vLLM 0.6.1

CPE Details

vLLM 0.6.1
0.6.1
2025-05-13
10h23 +00:00
2025-05-13
10h23 +00:00
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CPE Name: cpe:2.3:a:vllm:vllm:0.6.1:*:*:*:*:*:*:*

Informations

Vendor

vllm

Product

vllm

Version

0.6.1

Related CVE

Open and find in CVE List

CVE ID Published Description Score Severity
CVE-2025-46570 2025-05-29 16h32 +00:00 vLLM is an inference and serving engine for large language models (LLMs). Prior to version 0.9.0, when a new prompt is processed, if the PageAttention mechanism finds a matching prefix chunk, the prefill process speeds up, which is reflected in the TTFT (Time to First Token). These timing differences caused by matching chunks are significant enough to be recognized and exploited. This issue has been patched in version 0.9.0.
2.6
Low
CVE-2025-30202 2025-04-30 00h24 +00:00 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.
7.5
High