Veille CVE
CVE-2026-105754
6.5 MoyenneDescription
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.
Produits concernés
Scores CVSS
| Version | Score | Source | Vecteur |
|---|---|---|---|
| 3.1 | 6.5 Moyenne | security-advisories@github.com | CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H |
Faiblesses (CWE)
Références
- https://github.com/vllm-project/vllm/commit/1970f3ed4be7fa8620e4ddc4a12c36a8384cfc27 Patch
- https://github.com/vllm-project/vllm/pull/51898 Issue TrackingPatch
- https://github.com/vllm-project/vllm/releases/tag/v0.30.0 Release Notes
- https://github.com/vllm-project/vllm/security/advisories/GHSA-ph72-cqr5-qpp7 MitigationVendor Advisory