Improper Input Validation Affecting vllm-openai-cuda-13.0 package, versions <0.31.0-r0
Threat Intelligence
The probability is the direct output of the EPSS model, and conveys an overall sense of the threat of exploitation in the wild. The percentile measures the EPSS probability relative to all known EPSS scores. Note: This data is updated daily, relying on the latest available EPSS model version. Check out the EPSS documentation for more details.
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- published17 Oct 2026
- disclosed5 Oct 2026
Introduced: 5 Oct 2026
NewCVE-2026-105757 (opens in a new tab)How to fix?
Upgrade Chainguard vllm-openai-cuda-13.0 to version 0.31.0-r0 or higher.
NVD Description
Note: Versions mentioned in the description apply only to the upstream vllm-openai-cuda-13.0 package and not the vllm-openai-cuda-13.0 package as distributed by Chainguard.
See How to fix? for Chainguard relevant fixed versions and status.
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.