CVE Catalog

CVE-2026-105754

MediumCVSS 6.5
Published: Updated: Translated: NVD NIST

Exploitation Probability (EPSS)

Low risk
0.27%

17th percentile - higher than 17% of all known CVEs

Summary

In vLLM before 0.30.0, the /inference/v1/generate endpoint in the disaggregated scale-out path accepts caller-supplied tensors, cache identifiers, ranges, and wire-selected multimodal field processors without rebinding them to the active model renderer contract, which can terminate EngineCore, poison cache, or alter transport semantics.

Risk Assessment

An attacker can send forged data, causing fatal errors, cache poisoning, or incorrect transport behavior, potentially leading to denial of service or data integrity issues.

Recommendation

Upgrade vLLM to version 0.30.0 or later, which includes a fix.

Other vulnerabilities in vLLM

See all
Original NVD description (English source)

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.

Vulnerability data from NVD (NIST) · CISA KEV · EPSS