Fuzzy testing and compliance evaluation platform and method for cloud password service

Abstract

The invention discloses a cloud password service-oriented fuzzy test and compliance evaluation platform and method, and relates to the technical field of cloud computing and password security evaluation. The evaluation platform comprises a demand analysis module, a test case generation module, a fuzzy test execution module, a compliance detection module, a result fusion analysis module and a report generation module, and the result fusion analysis module is connected with the fuzzy test execution module and the compliance detection module. And the cloud password service detection module is used for carrying out association analysis on the response data, the abnormal log and the compliance detection result acquired by the fuzzy test, identifying the security vulnerability type and the compliance defect level of the cloud password service, and removing a repeated detection result. Fuzzy testing and compliance detection are organically fused, correlation analysis of the two results is achieved through the result fusion analysis module, the problems that in the prior art, the two tests are separated, and the results are difficult to integrate are solved, and the safety compliance condition of the cloud password service can be comprehensively reflected.

Description

Technical Field

[0001] This invention relates to the field of cloud computing and cryptographic security assessment technology, and more specifically to an integrated fuzzing and compliance assessment platform and method for cloud cryptographic services. It is applicable to the integrated automated testing and assessment of the security and compliance of cloud cryptographic services (such as cloud key management service KMS and cloud digital certificate service) provided in the form of API / SDK. Background Technology

[0002] With the rapid development of cloud computing technology, cloud cryptography services, as a core infrastructure for ensuring data security in cloud computing environments, are widely used in various fields such as finance, government, and enterprises. Cloud cryptography services are typically provided to users in the form of APIs (Application Programming Interfaces) or SDKs (Software Development Kits), including cloud key management services (KMS), cloud digital certificate services, and cloud encryption / decryption services. Because cloud cryptography services directly handle the encryption, decryption, and key management of sensitive data, their security and compliance are directly related to the security and privacy protection of user data.

[0003] Currently, the evaluation of cloud cryptography services is mainly divided into two independent areas: security testing and compliance testing. In terms of security testing, common methods include fuzzing and penetration testing. Fuzzing, in particular, detects security issues such as crashes and vulnerabilities by inputting abnormal data into the service interface. However, existing fuzzing tools are mostly general-purpose tools, lacking customized testing strategies tailored to cryptographic characteristics, making it difficult to accurately identify security vulnerabilities specific to cloud cryptography services (such as key management vulnerabilities and algorithm implementation defects). In terms of compliance testing, it mainly relies on manual checks against national / industry compliance standards (such as GM / T0054-2018 and GB / T35273-2020). This method is inefficient, highly subjective, and difficult to correlate with security testing results, leading to a fragmented evaluation process that fails to comprehensively reflect the security and compliance status of cloud cryptography services.

[0004] Furthermore, existing assessment tools are mostly single-function tools, unable to achieve integrated assessment of security and compliance. Assessors must use multiple tools separately for testing and then manually integrate the results, increasing costs and increasing the risk of omissions or misjudgments due to human error. Therefore, there is an urgent need for an integrated and automated assessment solution that can achieve fuzz testing and compliance checks for cloud cryptography services, improving assessment efficiency and comprehensiveness, and providing strong support for ensuring the security and compliance of cloud cryptography services. Summary of the Invention

[0005] In view of the technical problems existing in the prior art, the present invention provides an integrated fuzzing and compliance assessment platform and method for cloud cryptography services, which can effectively solve the technical problems existing in the prior art.

[0006] The present invention specifically adopts the following technical solution:

[0007] An integrated fuzzing and compliance assessment platform for cloud cryptography services, including:

[0008] The requirement parsing module is used to obtain the API / SDK interface specification documents and preset compliance standards of the cloud cryptography service, and parse them to obtain interface parameter information, call constraints and compliance detection indicators;

[0009] The test case generation module connects to the requirement parsing module. Based on the parsed interface parameter information, it generates basic test cases, expands and generates a fuzz test case set by combining cryptographic attack characteristics and fuzz testing strategies, and generates compliance detection cases based on compliance detection indicators.

[0010] The fuzz test execution module connects to the test case generation module. It is used to load fuzz test case sets, establish communication with the target cloud cryptography service through API calls or SDK integration, execute fuzz tests, and collect interface response data, exception logs, and service status information in real time during the test process.

[0011] The compliance testing module, connected to the requirements parsing module, is used to load compliance testing test cases. Based on preset compliance standards, it automatically tests the cryptographic algorithm selection, key management process, access control policies, and audit log integrity of the cloud cryptography service, and collects the compliance testing results.

[0012] The results fusion and analysis module is connected to the fuzz test execution module and the compliance detection module respectively. It is used to perform correlation analysis on the response data, anomaly logs and compliance detection results collected by fuzz test, identify the security vulnerability types and compliance defect levels of cloud cryptography services, and remove duplicate detection results.

[0013] The report generation module, connected to the results fusion analysis module, is used to generate an integrated assessment report that includes details of security vulnerabilities, compliance ratings, and remediation recommendations based on the fusion analysis results.

[0014] In some implementations, the requirement parsing module includes an interface parsing unit and a compliance standard parsing unit;

[0015] The interface parsing unit uses a combination of natural language processing and syntax analysis to extract interface name, parameter type, parameter range, required fields, return value format, and error code information from the API / SDK interface specification document;

[0016] The so-called "combination of natural language processing and syntax analysis" specifically refers to the core technical means by which the interface parsing unit extracts information from API / SDK interface specification documents. By integrating the semantic understanding capabilities of natural language processing (NLP) with the structural parsing capabilities of syntax analysis, it achieves accurate information extraction from unstructured / semi-structured interface documents.

