CVE-2026-105754
CVE.org · Published
- Record status
- Published
- Identifier year (not publication year)
- 2026
- Source publication
- Source updated
- Imported by cveboard
- Source snapshot
- cve_2026-10-24_midnight_baseline ·
CNA source text (English)
vLLM: Scale-out disaggregated multimodal transport trusts caller-supplied features
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.
Scoped product and version facts
Fix information unknown; no fixed version is derived here. Missing information does not prove that no fix exists.
Exploitation unknown; this catalogue does not assess exploitation.
vllm
- Vendor
- vllm-project
- Product
- vllm
- Platforms
- Unknown
- Default status
Unknown
| Version (version) | Status (status) | Version scheme (versionType) | Exclusive end (lessThan) | Inclusive end (lessThanOrEqual) | Status changes (at → status) |
|---|---|---|---|---|---|
| < 0.30.0 | affected | Unavailable | Unavailable | Unavailable | None listed |