LoRDMA: A New Low-Rate DoS Attack in RDMA Networks
Shicheng Wang, Menghao Zhang, Yuying Du, Ziteng Chen, Zhiliang Wang, Mingwei Xu, Renjie Xie, Jiahai Yang
Abstract
—RDMA is being widely used from private data center applications to multi-tenant clouds, which makes RDMA security gain tremendous attention. However, existing RDMA security studies mainly focus on the security of RDMA systems, and the security of the coupled traffic control mechanisms (represented by PFC and DCQCN) in RDMA networks is largely overlooked. In this paper, through extensive experiments and analysis, we demonstrate that concurrent short-duration bursts can cause drastic performance loss on flows across multiple hops via the interaction between PFC and DCQCN. And we also summarize the vulnerabilities between the performance loss and the burst peak rate, as well as the duration. Based on these vulnerabilities, we propose the LoRDMA attack, a low-rate DoS attack against RDMA traffic control mechanisms. By monitoring RTT as the feedback signal, LoRDMA can adaptively 1) coordinate the bots to different target switch ports to cover more victim flows efficiently; 2) schedule the burst parameters to cause significant performance loss efficiently. We conduct and evaluate the LoRDMA attack at both ns-3 simulations and a cloud RDMA cluster. The results show that compared to existing attacks, the LoRDMA attack achieves higher victim flow coverage and performance loss with much lower attack traffic and detectability. And the communication performance of typical distributed machine learning training applications ( NCCL Tests ) in the cloud RDMA cluster can be degraded from 18.23% to 56.12% under the LoRDMA attack.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 64d029a4-2ddc-48f4-be79-87992f441215Cited by top-tier papers2
- Hawkeye: Diagnosing RDMA Network Performance Anomalies with PFC ProvenanceShicheng Wang, Menghao Zhang, Xiao Li, Qiyang Peng et al.SIGCOMM 2025 · 7 citations
- Janus: Enabling Expressive and Efficient ACLs in High-speed RDMA CloudsZiteng Chen, Menghao Zhang, Jiahao Cao, Xuzheng Chen et al.NDSS 2026
Builds on29
- A Unified Architecture for Accelerating Distributed DNN Training in Heterogeneous GPU/CPU ClustersYimin Jiang, Yibo Zhu, Chang Lan, Bairen Yi et al.OSDI 2020 · 390 citations
- ATP: In-network Aggregation for Multi-tenant LearningChonLam Lao, Yanfang Le, Kshiteej Mahajan, Yixi Chen et al.NSDI 2021 · 359 citations
- Swift: Delay is Simple and Effective for Congestion Control in the DatacenterGautam Kumar, Nandita Dukkipati, Keon Jang, Hassan M. G. Wassel et al.SIGCOMM 2020 · 333 citations
- When Cloud Storage Meets RDMAYixiao Gao, Qiang Li, Lingbo Tang, Yongqing Xi et al.NSDI 2021 · 228 citations
- SP-PIFO: Approximating Push-In First-Out Behaviors using Strict-Priority QueuesAlbert Gran Alcoz, Alexander Dietmüller, Laurent VanbeverNSDI 2020 · 140 citations
Related papers
- PACC: Proactive and Accurate Congestion Feedback for RDMA Congestion ControlXiaolong Zhong, Jiao Zhang, Yali Zhang, Zixuan Guan et al.INFOCOM 2022 · 36 citations
- ReDMArk: Bypassing RDMA Security MechanismsBenjamin Rothenberger, Konstantin Taranov, Adrian Perrig, Torsten HoeflerUSENIX Security 2021 · 56 citations
- sRDMA - Efficient NIC-based Authentication and Encryption for Remote Direct Memory AccessKonstantin Taranov, Benjamin Rothenberger, Adrian Perrig, Torsten HoeflerUSENIX ATC 2020 · 59 citations
- Bedrock: Programmable Network Support for Secure RDMA SystemsJiarong Xing, Kuo-Feng Hsu, Yiming Qiu, Ziyang Yang et al.USENIX Security 2022
- Quantifying Rowhammer Vulnerability for DRAM SecurityYichen Jiang, Huifeng Zhu, Dean Sullivan, Xiaolong Guo et al.DAC 2021 · 20 citations