[0017] For unstructured text in documents (such as interface function descriptions, parameter explanations, etc.), NLP techniques such as text classification and named entity recognition (NER) are used to identify and label key information entities. For example, from the description "Create Key Interface: Used to generate symmetric / asymmetric keys, parameters include key type (required, supports SM2 / SM4), key length (range 256-1024 bits)," core entities such as "Create Key" (interface name), "Key Type," "Key Length" (parameter type), "Required" (required field), "SM2 / SM4," and "256-1024 bits" (parameter range) are identified.

[0018] The core function of Natural Language Processing (NLP) is to focus on understanding document semantics and solving the problem of extracting information from natural language descriptions in interface specification documents. It processes ambiguous or unclear text in documents, clarifying information attribution through semantic similarity matching and contextual analysis. For example, it distinguishes the semantic difference between "this parameter is optional" and "a valid parameter is required" in the document to accurately determine whether a parameter is mandatory; it correlates "return code 200 indicates success, 500 indicates server error" with the corresponding interface to ensure accurate matching of error code information with the interface.

[0019] The core function of syntax analysis is to focus on parsing document structure and solve the problems of format parsing and information association of structured / semi-structured content (such as tables, lists, and code snippets) in interface specification documents.

[0020] Using syntax analysis techniques (such as context-free grammar analysis and regular expression matching), the document's format structure is parsed to extract structured data. For example, the table structure of the "Interface Parameter Table" in the document can be identified, and data can be extracted in batches according to the column structure of "parameter name-type-range-required fields"; the format description of the interface return value (such as "the return value is in JSON format, containing code, msg, and data fields") can be matched with regular expressions to accurately extract the return value format information.

[0021] Establish syntactic relationships between information to ensure that the extracted interface names, parameters, return values, error codes, and other information form a complete logical chain. For example, by analyzing the syntactic hierarchy of "interface name - parameter list - return value description" in the documentation, we can avoid incorrectly associating parameters of interface A with interface B; and by parsing the syntax of code snippets (such as function definitions in SDK documentation), we can extract parameter constraints for interface calls (such as parameter data types and order requirements).

[0022] The advantages of combining the two are reflected in the fact that it can "complement the deficiencies of structural parsing with semantic understanding, and standardize the logic of semantic understanding with structural parsing," ensuring that core information such as interface names and parameter types can be extracted comprehensively, accurately, and unambiguously from API / SDK interface specification documents of various formats, providing reliable basic data for subsequent test case generation. If NLP is used alone, information extraction will be biased due to non-standard document formats (such as missing table headers or chaotic text descriptions), and syntax analysis alone cannot understand the semantic information in natural language descriptions (such as the optional / required meanings of parameters and the meanings of error codes).

[0023] The compliance standard parsing unit is used to parse preset national / industry cryptography compliance standards and generate quantifiable compliance detection indicators.

[0024] In some implementations, the test case generation module includes a basic test case generation unit, a fuzzy test case extension unit, and a compliance test case generation unit;

[0025] The basic test case generation unit generates positive test cases that conform to the interface call specification based on the normal value range of the interface parameters.

[0026] Its core function is to verify the basic availability of cloud cryptography services under normal business scenarios. For example, for the cloud KMS "create key" interface, it generates positive test cases with key type SM4 and length of 256 bits (both conforming to the interface specification) to ensure that the core functions of the service can run normally.

[0027] The fuzzy test case extension unit adopts a mutation-based fuzzy testing strategy, which performs random mutation, boundary value mutation, and special character injection mutation on the parameters of the basic test cases. At the same time, it designs targeted mutation rules in combination with cryptographic characteristics, including abnormal key length mutation, illegal algorithm parameter mutation, and disordered encrypted data format mutation.

[0028] The general mutation strategy is used to detect the service's fault tolerance capability for regular abnormal inputs, while the cryptography-specific mutation rules are designed for the core characteristics of cloud cryptography services. They can accurately discover unique security vulnerabilities such as key management and algorithm implementation. For example, the service's key length verification logic can be detected by abnormal key length mutation (inputting a 1-bit or 1024-bit key).

[0029] The compliance test case generation unit generates test cases covering scenarios such as cryptographic algorithm compliance, key lifecycle management, access control permissions, and audit log recording, based on compliance detection indicators.

[0030] These use cases directly connect to pre-defined national / industry compliance standards. For example, for the compliance indicator of "audit logs must be retained for no less than 90 days", specific log query and duration verification use cases are generated to ensure that the content being tested is accurately matched with compliance requirements.

[0031] In some implementations, the fuzz test execution module includes a communication adaptation unit, a test case execution unit, and a data acquisition unit;

[0032] The communication adaptation unit provides several types of API / SDK adaptation interfaces, supporting the access of cryptographic service SDKs including RESTful API and RPC API. That is, the communication adaptation unit provides RESTful API adaptation interfaces, RPC API adaptation interfaces, or other mainstream cloud service provider cryptographic service SDK adaptation interfaces, such as Alibaba Cloud KMS SDK adaptation interfaces, Tencent Cloud KMSSDK adaptation interfaces, Huawei Cloud cryptographic service SDK adaptation interfaces, etc. The initialization configuration, interface call and other functions of the corresponding SDK can be directly integrated without the need for additional protocol adaptation logic development.

[0033] RESTful API (Representative State Transfer API): A lightweight API design style based on HTTP / HTTPS protocol. It realizes data interaction through standard HTTP methods such as GET, POST, PUT, DELETE, and the format is mostly JSON / XML. It is the most commonly used interface form of cloud services (such as Alibaba Cloud KMS and Tencent Cloud cryptographic services, whose public APIs are mostly RESTful).

