论文标题

破产的秘密渠道:将网络可预测性转变为脆弱性

Bankrupt Covert Channel: Turning Network Predictability into Vulnerability

论文作者

Ustiugov, Dmitrii, Petrov, Plamen, Katebzadeh, M. R. Siavash, Grot, Boris

论文摘要

近年来,尽管云提供商采取了积极的信息范围措施,但数据泄漏的数量激增。当攻击者在安全的云环境中获取敏感数据时,秘密通信渠道是将数据渗透到外界的关键工具。尽管大部分的先前工作集中在单个CPU内的秘密渠道上,但它们需要间谍(发射器)和接收器共享CPU,这在具有数百或数千台机器的云环境中可能很难实现。 这项工作提出了破产,这是一种高速秘密渠道,可以在RDMA网络中的不同节点上运行的间谍和接收器之间的秘密通信。在破产中,间谍通过将RDMA网络数据包发给在其他机器上分配给它的私人内存区域(中介)(一个中介),与接收者进行通信。接收器类似地,在同一中介机构上分配一个单独的内存区域,也通过RDMA访问。通过将RDMA数据包转向一组特定的远程内存地址,间谍在一个内存库中引起了深度排队,这是主要内存的最优质内部单元。这揭示了一个计时渠道,接收器可以通过发出探针数据包来聆听,以地址映射到同一银行但在其自己的私人内存区域中。破产渠道在CloudLab的公共云中提供74KB/S吞吐量,同时无法发现现有的监视功能,例如CPU和NIC性能计数器。

Recent years have seen a surge in the number of data leaks despite aggressive information-containment measures deployed by cloud providers. When attackers acquire sensitive data in a secure cloud environment, covert communication channels are a key tool to exfiltrate the data to the outside world. While the bulk of prior work focused on covert channels within a single CPU, they require the spy (transmitter) and the receiver to share the CPU, which might be difficult to achieve in a cloud environment with hundreds or thousands of machines. This work presents Bankrupt, a high-rate highly clandestine channel that enables covert communication between the spy and the receiver running on different nodes in an RDMA network. In Bankrupt, the spy communicates with the receiver by issuing RDMA network packets to a private memory region allocated to it on a different machine (an intermediary). The receiver similarly allocates a separate memory region on the same intermediary, also accessed via RDMA. By steering RDMA packets to a specific set of remote memory addresses, the spy causes deep queuing at one memory bank, which is the finest addressable internal unit of main memory. This exposes a timing channel that the receiver can listen on by issuing probe packets to addresses mapped to the same bank but in its own private memory region. Bankrupt channel delivers 74Kb/s throughput in CloudLab's public cloud while remaining undetectable to the existing monitoring capabilities, such as CPU and NIC performance counters.

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