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AII-1001-92793
ConfirmedA court, a regulator or the organization itself has stated the core facts, or the record cites a court or regulator source.

Remote Code Execution via Unsafe Deserialization in vLLM V0 Multi-Node Clusters

A remote code execution vulnerability was disclosed in vLLM's V0 engine affecting multi-node distributed deployments. The flaw uses unsafe pickle deserialization on ZeroMQ sockets to execute arbitrary code. The vLLM Project decided not to provide a patch and instead recommends users maintain network-level security controls.

6 May 2025 Β· vLLM Project Β· Security and cyberattacks
6 May 2025
AII-1001-92793View source β†—
Quick facts
Category
Security and cyberattacks
Source
github.com
Date
6 May 2025
Drafted by
Raidu Incident Detection

What happened

In vLLM V0 engine deployments using multi-node tensor parallelism, secondary hosts connect to a primary host via ZeroMQ SUB/XPUB sockets for distributed communication. Data received on these SUB sockets is deserialized using Python's pickle module without validation, allowing arbitrary code execution.

Reported impact

If the primary vLLM host is compromised, this vulnerability could be leveraged to compromise secondary hosts in the cluster. Attackers could alternatively exploit the vulnerability by using ARP cache poisoning to redirect traffic to a malicious endpoint that delivers arbitrary code payloads to target machines.

Index analysis

The vulnerability affects vLLM versions 0.5.2 and later, but only the V0 engine, which has been off by default since v0.8.0. The vLLM Project stated that V0 is not expected to be commonly deployed in multi-node configurations and noted the fix would be invasive, so no fix was provided. The V1 engine is not affected by this issue. The vulnerability is classified as High severity with a CVSS v3 base score of 8.0.

Governance controls

The vLLM Project recommends that users ensure their environment is on a secure network if using the V0 engine with multi-node tensor parallelism.

Classification

Category
Security and cyberattacks
Industry
IT infrastructure and hosting
Harm status
Potential harm
Intent
Unintentional
Timing
Post-deployment
Consequences
None recorded
AI systems
vLLM

Sources and evidence

This record was researched and written by the Index, based on the following original reporting.

github.com
https://github.com/vllm-project/vllm/security/advisories/GHSA-9pcc-gvx5-r5wm