[0034] RPC API (Remote Procedure Call API): A communication protocol for directly calling remote service functions / methods. It is based on underlying protocols such as TCP / UDP, has high transmission efficiency and compact data format (such as gRPC, Thrift). It is often used for enterprise internal private cloud cryptographic services or cryptographic operation scenarios with high performance requirements.

[0035] Cryptographic Service SDK (Software Development Kit): A development kit (such as Java, Python, or Go language SDK) provided by cloud service providers that encapsulates API call logic, authentication, data encryption, and other functions. Developers can directly integrate and use it without having to worry about the underlying communication details. The platform supports "SDK access", which means that there is no need to manually write API call code; the SDK can be directly loaded to complete the connection with the service under test.

[0036] The platform constructs a multi-protocol compatibility layer through a "communication adaptation unit," and has designed dedicated adaptation interfaces for SDKs of different API types. The specific implementation method is as follows:

[0037] For SDKs with RESTful APIs: Adapt through HTTP client libraries (such as Python Requests, JavaOkHttp) to automatically parse API addresses, request headers, and parameter formats in the SDK, and support HTTPS encrypted transmission and authentication (such as AK / SK key verification).

[0038] For SDKs with RPC API types: adapt to the corresponding RPC framework (such as gRPC library, Thrift library), load the service description file (such as .proto file) in the SDK, parse the remote method definition, and realize the call to the RPC interface and data interaction;

[0039] Unified adaptation mechanism: Users only need to select the SDK type (RESTful / RPC) and fill in the access parameters (such as SDK path and authentication information) in the platform configuration file, and the adaptation unit will automatically complete the conversion of communication protocol and connection establishment without modifying the core test logic;

[0040] This platform is designed to enhance its applicability: it covers the mainstream interface forms of current cloud cryptography services, whether it is a public cloud RESTful API SDK (such as Huawei Cloud Cryptography Service SDK) or a private cloud RPC API SDK (such as an enterprise's self-developed cryptography middleware SDK), all of which can be accessed and evaluated.

[0041] Reduce user operating costs: Users do not need to develop custom access code for different interface types; the configuration process is simplified through standardized adaptation.

[0042] Ensuring test stability: The adapter unit has a built-in protocol fault tolerance mechanism (such as HTTP timeout retry and RPC connection keep-alive) to ensure the stable execution of test cases and data collection under different protocols.

[0043] The test case execution unit supports concurrent execution of fuzz test cases and can configure test rate, retry mechanism and timeout.

[0044] The data acquisition unit collects the return code, return data, and response time of the interface in real time, as well as the system logs, abnormal crash information, and resource usage of the cloud password service.

[0045] An integrated approach to fuzz testing and compliance assessment for cloud cryptography services includes the following steps:

[0046] S1: Requirement analysis, obtain the API / SDK interface specification document and preset compliance standards of the target cloud cryptography service, and parse to obtain interface parameter information, call constraints and compliance detection indicators;

[0047] S2: Test case generation. Basic test cases are generated based on interface parameter information. Fuzzy test case sets are generated by combining cryptographic features and fuzz testing strategies. At the same time, compliance test cases are generated based on compliance detection indicators.

[0048] S3: Fuzz test execution, loads fuzz test case set, establishes communication with the target cloud cryptography service through API calls or SDK integration, executes fuzz tests and collects test process data in real time;

[0049] S4: Compliance Detection. Load compliance detection test cases and automatically detect the cryptographic algorithm selection, key management process, access control policy, and audit log integrity of the cloud cryptography service based on preset compliance standards, and collect the compliance detection results.

[0050] S5: Results fusion analysis, which performs correlation analysis on the response data, anomaly logs and compliance test results collected by fuzz testing, identifies the types of security vulnerabilities and the levels of compliance defects, and removes duplicate test results;

[0051] S6: Report generation. Based on the fusion analysis results, an integrated assessment report is generated, which includes details of security vulnerabilities, compliance ratings, and remediation recommendations.

[0052] In some implementations, in step S1, the interface parameter information includes the interface name, parameter type, parameter range, required fields, return value format, and error code information;

[0053] The compliance testing indicators include cryptographic algorithm compliance indicators, key management compliance indicators, access control compliance indicators, and audit log compliance indicators.

[0054] In some implementations, step S2, the process of generating the fuzz test case set, includes:

[0055] S21: Generate positive base test cases based on the normal value range of interface parameters;

[0056] S22: Perform random mutation, boundary value mutation, and special character injection mutation on the parameters of the positive base test cases to generate general fuzz test cases;

[0057] S23: Design targeted mutation rules based on cryptographic characteristics, mutate key parameters such as key length, algorithm parameters, and encrypted data format, and generate cryptographic-specific fuzzy test cases;

[0058] S24: Integrate general fuzzy test cases with cryptography-specific fuzzy test cases to form a fuzzy test case set, and deduplicate and prioritize the test cases.

[0059] In some implementations, in step S3, the test process data includes interface return codes, return data, response time, system logs of the cloud password service, abnormal crash information, and CPU and memory resource usage.

[0060] During the fuzzing process, if the cloud cryptography service is detected to crash, become unresponsive, or return an abnormal error code, it is marked as a potential security vulnerability, and the corresponding fuzzing test case is recorded.

[0061] In some implementations, step S4 includes the following specific process for compliance testing:

[0062] S41: Check whether the cryptographic algorithms supported by the cloud cryptography service comply with the preset compliance standards and determine whether there are any disabled algorithms;

[0063] S42: Check whether the generation, storage, backup, and destruction processes of the key comply with compliance requirements, and verify whether the key length meets the standard;

[0064] S43: Detect the access control policy of the cloud password service and verify whether the principle of least privilege, multi-factor authentication and permission approval process are implemented;

[0065] S44: Check the integrity and traceability of audit logs, verify whether the logs contain key information such as user operations, key changes, and service anomalies, and whether the log retention time meets the requirements.

