Researchers Identify Remote Side-Channel Attacks on Open vSwitch

Global: Researchers Identify Remote Side-Channel Attacks on Open vSwitch

Daewoo Kim and Sihang Liu have presented three remote side‑channel attacks that break isolation in virtualized cloud environments, as detailed in a paper submitted to arXiv on January 22, 2026. The study focuses on Open vSwitch, a widely deployed software‑based virtual switch, and demonstrates how its internal caching mechanisms can be exploited to leak information across virtual machines.

Background on Open vSwitch

Open vSwitch (OVS) operates within the host operating system of a virtualized server, providing packet forwarding between virtual machines and the physical network. To improve performance, OVS implements a multi‑level cache hierarchy that stores frequently accessed packet‑processing data, such as flow tables and header fields.

Identified Attack Primitives

The authors characterize the caching subsystem from a security perspective and isolate three primitives that enable remote observation of cache activity: timing differences, contention patterns, and cache‑state inference. These primitives form the basis for the subsequent attacks described in the paper.

Remote Covert Channels

By manipulating cache usage, the researchers establish covert channels that transmit data between otherwise isolated virtual machines. The channel leverages measurable latency variations caused by cache hits and misses, allowing an attacker to encode bits without direct network communication.

Header Recovery Attack

A novel attack recovers packet header fields of a remote victim. The technique repeatedly probes specific cache lines associated with header processing, using timing analysis to infer the presence of particular header values, thereby compromising confidentiality.

Packet Rate Monitoring Attack

The third attack monitors the packet transmission rate of a target machine. By observing fluctuations in cache contention, the attacker can reconstruct the victim’s packet rate with sufficient accuracy to infer activity patterns.

Proposed Mitigations

The paper discusses several mitigation strategies, including cache partitioning, constant‑time processing, and noise injection to obscure timing signals. Preliminary evaluations suggest that these defenses can significantly reduce the efficacy of the described attacks while imposing modest performance overhead.

Implications for Cloud Security

These findings highlight a previously underexplored attack surface in software‑defined networking components used in cloud infrastructures. Operators may need to reassess security assumptions surrounding virtual switch isolation and consider adopting the recommended countermeasures to protect multi‑tenant environments.

This report is based on information from arXiv, licensed under Academic Preprint / Open Access. Based on the abstract of the research paper. Full text available via ArXiv.