A AegiFlow
MEDIUMCVSS 6.5EPSS 0.3%

CVE-2026-105757

CVE-2026-105757 updated by NVD

Published
2026-10-05
Modified
2026-10-09
EPSS percentile
22%
Sources
github-advisory, nvd

Summary

vLLM is an inference and serving engine for large language models. Prior to 0.30.0, structured-output request failures can escape request-scoped validation and reach the EngineCore fatal-error path. A per-request backend mismatch can re-raise a grammar compilation exception, padding produced by the ngram_gpu speculative-decoding mode can pass a negative token to guidance validation, and the Rust frontend can admit empty structured-output values that the Python frontend rejects, allowing ordinary constrained-generation requests to terminate the shared engine. This issue is fixed in version 0.30.0.

Affected packages

EcosystemPackageAffected versionsFixed versions
PyPIvllm—0.30.0

Remediation: Upgrade to 0.30.0 or later.

References

Includes data from the GitHub Advisory Database, licensed under CC-BY 4.0.

Includes data from the National Vulnerability Database (NIST). NVD data is in the public domain; this page is not endorsed by NIST.

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EPSS scores provided by the FIRST.org Exploit Prediction Scoring System.