[0066] In some implementations, step S5 includes the following steps: associating abnormal responses discovered by fuzzing with defects discovered by compliance testing to determine whether there are security vulnerabilities caused by compliance defects; aggregating security vulnerabilities and compliance defects of the same type to determine the root cause of the defects; and comprehensively rating the security compliance of the cloud cryptography service based on the severity of the vulnerabilities and the severity of the compliance defects.

[0067] The advantages of this invention are as follows:

[0068] 1. This invention organically integrates fuzz testing and compliance testing, and realizes the correlation analysis of the results of the two through the result fusion analysis module. This solves the problem of the two tests being separate and the results being difficult to integrate in the prior art, and can comprehensively reflect the security and compliance status of cloud cryptography services.

[0069] 2. This invention designs targeted fuzzing mutation rules based on the cryptographic characteristics of cloud cryptography services, and generates cryptography-specific fuzzing test cases, which can accurately discover security vulnerabilities unique to cloud cryptography services (such as key management vulnerabilities, algorithm implementation defects, etc.), thereby improving the accuracy of security testing.

[0070] 3. The invention has a high degree of automation: from requirements analysis, test case generation, test execution to result analysis and report generation, the entire process is automated, requiring minimal human intervention, effectively improving evaluation efficiency, reducing evaluation costs, and minimizing omissions or misjudgments caused by human operation. Attached Figure Description

[0071] Figure 1 This is a schematic diagram of the module structure of the integrated fuzz testing and compliance assessment platform for cloud cryptography services in Embodiment 1 of the present invention;

[0072] Figure 2 This is a flowchart illustrating the integrated fuzzing and compliance assessment method for cloud cryptography services in Embodiment 2 of the present invention.

[0073] Attached label: 10, Requirements Analysis Module; 20, Test Case Generation Module; 30, Fuzz Test Execution Module; 40, Compliance Detection Module; 50, Result Fusion Analysis Module; 60, Report Generation Module. Detailed Implementation

[0074] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0075] Example 1

[0076] like Figure 1 As shown, this embodiment provides an integrated fuzzing and compliance assessment platform for cloud cryptography services, including a requirements parsing module 10, a test case generation module 20, a fuzzing execution module 30, a compliance detection module 40, a result fusion and analysis module 50, and a report generation module 60. The specific implementation of each module is as follows:

[0077] Module 10, the Requirements Analysis Unit, is developed using Python and includes an Interface Analysis Unit and a Compliance Standard Analysis Unit. The Interface Analysis Unit uses the PyPDF2 library to parse API / SDK interface specification documents (PDF format) and, in conjunction with the Natural Language Processing (NLTK) tool, extracts interface names, parameter types, parameter ranges, required fields, return value formats, and error code information. The Compliance Standard Analysis Unit has a built-in structured rule base, such as the structured rule bases of compliance standards like GM / T0054-2018 "Information Security Technology Cloud Cryptography Service Interface Specification" and GB / T35273-2020 "Information Security Technology Personal Information Security Specification," to generate quantifiable compliance testing indicators, such as: "Supported symmetric encryption algorithm must be SM4," "Key length not less than 256 bits," and "Audit log retention time not less than 90 days."

[0078] Test Case Generation Module 20: Developed using Python, it connects to the Requirements Analysis Module 10. The basic test case generation unit generates positive basic test cases based on the parameter information extracted by the interface analysis unit, using equivalence class partitioning. For example, for the "Create Key" interface of Cloud KMS, it generates normal test cases with a key type of SM4 and a key length of 256 bits. The fuzzy test case extension unit uses a mutation-based fuzzy testing strategy, randomly mutating the parameters of the basic test cases (e.g., changing the key length to a random string), boundary value mutation (e.g., changing the key length to 1 bit or 1024 bits), and special character injection mutation (e.g., injecting "..." into the key name). <script>”），同时结合密码学特性设计针对性变异规则，如：密钥长度异常变异（小于128位）、算法参数非法变异（指定禁用的DES算法）、加密数据格式错乱变异（将JSON格式数据改为二进制乱码），生成模糊测试用例集；合规用例生成单元根据合规检测指标，生成覆盖密码算法合规性、密钥管理流程等场景的检测用例，如："检测是否支持SM2椭圆曲线密码算法”、"检测密钥销毁是否有审批日志”等。

[0079] 模糊测试执行模块30：采用Python+Requests库（用于API调用）开发，包括通信适配单元、用例执行单元及数据采集单元。通信适配单元支持RESTful API（通过Requests库）、RPC API（通过grpc库）及阿里云KMS SDK、腾讯云KMS SDK等主流云密码服务SDK的接入，用户可通过配置文件选择接入方式；用例执行单元采用多线程并发机制，可配置测试速率（如：每秒执行10个用例）、重试机制（失败后重试3次）及超时时间（30秒）；数据采集单元通过日志拦截、接口响应捕获的方式，实时采集接口返回码、返回数据、响应时间，以及云密码服务的系统日志（通过云服务提供商的日志接口获取）、异常崩溃信息、CPU与内存资源占用情况（通过云监控API获取），并将采集的数据存储至MySQL数据库。

[0080] 合规性检测模块40：基于Python开发，连接需求解析模块10。该模块加载合规性检测用例后，通过调用云密码服务的API / SDK获取相关配置信息与日志数据，与预设的合规标准进行比对，实现自动化检测。例如，检测密码算法合规性时，调用"查询支持的算法列表”接口，比对返回的算法是否包含禁用算法；检测密钥管理合规性时，调用"查询密钥生命周期记录”接口，验证密钥生成、备份、销毁流程是否完整；检测访问控制合规性时，通过模拟不同权限用户的操作，验证是否实现最小权限原则；检测审计日志合规性时，调用"查询审计日志”接口，验证日志是否包含用户操作、密钥变更等关键信息，且日志保留时间是否达标。检测结果分为"符合”、"不符合”、"待核实”三个等级，存储至MySQL数据库。

