based on the configuration information; the rule verification list is used to mark the specific test indicators of the network system to be tested.

[0027] Specifically, in this embodiment, the configuration information (identification rule type, parameters, and protection actions) of the network system to be tested is received, an identification rule model is constructed based on four dimensions: IP, behavior, device, and protocol, the configuration information is input into the identification rule model, the rules corresponding to the configuration information are mapped to testable verification points, and a rule verification list containing specific test indicators is generated; the identification rule model is constructed based on the four dimensions of IP, behavior, device, and protocol.

[0028] The method further includes: S2, Generate a test case set based on the rule checklist.

[0029] Specifically, in this embodiment, a scenario template library covering six major categories of core circumvention technologies and their variations is constructed. Based on the scenario-driven algorithm, three types of test case sets are generated: illegal circumvention, normal access, and ambiguous boundaries. The test cases are prioritized according to the probability of scenario occurrence, rule weight, and security risk level. The scenario template library includes basic proxy, VPN tunnel, virtual environment, encrypted tunnel, hybrid circumvention, and boundary scenario.

[0030] The method further includes: S3, perform scenario simulation based on the test case set, and extract the circumvention system response dataset during the scenario simulation; the scenario simulation includes injecting circumvention scenario features.

[0031] Specifically, in this embodiment, a multi-protocol simulation engine is built to achieve high-fidelity simulation of circumvention tools, network environments, device fingerprints, and protocol features. Test cases are executed according to priority, scenario features are injected in real time, and system response data is captured. Feature changes are continuously injected for dynamic circumvention scenarios to test real-time response capabilities. The scenario features are injected requests, resulting in a circumvention system response dataset.

[0032] The method further includes: S4. Perform a full-dimensional analysis based on the response dataset of the circumvention system to obtain a test report; the test report includes rule vulnerabilities, performance bottlenecks, and optimization suggestions.

[0033] Specifically, in this embodiment, a three-layer verification model is constructed, which includes rule matching, protection actions, and performance and stability. The test results are analyzed in all dimensions, and core indicators such as accuracy, false negative rate, and false positive rate are statistically analyzed to generate a test report containing rule vulnerabilities, performance bottlenecks, and optimization suggestions.

[0034] The method further includes: S5. Based on the rule vulnerabilities in the test report, generate an optimized test case set, perform iterative testing until the preset indicators are met, and adjust the configuration information of the network system under test according to the performance bottleneck and the optimization suggestions.

[0035] Specifically, in this embodiment, the system automatically generates optimized test case sets based on rule vulnerabilities in the test report, supports iterative testing until preset indicators are met, and provides a rule parameter tuning simulation function to verify the system's recognition effect after parameter adjustment.

[0036] It should be noted that extending the multi-dimensional recognition rule verification and high-fidelity scenario simulation technology of this embodiment to the automated testing of network security protection systems such as network attack protection and malicious crawler interception only requires adjusting the scenario template library and recognition rule verification points to adapt it.

[0037] It should be noted that, based on the existing library of six major categories of circumvention scenario templates, scenario templates for new circumvention technologies such as AI-generated fake circumvention and blockchain node proxy can be added. By upgrading the scenario-driven algorithm, simulation tests of new circumvention behaviors can be achieved.

[0038] It should be noted that by connecting to the cybersecurity big data platform, test data is integrated with actual circumvention attack data, enabling real-time updates of the scenario template library and improving the realism and relevance of the tests.

[0039] Figure 3 This is a schematic diagram of the automated testing system for circumvention control based on multi-dimensional recognition rules, as described in this application.

[0040] See Figure 3 Therefore, this embodiment also provides an automated testing system for circumvention control based on multi-dimensional recognition rules, used to execute the above method. The system includes: The rule parsing and modeling module is configured to obtain the configuration information of the network system to be tested and generate a rule verification list based on the configuration information; the rule verification list is used to mark the specific test indicators of the network system to be tested.

