7.5

CVE-2025-30202

Exploit

Data exposure via ZeroMQ on multi-node vLLM deployment

vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs. Versions starting from 0.5.2 and prior to 0.8.5 are vulnerable to denial of service and data exposure via ZeroMQ on multi-node vLLM deployment. In a multi-node vLLM deployment, vLLM uses ZeroMQ for some multi-node communication purposes. The primary vLLM host opens an XPUB ZeroMQ socket and binds it to ALL interfaces. While the socket is always opened for a multi-node deployment, it is only used when doing tensor parallelism across multiple hosts. Any client with network access to this host can connect to this XPUB socket unless its port is blocked by a firewall. Once connected, these arbitrary clients will receive all of the same data broadcasted to all of the secondary vLLM hosts. This data is internal vLLM state information that is not useful to an attacker. By potentially connecting to this socket many times and not reading data published to them, an attacker can also cause a denial of service by slowing down or potentially blocking the publisher. This issue has been patched in version 0.8.5.
Daten sind bereitgestellt durch National Vulnerability Database (NVD)
VllmVllm Version >= 0.5.2 < 0.8.5
VulnDex Vulnerability Enrichment
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EPSS Metriken
Typ Quelle Score Percentile
EPSS FIRST.org 0.49% 0.379
CVSS Metriken
Quelle Base Score Exploit Score Impact Score Vector String
nvd@nist.gov 7.5 3.9 3.6
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
security-advisories@github.com 7.5 3.9 3.6
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
CWE-770 Allocation of Resources Without Limits or Throttling

The product allocates a reusable resource or group of resources on behalf of an actor without imposing any restrictions on the size or number of resources that can be allocated, in violation of the intended security policy for that actor.

https://github.com/vllm-project/vllm/security/advisories/GHSA-9f8f-2vmf-885j
Vendor Advisory
Exploit
https://github.com/vllm-project/vllm/pull/6183
Patch
Issue Tracking
https://github.com/vllm-project/vllm/commit/a0304dc504c85f421d38ef47c64f83046a13641c
Patch