[0081] 结果融合分析模块50：采用Python+Pandas库开发，分别连接模糊测试执行模块30与合规性检测模块40的MySQL数据库。该模块首先对模糊测试结果进行分析，根据异常日志与响应数据识别安全漏洞类型，如：缓冲区溢出、拒绝服务、信息泄露等；然后对合规性检测结果进行整理，明确合规缺陷类型；接着通过关联规则（如："拒绝服务漏洞可能与密钥管理流程不合规相关”）将两者结果进行关联分析，判断是否存在因合规缺陷导致的安全漏洞，例如若检测到"密钥生成无需权限验证”（合规缺陷），且模糊测试中通过无权限用户调用"创建密钥”接口成功（安全漏洞），则关联两者为同一根源缺陷；最后对相同类型的缺陷进行聚合，去除重复结果，并根据漏洞的危害程度（高、中、低）与合规缺陷的严重等级（严重、一般、轻微），采用加权评分法对云密码服务的安全合规性进行综合评级（A级：优秀、B级：合格、C级：不合格）。

[0082] 报告生成模块60：采用Python+ReportLab库开发，连接结果融合分析模块50。该模块从融合分析结果中提取安全漏洞详情（包括漏洞描述、触发用例、危害程度）、合规缺陷详情（包括缺陷描述、检测依据）、综合评级，生成PDF格式的一体化评估报告，并提供整改建议（如："修复拒绝服务漏洞，增加参数合法性校验”、"完善密钥销毁审批流程，补充审计日志”）。用户可通过平台界面下载报告。

[0083] 实施例2

[0084] 如图2所示，本实施例提供面向云密码服务的模糊测试与合规性一体化评估方法，本实施例采用实施例1中的平台，对某云服务商的KMS服务进行评估，具体步骤如下：

[0085] S1：需求解析。获取该云服务商KMS服务的API接口规范文档（PDF格式）及预设的合规性标准（如：GM / T0054-2018、GB / T35273-2020）。通过需求解析模块10的接口解析单元提取接口信息，包括"创建密钥”接口（参数：密钥类型、密钥长度、密钥名称）、"加密数据”接口（参数：密钥ID、明文数据、加密模式）等；通过合规标准解析单元生成合规检测指标，如："支持SM2、SM3、SM4算法”、"密钥长度不小于256位”、"审计日志保留时间≥90天”等。

[0086] S2：测试用例生成。基础用例生成单元生成正向基础测试用例，如"创建密钥：密钥类型SM4、长度256位、名称test_key”、"加密数据：密钥ID123、明文数据abc、加密模式CBC”；模糊用例扩展单元生成模糊测试用例集，包括通用模糊用例（如：密钥长度改为0位、密钥名称注入特殊字符）与密码专项模糊用例（如：指定算法为DES、明文数据为二进制乱码）；合规用例生成单元生成合规检测用例，如："检测支持的算法列表是否包含SM2”、"检测密钥销毁是否有审批日志”等。

[0087] S3：模糊测试执行。配置通信适配单元采用RESTful API接入方式，输入云KMS服务的API密钥与地址；用例执行单元以每秒5个用例的速率并发执行模糊测试用例集；数据采集单元实时采集测试过程数据，发现当输入密钥长度为0位时，"创建密钥”接口无响应（标记为拒绝服务漏洞），当注入特殊字符时，接口返回敏感错误信息（标记为信息泄露漏洞）。

[0088] S4：合规性检测。加载合规检测用例执行检测，发现该云KMS服务支持DES算法（不符合合规要求），密钥销毁无审批日志（不符合合规要求），审计日志保留时间为60天（不符合合规要求）。

[0089] S5：结果融合分析。关联分析发现，"拒绝服务漏洞”与"密钥长度参数未校验”相关，"信息泄露漏洞”与"错误处理机制不合规”相关；聚合相同类型缺陷，去除重复结果；采用加权评分法计算综合评级为C级（不合格）。

[0090] S6：报告生成。生成一体化评估报告，包含安全漏洞详情（拒绝服务、信息泄露）、合规缺陷详情（支持禁用算法、日志保留时间不足等）、综合评级C级，以及整改建议（修复参数校验逻辑、删除DES算法、延长日志保留时间等）。

[0091] 本实施例通过一体化评估方法，成功发现了该云KMS服务的安全漏洞与合规缺陷，生成了全面的评估报告，为服务优化提供了精准依据。

[0092] 实施例3

[0093] 如图2所示，本实施例提供面向云密码服务的模糊测试与合规性一体化评估方法，本实施例采用实施例1中的一体化评估平台，对某政务云服务商提供的云数字证书服务进行评估，该服务以SDK形式对外提供证书申请、证书吊销、证书验证等功能，评估步骤如下：

[0094] S1：需求解析。获取该云数字证书服务的SDK开发文档及预设的合规性标准（如：GM / T0054-2018《信息安全技术云密码服务接口规范》、GB / T38540-2020《信息安全技术安全电子签章密码技术规范》）。通过需求解析模块10的接口解析单元提取核心功能接口信息，包括"证书申请”接口（参数：主体名称、证书类型、密钥算法、有效期）、"证书吊销”接口（参数：证书序列号、吊销原因）、"证书验证”接口（参数：证书文件、待验证数据、签名值）；通过合规标准解析单元生成针对性合规检测指标，如："支持SM2密钥算法的数字证书签发”、"证书吊销流程需留存审批记录”、"证书验证日志包含完整的验证时间与结果”、"证书有效期不超过2年”等。