[0041] Specifically, in this embodiment, the rule parsing and modeling module receives configuration information, constructs a multi-dimensional rule model, and generates a verification list, supporting the addition / modification / import and export of rules, and adapting to the rule systems of different vendors' anti-circumvention systems.

[0042] The system also includes: The scenario generation and test case design module is configured to generate a test case set based on the rule verification list; the test case set is sorted according to the probability of scenario occurrence, rule weight, and security risk level.

[0043] Specifically, in this embodiment, the scenario generation and test case design module has a built-in library of six major categories of circumvention scenario templates (supporting template updates / custom additions), and generates three types of test case sets through a scenario-driven algorithm and completes priority sorting.

[0044] The system also includes: A high-fidelity simulation and execution module is configured to perform scenario simulation based on the test case set and extract the circumvention system response dataset during the scenario simulation process; the scenario simulation includes injecting circumvention scenario features.

[0045] Specifically, in this embodiment, the high-fidelity simulation and execution module includes a multi-protocol simulation engine and a network environment / device fingerprint / protocol feature simulation unit, which realizes high-fidelity simulation of diverse circumvention scenarios, test case execution, and response data capture.

[0046] The system also includes: A multi-dimensional verification and analysis module is configured to perform a full-dimensional analysis based on the response dataset of the circumvention system to obtain a test report; the test report includes rule vulnerabilities, performance bottlenecks, and optimization suggestions.

[0047] Specifically, in this embodiment, the multi-dimensional verification and analysis module completes full-dimensional verification based on a three-layer verification model, locates rule vulnerabilities and performance bottlenecks, generates detailed test reports, and provides targeted optimization suggestions.

[0048] The system also includes: An iterative optimization module is configured to generate an optimized test case set based on the rule vulnerabilities in the test report, perform iterative testing until preset indicators are met, and adjust the configuration information of the network system under test according to the performance bottleneck and the optimization suggestions.

[0049] Specifically, in this embodiment, the iterative optimization module automatically generates an optimized test case set, supports iterative testing, provides rule parameter tuning simulation function, and verifies the performance of the optimized anti-circumvention system.

[0050] For example: (1) Test prerequisites The anti-circumvention system under test only supports IP-level (IP reputation, location) and protocol-level (VPN protocol characteristics) identification rules. The preset IP reputation threshold is "above 80 points is considered high risk", and the protection action is "direct blocking + log reporting". It is necessary to verify the system's ability to identify VPN circumvention and low-reputation IP access and its false judgment rate.

[0051] (2) Test steps Rule parsing and modeling: Receive the configuration information of the network system to be tested, construct a two-dimensional identification rule model of IP and protocol, and map the verification points as "IP reputation level identification and VPN protocol feature matching". The generated test indicators are "IP reputation identification accuracy, VPN protocol identification rate, and normal access false positive rate". Scenario generation and test case design: 12 core scenarios (including HTTP proxy, SSL VPN, virtual machine spoofing, and VPN with protocol spoofing as HTTPS) were selected from 6 major scenario template libraries to generate 30 test cases, including 20 cases of illegal circumvention, 8 cases of normal access, and 2 cases of ambiguous boundaries (legitimate access via shared proxy IP and normal office access via low-reputation IP <60 points>). After sorting by security risk level, high-risk scenario test cases such as SSL VPN and protocol spoofing VPN were executed first. High-fidelity scenario simulation and test execution: Start the SSL VPN client through a multi-protocol simulation engine, configure 3 proxy nodes to rotate, and encapsulate VPN traffic as HTTPS protocol to achieve protocol masquerading; at the same time, simulate normal office access (boundary use case) of low-reputation IP (60 points), send access request to the government service platform, and capture system response data in real time; Multi-dimensional verification and result analysis: Based on a three-layer verification model, rule matching: 19 out of 20 violating test cases were correctly identified, and 1 "protocol spoofing + IP rotation" scenario was missed (the protocol feature rule was not matched); protection actions: 8 normal test cases were blocked without error, and 2 boundary test cases were accurately distinguished (normal access by low-reputation IPs was not blocked), with a false positive rate of 0% and an overprotection rate of 0%; performance and stability: the SSLVPN scenario response time was 30ms, and the CPU / memory resource utilization was less than 10%, with no crashes. Iterative testing and rule optimization verification: For the "protocol feature identification vulnerability in protocol spoofing scenarios", an optimized test case set was automatically generated (supplementing HTTPS-encapsulated VPN traffic scenarios with different encryption levels). At the same time, it was recommended to optimize the protocol feature matching library and supplement the VPN traffic features encapsulated by HTTPS. After adjusting the rule parameters and testing again, the missed scenarios were successfully identified, and the VPN protocol identification rate was improved to 100%.

