Search/CVE-2026-105754
● CVE — Medium

CVE-2026-105754

VendorvllmProductvllmDiscoveredOct 5, 2026UpdatedOct 8, 2026

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.

CVSS v3.1
6.5 MEDIUM
EPSS
0.27%
probability of exploitation in 30 days
CISA KEV
Not listed
no confirmed exploitation reported
News coverage
0
sources referencing this CVE
Related IOCs
0
seen in the same coverage
EPSS Trend
Oct 7, 2026 → Oct 22, 2026
● 0.00pp
0.27% → 0.27% over 2 tracked changes
CVSS v3.1 Detail
Attack VectorNETWORK
Attack ComplexityLOW
Privileges RequiredLOW
User InteractionNONE
ScopeUNCHANGED
ConfidentialityNONE
IntegrityNONE
AvailabilityHIGH
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Timeline
disclosure → media coverage
Oct 5, 2026
Disclosure — published as a CVE record.