[0095] S2：测试用例生成。基础用例生成单元生成正向基础测试用例，如："证书申请：主体名称为XX政务部门、证书类型为服务器证书、密钥算法SM2、有效期1年”、"证书验证：证书文件为valid.crt、待验证数据为testdata、签名值为sign123”；模糊用例扩展单元结合云数字证书服务特性生成模糊测试用例集，通用模糊用例包括"证书有效期改为0天”、"证书序列号注入特殊字符@#$”、"待验证数据为空字符串”，密码专项模糊用例包括"指定密钥算法为RSA1024（不合规算法）”、"证书文件篡改后注入（修改证书签名字段）”、"签名值格式错乱（将Base64格式改为十六进制乱码）”；合规用例生成单元生成覆盖证书签发合规性、吊销流程合规性、日志完整性等场景的检测用例，如："检测是否支持SM2算法证书签发”、"检测证书吊销是否有审批日志留存”、"验证证书验证日志是否包含签名值校验细节”等。

[0096] S3：模糊测试执行。配置通信适配单元采用SDK集成方式接入，导入该云数字证书服务的Java SDK并完成初始化配置；用例执行单元以每秒3个用例的速率并发执行模糊测试用例集（考虑政务云服务稳定性要求，降低测试速率）；数据采集单元实时采集测试过程数据，发现当输入"证书有效期为3650天（10年）”时，"证书申请”接口虽返回成功但生成的证书有效期与输入不一致（标记为参数处理异常漏洞），当注入篡改后的证书文件执行"证书验证”接口时，服务出现内存溢出并重启（标记为严重拒绝服务漏洞）。

[0097] S4：合规性检测。加载合规检测用例执行自动化检测，发现以下合规缺陷：1）支持RSA1024算法的证书签发（违反GM / T0054-2018中关于密钥算法强度的要求）；2）证书吊销仅需提交证书序列号即可完成，无权限审批流程及审批日志（违反政务信息系统安全合规要求）；3）证书验证日志仅记录验证结果，未包含待验证数据、签名值等关键信息，且日志保留时间为60天（不足90天的合规要求）；4）存在部分超过2年有效期的证书签发记录（违反GB / T38540-2020的相关规定）。

[0098] S5：结果融合分析。通过关联规则进行结果关联，发现"参数处理异常漏洞”与"证书有效期合规校验缺失”直接相关，"严重拒绝服务漏洞”源于"证书文件合法性校验流程不合规”；对同类缺陷进行聚合，例如将"支持不合规算法”、"证书有效期超标”归为证书签发环节合规缺陷；采用加权评分法（安全漏洞权重60%、合规缺陷权重40%）计算综合评级为C级（不合格），其中严重拒绝服务漏洞为核心扣分项。

[0099] S6：报告生成。生成一体化评估报告，明确标注安全漏洞详情（参数处理异常、严重拒绝服务）、合规缺陷详情（4项不合规内容及对应的检测标准依据）、综合评级C级；针对核心问题给出整改建议，包括"完善参数合法性校验逻辑，严格限制证书有效期上限为2年”、"新增证书吊销权限审批流程，补充审批日志留存功能”、"删除RSA1024算法支持，仅保留SM2等合规算法”、"优化证书验证日志记录维度，延长日志保留时间至90天以上”、"修复证书文件校验逻辑，避免内存溢出漏洞”等。

[0100] 本实施例针对云数字证书服务的特性完成了全流程一体化评估，精准定位了政务云密码服务中的安全隐患与合规短板，生成的整改建议具备较强的针对性和可操作性，为政务云数字证书服务的安全合规优化提供了有效技术支撑。

[0101] 实施例4

[0102] 如图2所示，本实施例提供面向云密码服务的模糊测试与合规性一体化评估方法，本实施例采用实施例1中的一体化评估平台，对某金融云服务商提供的云加密解密服务进行评估，该服务以RESTful API形式对外提供对称加密、非对称加密、解密验证等功能，主要应用于金融交易数据加密场景，评估步骤如下：

[0103] S1：需求解析。获取该云加密解密服务的API接口规范文档及预设的合规性标准（如：GM / T0054-2018《信息安全技术云密码服务接口规范》、JR / T0025-2018《银行业信息系统密码应用技术规范》）。通过需求解析模块10的接口解析单元提取核心功能接口信息，包括"对称加密”接口（参数：加密算法、明文数据、密钥ID、填充模式）、"非对称解密”接口（参数：解密算法、密文数据、密钥ID、签名验证标识）、"密钥查询”接口（参数：密钥ID、查询范围）；通过合规标准解析单元生成金融场景针对性合规检测指标，如："对称加密算法需支持SM4，非对称加密算法需支持SM2”、"加密数据传输需采用TLS 1.2及以上协议”、"解密操作需留存详细审计日志（含操作人、操作时间、数据标识）”、"密钥使用权限需与金融业务角色严格绑定”等。

[0104] S2：测试用例生成。基础用例生成单元生成正向基础测试用例，如："对称加密：加密算法SM4、明文数据为金融交易流水（1234567890123456）、密钥ID K12345、填充模式PKCS7”、"非对称解密：解密算法SM2、密文数据为encryptData123、密钥ID P67890、签名验证标识True”；模糊用例扩展单元结合金融云加密解密服务的高安全性要求，生成模糊测试用例集，通用模糊用例包括"明文数据为空、明文数据长度超过接口限制（10MB）”、"密钥ID注入无效字符（如：中文‘密钥’）”、"填充模式输入不存在的值（如：PKCS10）”，密码专项模糊用例包括"指定加密算法为3DES（金融领域禁用算法）”、"密文数据篡改（修改密文末尾3位字符）”、"签名验证标识注入布尔值以外的字符串（如：‘yes’）”；合规用例生成单元生成覆盖算法合规性、传输安全、审计日志、权限管控等场景的检测用例，如："检测是否仅支持SM2 / SM4等合规算法”、"验证加密数据传输是否采用TLS 1.2+协议”、"检测解密操作审计日志是否包含完整业务关联信息”等。