[0052] (3) Test results The core vulnerability of the network system under test is that the protocol feature matching library does not cover the VPN traffic features encapsulated by HTTPS. After optimization, the system has a 100% recognition rate for VPN-type circumvention behaviors, a 0% false positive rate for normal access, and a response time of ≤30ms, which meets the anti-circumvention test requirements of the government service platform.

[0053] This embodiment has the following advantages: 1. Full-scene circumvention simulation coverage: The library of 6 major circumvention scenario templates covers traditional and new dynamic circumvention technologies, increasing the scenario coverage rate from less than 60% of existing technologies to more than 99%, which can accurately test the anti-circumvention system's ability to identify various circumvention methods; 2. Accurate multi-dimensional rule verification: Specialized testing is conducted on the four dimensions of the identification rules, which can accurately locate rule vulnerabilities (such as missed identification of protocol features, unreasonable IP reputation thresholds), thereby improving the identification accuracy of the anti-circumvention system by more than 40%. 3. Precise control of false positive rate: Through the design of fuzzy boundary use cases, the ability to distinguish between legal and illegal behaviors is specifically verified, and the false positive rate of the anti-circumvention system for legitimate access is controlled within 0.1%, solving the false positive problem of existing technologies; 4. Real-time protection and comprehensive performance evaluation: Supports continuous simulation of dynamic circumvention scenarios, can test the system's real-time response speed (response time ≤50ms), and covers performance scenarios such as high concurrency and 24-hour continuous testing, providing comprehensive performance evaluation data; 5. Significantly improved testing efficiency and adaptability: Through automated scenario generation, test case execution, and iterative testing, testing efficiency is improved by more than 80% compared to manual testing; the rule parsing and modeling module supports different vendor rule systems, and combined with the optimization simulation function, the system adaptability is improved by more than 70%; 6. Significantly enhanced vulnerability discovery capabilities: Compared to existing testing tools, this invention can discover more hidden rule vulnerabilities (such as cloud phone features not being covered, and protocol spoofing traffic not being identified), increasing the number of vulnerabilities discovered by more than 50%, providing accurate basis for the optimization of anti-circumvention systems.

[0054] For ease of explanation, the above description has been provided in conjunction with specific embodiments. However, the discussion in some embodiments is not intended to be exhaustive or to limit the embodiments to the specific forms disclosed above. Various modifications and variations can be obtained based on the above teachings. The selection and description of the above embodiments are for the purpose of better explaining the contents of this disclosure, thereby enabling those skilled in the art to better utilize the embodiments.

Claims

1. An automated testing method for circumvention control based on multi-dimensional recognition rules, characterized in that, The method includes: Obtain the configuration information of the network system to be tested, and generate a rule verification list based on the configuration information; the rule verification list is used to mark the specific test indicators of the network system to be tested. A test case set is generated based on the rule verification list; Scenario simulation is performed based on the test case set, and the response dataset of the circumvention system is extracted during the scenario simulation; the scenario simulation includes injecting circumvention scenario features; A comprehensive analysis of the circumvention system's response dataset was conducted to obtain a test report, which included rule vulnerabilities, performance bottlenecks, and optimization suggestions. Based on the rule vulnerabilities identified in the test report, an optimized test case set is generated and iteratively tested until preset indicators are met. Then, the configuration information of the network system under test is adjusted according to the performance bottlenecks and optimization suggestions.

