logical testing model and resource lifecycle information,generate test cases and complete parameters,and alleviate inconsistency issues through parameter inference.Once again,we propose a method of analyzing test resu...logical testing model and resource lifecycle information,generate test cases and complete parameters,and alleviate inconsistency issues through parameter inference.Once again,we propose a method of analyzing test results using joint state codes and call stack information,which compensates for the shortcomings of traditional analysis methods.We will apply our method to testing REST services,including OpenStack,an open source cloud operating platform for experimental evaluation.We have found a series of inconsistencies,known vulnerabilities,and new unknown logical defects.展开更多
rest风格的web服务框架,是一种新兴的、灵活的架构,相比于SOAP Web Service更加适合大规模web应用。设计rest架构的校园一卡通开放平台,通过开放API,第三方应用系统可以方便的将一卡通的功能引入到自己的平台中,达到应用融合的目的,即...rest风格的web服务框架,是一种新兴的、灵活的架构,相比于SOAP Web Service更加适合大规模web应用。设计rest架构的校园一卡通开放平台,通过开放API,第三方应用系统可以方便的将一卡通的功能引入到自己的平台中,达到应用融合的目的,即方便了用户,也有利于双方应用的推广。展开更多
RESTful APIs have been adopted as the standard way of developing web services,allowing for smooth communication between clients and servers.Their simplicity,scalability,and compatibility have made them crucial to mode...RESTful APIs have been adopted as the standard way of developing web services,allowing for smooth communication between clients and servers.Their simplicity,scalability,and compatibility have made them crucial to modern web environments.However,the increased adoption of RESTful APIs has simultaneously exposed these interfaces to significant security threats that jeopardize the availability,confidentiality,and integrity of web services.This survey focuses exclusively on RESTful APIs,providing an in-depth perspective distinct from studies addressing other API types such as GraphQL or SOAP.We highlight concrete threats-such as injection attacks and insecure direct object references(IDOR)-to illustrate the evolving risk landscape.Our work systematically reviews state-of-the-art detection methods,including static code analysis and penetration testing,and proposes a novel taxonomy that categorizes vulnerabilities such as authentication and authorization issues.Unlike existing taxonomies focused on general web or network-level threats,our taxonomy emphasizes API-specific design flaws and operational dependencies,offering a more granular and actionable framework for RESTful API security.By critically assessing current detection methodologies and identifying key research gaps,we offer a structured framework that advances the understanding and mitigation of RESTful API vulnerabilities.Ultimately,this work aims to drive significant advancements in API security,thereby enhancing the resilience of web services against evolving cyber threats.展开更多
RESTful API fuzzing is a promising method for automated vulnerability detection in Kubernetes platforms.Existing tools struggle with generating lengthy,high-semantic request sequences that can pass Kubernetes API gate...RESTful API fuzzing is a promising method for automated vulnerability detection in Kubernetes platforms.Existing tools struggle with generating lengthy,high-semantic request sequences that can pass Kubernetes API gateway checks.To address this,we propose KubeFuzzer,a black-box fuzzing tool designed for Kubernetes RESTful APIs.KubeFuzzer utilizes Natural Language Processing(NLP)to extract and integrate semantic information from API specifications and response messages,guiding the generation of more effective request sequences.Our evaluation of KubeFuzzer on various Kubernetes clusters shows that it improves code coverage by 7.86%to 36.34%,increases the successful response rate by 6.7%to 83.33%,and detects 16.7%to 133.3%more bugs compared to three leading techniques.KubeFuzzer identified over 1000 service crashes,which were narrowed down to 7 unique bugs.We tested these bugs on 10 real-world Kubernetes projects,including major providers like AWS(EKS),Microsoft Azure(AKS),and Alibaba Cloud(ACK),and confirmed that these issues could trigger service crashes.We have reported and confirmed these bugs with the Kubernetes community,and they have been addressed.展开更多
文摘logical testing model and resource lifecycle information,generate test cases and complete parameters,and alleviate inconsistency issues through parameter inference.Once again,we propose a method of analyzing test results using joint state codes and call stack information,which compensates for the shortcomings of traditional analysis methods.We will apply our method to testing REST services,including OpenStack,an open source cloud operating platform for experimental evaluation.We have found a series of inconsistencies,known vulnerabilities,and new unknown logical defects.
文摘RESTful APIs have been adopted as the standard way of developing web services,allowing for smooth communication between clients and servers.Their simplicity,scalability,and compatibility have made them crucial to modern web environments.However,the increased adoption of RESTful APIs has simultaneously exposed these interfaces to significant security threats that jeopardize the availability,confidentiality,and integrity of web services.This survey focuses exclusively on RESTful APIs,providing an in-depth perspective distinct from studies addressing other API types such as GraphQL or SOAP.We highlight concrete threats-such as injection attacks and insecure direct object references(IDOR)-to illustrate the evolving risk landscape.Our work systematically reviews state-of-the-art detection methods,including static code analysis and penetration testing,and proposes a novel taxonomy that categorizes vulnerabilities such as authentication and authorization issues.Unlike existing taxonomies focused on general web or network-level threats,our taxonomy emphasizes API-specific design flaws and operational dependencies,offering a more granular and actionable framework for RESTful API security.By critically assessing current detection methodologies and identifying key research gaps,we offer a structured framework that advances the understanding and mitigation of RESTful API vulnerabilities.Ultimately,this work aims to drive significant advancements in API security,thereby enhancing the resilience of web services against evolving cyber threats.
基金supported by the National Natural Science Foundation of China(No.62202320)the Fundamental Research Funds for the Central Universities(Nos.SCU2023D008,2023SCU12129)+2 种基金the Natural Science Foundation of Sichuan Province(No.2024NSFSC1449)the Science and Engineering Connotation Development Project of Sichuan University(No.2020SCUNG129)the Key Laboratory of Data Protection and Intelligent Management(Sichuan University),Ministry of Education.
文摘RESTful API fuzzing is a promising method for automated vulnerability detection in Kubernetes platforms.Existing tools struggle with generating lengthy,high-semantic request sequences that can pass Kubernetes API gateway checks.To address this,we propose KubeFuzzer,a black-box fuzzing tool designed for Kubernetes RESTful APIs.KubeFuzzer utilizes Natural Language Processing(NLP)to extract and integrate semantic information from API specifications and response messages,guiding the generation of more effective request sequences.Our evaluation of KubeFuzzer on various Kubernetes clusters shows that it improves code coverage by 7.86%to 36.34%,increases the successful response rate by 6.7%to 83.33%,and detects 16.7%to 133.3%more bugs compared to three leading techniques.KubeFuzzer identified over 1000 service crashes,which were narrowed down to 7 unique bugs.We tested these bugs on 10 real-world Kubernetes projects,including major providers like AWS(EKS),Microsoft Azure(AKS),and Alibaba Cloud(ACK),and confirmed that these issues could trigger service crashes.We have reported and confirmed these bugs with the Kubernetes community,and they have been addressed.