[0105] S3：模糊测试执行。配置通信适配单元采用RESTful API接入方式，输入金融云加密解密服务的API密钥、访问地址及TLS认证证书；用例执行单元采用低并发模式（每秒2个用例）执行模糊测试用例集（避免影响金融核心业务运行）；数据采集单元实时采集测试过程数据，发现以下安全漏洞：1）当输入明文数据长度超过10MB且为非结构化二进制数据时，"对称加密”接口出现响应超时并触发服务降级（标记为拒绝服务漏洞）；2）当密文数据被篡改后输入"非对称解密”接口时，服务返回详细的密钥格式错误信息（含部分密钥片段），存在信息泄露风险（标记为敏感信息泄露漏洞）；3）当签名验证标识注入字符串"yes”时，接口直接崩溃并返回500内部服务器错误（标记为接口稳定性漏洞）。

[0106] S4：合规性检测。加载合规检测用例执行自动化检测，发现以下合规缺陷：1）服务仍支持3DES对称加密算法（违反JR / T0025-2018中金融领域密码算法选型要求）；2）部分加密数据传输采用TLS 1.1协议（未达到TLS 1.2+的合规标准）；3）解密操作审计日志仅记录操作人及时间，未包含金融交易流水号等业务关联数据，且日志保留时间为80天（不足90天的合规要求）；4）存在跨业务角色调用密钥解密的情况（如：普通查询角色可调用交易数据解密密钥），未实现权限与业务角色的严格绑定。

[0107] S5：结果融合分析。通过关联规则进行结果关联，发现"敏感信息泄露漏洞”与"错误信息返回规范不合规”直接相关，"跨角色权限调用”合规缺陷可能导致未授权解密风险，与模糊测试未覆盖的权限绕过漏洞存在潜在关联；对同类缺陷进行聚合，将"支持禁用算法”、"传输协议不合规”归为传输与算法层合规缺陷，将"日志不完整”、"权限管控不严”归为安全管控层合规缺陷；采用加权评分法（安全漏洞权重65%、合规缺陷权重35%）计算综合评级为C级（不合格），其中敏感信息泄露漏洞及跨角色权限调用缺陷为核心风险点。

[0108] S6：报告生成。生成一体化评估报告，详细列明安全漏洞详情（3类漏洞的触发条件、危害范围及影响程度）、合规缺陷详情（4项不合规内容及对应的金融行业合规标准依据）、综合评级C级；针对金融场景特性给出专项整改建议，包括"新增明文数据长度及格式校验逻辑，优化大文件加密处理机制，修复拒绝服务漏洞”、"规范错误信息返回格式，屏蔽敏感密钥相关信息，修复信息泄露漏洞”、"删除3DES算法支持，仅保留SM2 / SM4合规算法”、"升级数据传输协议至TLS 1.2+，强化传输层安全”、"完善审计日志记录维度，补充金融交易流水号等业务信息，延长日志保留时间至90天以上”、"重构权限管控体系，实现密钥使用权限与金融业务角色的严格绑定，新增跨角色权限调用拦截机制”等。

[0109] 本实施例针对金融云加密解密服务的高安全、高合规要求完成了精准评估，定位的核心风险点直接关联金融交易数据安全，生成的整改建议贴合金融行业监管要求，为金融云密码服务的安全合规升级提供了针对性技术方案，助力服务商满足银行业密码应用评估要求。

[0110] 因此，以上对在附图中提供的本发明的实施例的详细描述并非旨在限制要求保护的本发明的范围，而是仅仅表示本发明的选定实施例。基于本发明中的实施例，本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。< / script>

Claims

1. An integrated fuzzing testing and compliance assessment platform for cloud cryptography services, characterized in that: include: The requirement parsing module is used to obtain the API / SDK interface specification documents and preset compliance standards of the cloud cryptography service, and parse them to obtain interface parameter information, call constraints and compliance detection indicators; The test case generation module connects to the requirement parsing module. Based on the parsed interface parameter information, it generates basic test cases, expands and generates a fuzz test case set by combining cryptographic attack characteristics and fuzz testing strategies, and generates compliance detection cases based on compliance detection indicators. The fuzz test execution module connects to the test case generation module. It is used to load fuzz test case sets, establish communication with the target cloud cryptography service through API calls or SDK integration, execute fuzz tests, and collect interface response data, exception logs, and service status information in real time during the test process. The compliance testing module, connected to the requirements parsing module, is used to load compliance testing test cases. Based on preset compliance standards, it automatically tests the cryptographic algorithm selection, key management process, access control policies, and audit log integrity of the cloud cryptography service, and collects the compliance testing results. The results fusion and analysis module is connected to the fuzz test execution module and the compliance detection module respectively. It is used to perform correlation analysis on the response data, anomaly logs and compliance detection results collected by fuzz test, identify the security vulnerability types and compliance defect levels of cloud cryptography services, and remove duplicate detection results. The report generation module, connected to the results fusion analysis module, is used to generate an integrated assessment report that includes details of security vulnerabilities, compliance ratings, and remediation recommendations based on the fusion analysis results.