2. The automated testing method for anti-circumvention control based on multi-dimensional recognition rules according to claim 1, characterized in that, The step of generating a rule verification list based on the configuration information includes: Construct a recognition rule model; The configuration information is input into the recognition rule model to map the rules corresponding to the configuration information into testable verification points and generate the rule verification list.

3. The automated testing method for anti-circumvention control based on multi-dimensional recognition rules according to claim 2, characterized in that, The identification rule model is built based on four dimensions: IP, behavior, device, and protocol.

4. The automated testing method for anti-circumvention control based on multi-dimensional recognition rules according to claim 1, characterized in that, The step of generating a test case set based on the rule verification list includes: Build a scene template library; The test case set is generated based on the rule verification list, the constructed scenario template library, and the scenario-driven algorithm; the test case set includes three categories: unauthorized circumvention, normal access, and ambiguous boundaries.

5. The automated testing method for anti-circumvention control based on multi-dimensional recognition rules according to claim 4, characterized in that, The scenario template library includes basic proxies, VPN tunnels, virtual environments, encrypted tunnels, hybrid evasion, and boundary scenarios.

6. The automated testing method for anti-circumvention control based on multi-dimensional recognition rules according to claim 1, characterized in that, The test case set is sorted according to the probability of scenario occurrence, rule weight, and security risk level to determine the priority.

7. The automated testing method for anti-circumvention control based on multi-dimensional recognition rules according to claim 6, characterized in that, The step of performing scenario simulation based on the test case set and extracting the circumvention system response dataset during the scenario simulation includes: Build a multi-protocol simulation engine; The test case set is executed according to the security risk level corresponding to the test case set, and during the execution process, circumvention scenario features are injected for dynamic circumvention scenarios to extract the circumvention system response dataset when the network system under test responds to circumvention.

8. The automated testing method for anti-circumvention control based on multi-dimensional recognition rules according to claim 7, characterized in that, The steps for performing a full-dimensional analysis based on the circumvention system response dataset include: Construct a three-layer verification model; The three-layer verification model is used to perform a full-dimensional analysis of the response dataset of the circumvention system to statistically analyze the identification accuracy, false negative rate, and false positive rate, and to generate the test report.

9. The automated testing method for anti-circumvention control based on multi-dimensional recognition rules according to claim 8, characterized in that, The three-layer verification model is constructed based on three levels: rule matching, protection actions, and performance and stability.

10. An automated testing system for circumvention control based on multi-dimensional recognition rules, the system being applicable to the method described in any one of claims 1 to 9, characterized in that, The system includes: The rule parsing and modeling module is configured to obtain the configuration information of the network system to be tested and generate a rule verification list based on the configuration information; the rule verification list is used to mark the specific test indicators of the network system to be tested. The scenario generation and test case design module is configured to generate a test case set based on the rule verification list; the test case set is sorted according to the scenario occurrence probability, rule weight, and security risk level priority. A high-fidelity simulation and execution module is configured to perform scenario simulation based on the test case set and extract the circumvention system response dataset during the scenario simulation process; the scenario simulation includes injecting circumvention scenario features. A multi-dimensional verification and analysis module is configured to perform a full-dimensional analysis based on the response dataset of the circumvention system to obtain a test report; the test report includes rule vulnerabilities, performance bottlenecks, and optimization suggestions. An iterative optimization module is configured to generate an optimized test case set based on the rule vulnerabilities in the test report, perform iterative testing until preset indicators are met, and adjust the configuration information of the network system under test according to the performance bottleneck and the optimization suggestions.

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