Linux kernel introduces the memory control group (memcg) to account and confine memory usage at the process-level. Due to its flexibility and efficiency, memcg has been widely adopted by container platforms and has become a fundamental technique. While being critical, memory accounting is prone to missing-account bugs due to the diverse memory accounting interfaces and the massive amount of allocation/free paths. To our knowledge, there is still no systematic analysis against the memory missing-account problem, with respect to its security impacts, detection, etc.

The flow of data across nodes has become the dominant feature of data sharing in distributed environments with increasingly blurred boundaries, where it is crucial to maintain data access dynamic, trusted, and efficient. However, traditional centralized access control models are not only difficult to apply in distributed environments but also ignore trusted verification of authorized entities. What’s worse, existing access control models rarely consider themselves security, lack independence, at a high risk of being bypassed or tampered with. Thus, we propose in this paper a distributed, dynamic, and trusted access control model, DDTAC-BSS, where the standard Attribute-Based Access Control (ABAC) architecture is modified and extended. To reduce the attack surface, we separate policy enforcement point (PEP) from other core components, they are located in the node system and access control system, respectively. Then, the access control entry point (ACEP) is added as the only interface for the node system to interact with the access control system. Subsequently, the model introduces the entity trusted assessment mechanism to improve the trustworthiness of access control services. Driven by the dynamic attributes, our model can achieve dynamic trusted authorization and fine-grained access control. Moreover, we implement a lightweight, independent, and distributed security subsystem to achieve unified management of policies and decision-making autonomy by message-driven. By considering the independence of the security subsystem, a trusted operating environment is built based on Trusted Execution Environment (TEE) to ensure the security of the access control mechanism itself. The security of our model is proved rigorously based on the non-interference theory. Comprehensive experiments and comparisons have demonstrated the superior functionality, comparable performance, and strong security of our model.

Due to its faster start-up speed and better resource utilization efficiency, OS-level virtualization has been widely adopted and has become a fundamental technology in cloud computing. Compared to hardware virtualization, OS-level virtualization leverages the shared-kernel design to achieve high efficiency and runs multiple user-space instances (a.k.a., containers) on the shared kernel. However, in this paper, we reveal a new attack surface that is intrinsic to OS-level virtualization, affecting Linux, FreeBSD, and Fuchsia. The root cause is that the shared-kernel design in OS-level virtualization results containers in sharing thousands of kernel variables and data structures directly and indirectly. Without exploiting any kernel vulnerabilities, a non-privileged container can easily exhaust the shared kernel variables and data structure instances to cause DoS attacks against other containers. Compared with the physical resources, these kernel variables or data structure instances (termed abstract resources) are more prevalent but under-protected. To show the importance of confining abstract resources, we conduct abstract resource attacks that target different aspects of the OS kernel. The results show that attacking abstract resources is highly practical and critical. We further conduct a systematic analysis to identify vulnerable abstract resources in the Linux kernel, which successfully detects 1,010 abstract resources and 501 of them can be repeatedly consumed dynamically. We also conduct the attacking experiments in the self-deployed shared-kernel container environments on the top 4 cloud vendors. The results show that all environments are vulnerable to abstract resource attacks. We conclude that containing abstract resources is hard and give out multiple strategies for mitigating the risks.

Serverless computing promises cost-efficiency and elasticity for high-productive software development. To achieve this, the serverless sandbox system must address two challenges: strong isolation between function instances, and low startup latency to ensure user experience. While strong isolation can be provided by virtualization-based sandboxes, the initialization of sandbox and application causes non-negligible startup overhead. Conventional sandbox systems fall short in low-latency startup due to their application-agnostic nature: they can only reduce the latency of sandbox initialization through hypervisor and guest kernel customization, which is inadequate and does not mitigate the majority of startup overhead.

Serverless computing promises auto-scalability and cost-efficiency (in "pay-as-you-go" manner) for high-productive software development. Because of its virtue, serverless computing has motivated increasingly new applications and services in the cloud. This, however, also presents new challenges including how to efficiently design high-performance serverless platforms and how to efficiently program on the platforms.