{"schemaVersion":3,"id":"CVE-2026-105757","aliases":["GHSA-85xf-c7hm-whqw","PYSEC-2026-4199","CGA-4924-cf4c-r9cp","CGA-4h9c-mpmm-p375","CGA-776x-4m4f-9qgm","CGA-8f7h-j7c7-m9hw","CGA-jp95-qwwj-rqph","CGA-p6g8-72pq-wvcg","CGA-rvxx-w622-w479","CGA-qm8r-4vfc-9p36","CGA-vqw5-rxg2-ph9v"],"status":"published","duplicateOf":null,"title":null,"description":"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. 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