CVEvulnerability

CVE-2026-105754

6.5 MEDIUM Published 2026-10-05 Modified 2026-10-08 Official page ↗
Status
Analyzed
Published
2026-10-05
Last modified
2026-10-08
Assigner
[email protected]
CVSS 3.1 ([email protected])
6.5 MEDIUM — CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Weaknesses
CWE-1284, CWE-20, CWE-617, CWE-639, CWE-668, CWE-704

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.

Affected configurations

• vllm vllm (< 0.30.0)

Related

Weakness · CWE (6)

  • CWE-1284 Improper Validation of Specified Quantity in Input weakness
  • CWE-20 Improper Input Validation weakness
  • CWE-617 Reachable Assertion weakness
  • CWE-639 Authorization Bypass Through User-Controlled Key weakness
  • CWE-668 Exposure of Resource to Wrong Sphere weakness
  • CWE-704 Incorrect Type Conversion or Cast weakness

References