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
The Qinling Mountains, known for their rich vegetation and diverse pollinating insects, have seen a significant decline in bee species richness and abundance over recent decades, largely due to the introduction and sp...The Qinling Mountains, known for their rich vegetation and diverse pollinating insects, have seen a significant decline in bee species richness and abundance over recent decades, largely due to the introduction and spread of Apis mellifera. This decline has caused cascading effects on the region's community structure and ecosystem stability. To improve the protection of native bees in the natural and agricultural landscape of the Qinling Mountains and its surrounding areas, we investigated 33 sampling sites within three habitats: forest, forest-agriculture ecotones, and farmland. Using a generalized linear mixing model, t-test, and other data analysis methods, we explored the impact of Apis mellifera on local pollinator bee richness, abundance, and the pollination network in different habitats in these regional areas. The results show that(1)Apis mellifera significantly negatively affects the abundance and richness of wild pollinator bees,while Apis cerana abundance is also affected by beekeeping conditions.(2)There are significant negative effects of Apis mellifera on the community structure of pollinator bees in the Qinling Mountains and its surrounding areas: the Shannon-Wiener diversity index, Pielou evenness index, and Margalef richness index of bee communities at sites with Apis mellifera influence were significantly lower than those at sites without Apis mellifera influence.(3)The underlying driver of this effect is the monopolization of flowering resources by Apis mellifera. This species tends to visit flowering plants with large nectar sources, which constitute a significant portion of the local plant community. By maintaining a dominant role in the bee-plant pollination network, Apis mellifera competitively displaces native pollinator bees, reducing their access to floral resources. This ultimately leads to a reduction in local bee-plant interactions, decreasing the complexity and stability of the pollination network. These findings highlight the need for targeted conservation efforts to protect native pollinator species and maintain the ecological balance in the Qinling Mountains.展开更多
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.
基金funded by the National Key R&D Program of China (2022YFE0115200)the Biodiversity Survey and the Assessment Project of the Ministry of Ecology and Environment, China (2019HJ2096001006)the National Animal Collection Resource Center, China。
文摘The Qinling Mountains, known for their rich vegetation and diverse pollinating insects, have seen a significant decline in bee species richness and abundance over recent decades, largely due to the introduction and spread of Apis mellifera. This decline has caused cascading effects on the region's community structure and ecosystem stability. To improve the protection of native bees in the natural and agricultural landscape of the Qinling Mountains and its surrounding areas, we investigated 33 sampling sites within three habitats: forest, forest-agriculture ecotones, and farmland. Using a generalized linear mixing model, t-test, and other data analysis methods, we explored the impact of Apis mellifera on local pollinator bee richness, abundance, and the pollination network in different habitats in these regional areas. The results show that(1)Apis mellifera significantly negatively affects the abundance and richness of wild pollinator bees,while Apis cerana abundance is also affected by beekeeping conditions.(2)There are significant negative effects of Apis mellifera on the community structure of pollinator bees in the Qinling Mountains and its surrounding areas: the Shannon-Wiener diversity index, Pielou evenness index, and Margalef richness index of bee communities at sites with Apis mellifera influence were significantly lower than those at sites without Apis mellifera influence.(3)The underlying driver of this effect is the monopolization of flowering resources by Apis mellifera. This species tends to visit flowering plants with large nectar sources, which constitute a significant portion of the local plant community. By maintaining a dominant role in the bee-plant pollination network, Apis mellifera competitively displaces native pollinator bees, reducing their access to floral resources. This ultimately leads to a reduction in local bee-plant interactions, decreasing the complexity and stability of the pollination network. These findings highlight the need for targeted conservation efforts to protect native pollinator species and maintain the ecological balance in the Qinling Mountains.
