CVE•Published 2026-10-05•Modified 2026-10-08•0 articles on news•4 live references•NVD data

CVE-2026-105754Vllm · Vllm

Vulnerability data via NVD (ingested)

CVSS v3.1
6.5
MEDIUM
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
EPSS percentile
18
Exploit Prediction Scoring System · top 82% of all CVEs
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.

Timeline
Published 2026-10-05
Modified 2026-10-08

External references

Search for exposed instances

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More intel sources (5)

Known PoCs on GitHub

No public proof-of-concept repositories found for CVE-2026-105754 on GitHub.
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