2. The integrated fuzz testing and compliance assessment platform for cloud cryptography services according to claim 1, characterized in that, The requirement parsing module includes an interface parsing unit and a compliance standard parsing unit; The interface parsing unit uses a combination of natural language processing and syntax analysis to extract interface name, parameter type, parameter range, required fields, return value format, and error code information from the API / SDK interface specification document; The compliance standard parsing unit is used to parse preset national / industry cryptography compliance standards and generate quantifiable compliance detection indicators.

3. The integrated fuzz testing and compliance assessment platform for cloud cryptography services according to claim 1, characterized in that, The test case generation module includes a basic test case generation unit, a fuzzy test case extension unit, and a compliant test case generation unit. The basic test case generation unit generates positive test cases that conform to the interface call specification based on the normal value range of the interface parameters. The fuzzy test case extension unit adopts a mutation-based fuzzy testing strategy, which performs random mutation, boundary value mutation, and special character injection mutation on the parameters of the basic test cases. At the same time, it designs targeted mutation rules in combination with cryptographic characteristics, including abnormal key length mutation, illegal algorithm parameter mutation, and disordered encrypted data format mutation. The compliance test case generation unit generates test cases covering scenarios such as cryptographic algorithm compliance, key lifecycle management, access control permissions, and audit log recording, based on compliance detection indicators.

4. The integrated fuzz testing and compliance assessment platform for cloud cryptography services according to claim 1, characterized in that, The fuzz test execution module includes a communication adaptation unit, a test case execution unit, and a data acquisition unit. The communication adaptation unit provides several types of API / SDK adaptation interfaces; The test case execution unit supports concurrent execution of fuzz test cases and can configure test rate, retry mechanism and timeout. The data acquisition unit collects the return code, return data, and response time of the interface in real time, as well as the system logs, abnormal crash information, and resource usage of the cloud password service.

5. A method for integrated fuzz testing and compliance assessment for cloud cryptography services, characterized in that: Includes the following steps: S1: Requirement analysis, obtain the API / SDK interface specification document and preset compliance standards of the target cloud cryptography service, and parse to obtain interface parameter information, call constraints and compliance detection indicators; S2: Test case generation. Basic test cases are generated based on interface parameter information. Fuzzy test case sets are generated by combining cryptographic features and fuzz testing strategies. At the same time, compliance test cases are generated based on compliance detection indicators. S3: Fuzz test execution, loads fuzz test case set, establishes communication with the target cloud cryptography service through API calls or SDK integration, executes fuzz tests and collects test process data in real time; S4: Compliance Detection. Load compliance detection test cases and automatically detect the cryptographic algorithm selection, key management process, access control policy, and audit log integrity of the cloud cryptography service based on preset compliance standards, and collect the compliance detection results. S5: Results fusion analysis, which performs correlation analysis on the response data, anomaly logs and compliance test results collected by fuzz testing, identifies the types of security vulnerabilities and the levels of compliance defects, and removes duplicate test results; S6: Report generation. Based on the fusion analysis results, an integrated assessment report is generated, which includes details of security vulnerabilities, compliance ratings, and remediation recommendations.

6. The integrated fuzzing and compliance assessment method for cloud cryptography services according to claim 5, characterized in that, In step S1, the interface parameter information includes the interface name, parameter type, parameter range, required fields, return value format, and error code information; The compliance testing indicators include cryptographic algorithm compliance indicators, key management compliance indicators, access control compliance indicators, and audit log compliance indicators.

7. The integrated fuzzing and compliance assessment method for cloud cryptography services according to claim 5, characterized in that, In step S2, the process of generating the fuzz test case set includes: S21: Generate positive base test cases based on the normal value range of interface parameters; S22: Perform random mutation, boundary value mutation, and special character injection mutation on the parameters of the positive base test cases to generate general fuzz test cases; S23: Design targeted mutation rules based on cryptographic characteristics, mutate key parameters such as key length, algorithm parameters, and encrypted data format, and generate cryptographic-specific fuzzy test cases; S24: Integrate general fuzzy test cases with cryptography-specific fuzzy test cases to form a fuzzy test case set, and deduplicate and prioritize the test cases.

8. The integrated fuzzing and compliance assessment method for cloud cryptography services according to claim 5, characterized in that, In step S3, the test process data includes interface return codes, returned data, response time, system logs of the cloud password service, abnormal crash information, and CPU and memory resource usage. During the fuzzing process, if the cloud cryptography service is detected to crash, become unresponsive, or return an abnormal error code, it is marked as a potential security vulnerability, and the corresponding fuzzing test case is recorded.

9. The integrated fuzzing and compliance assessment method for cloud cryptography services according to claim 5, characterized in that, In step S4, the specific process of the compliance inspection includes: S41: Check whether the cryptographic algorithms supported by the cloud cryptography service comply with the preset compliance standards and determine whether there are any disabled algorithms; S42: Check whether the generation, storage, backup, and destruction processes of the key comply with compliance requirements, and verify whether the key length meets the standard; S43: Detect the access control policy of the cloud password service and verify whether the principle of least privilege, multi-factor authentication and permission approval process are implemented; S44: Check the integrity and traceability of audit logs, verify whether the logs contain key information such as user operations, key changes, and service anomalies, and whether the log retention time meets the requirements.

10. The integrated fuzzing and compliance assessment method for cloud cryptography services according to claim 5, characterized in that, In step S5, the correlation analysis includes: associating the abnormal responses discovered by fuzzing with the defects discovered by compliance testing to determine whether there are security vulnerabilities caused by compliance defects; aggregating security vulnerabilities and compliance defects of the same type to determine the root cause of the defects; and comprehensively rating the security compliance of the cloud cryptography service based on the severity of the vulnerabilities and the severity level of the compliance defects.

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