| Component | vLLM |
| Severity | medium (CVSS 6.5) |
| CVSS vector | CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H |
| Published (NVD) | 2026-10-05 |
| Last modified | 2026-10-08 |
| Affected versions | vllm < 0.30.0 |
| Fixed in | 0.30.0 |
| Weakness | CWE-20CWE-617CWE-639CWE-668CWE-704CWE-1284 |
| CISA KEV | not listed |
NVD description
vLLM is an inference and serving engine for large language models. Prior to 0.30.0, the /inference/v1/generate endpoint in the disaggregated scale-out path accepts caller-supplied tensors in the features.kwargs_data field, cache identifiers in the features.mm_hashes field, ranges in the features.mm_placeholders field, and wire-selected multimodal field processors without rebinding them to the active model renderer contract. Forged grid geometry, field types, or non-positive placeholder lengths can terminate the shared EngineCore; when an attacker knows or can induce a victim's content hash, forged cache hashes can poison or retrieve cross-request encoder-cache state; and dropped sparse placeholder masks can alter replayed transport semantics. This issue is fixed in version 0.30.0.
What to do
- Upgrade vLLM to
0.30.0or later. - Do not expose the component's API or UI to the internet without authentication in front of it.
Sources
- NVD: CVE-2026-105754
- https://github.com/vllm-project/vllm/security/advisories/GHSA-ph72-cqr5-qpp7
- https://github.com/vllm-project/vllm/commit/1970f3ed4be7fa8620e4ddc4a12c36a8384cfc27
- https://github.com/vllm-project/vllm/pull/51898
- https://github.com/vllm-project/vllm/releases/tag/v0.30.0
Read more
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