CVE-2026-100653: vLLM is an inference and serving engine for large language models. In versions from 0.22.1 through 0…
- Occurred
- Sep 26, 2026
- Published
- Sep 26, 2026
- Source
- NVD CVE
Summary
vLLM is an inference and serving engine for large language models. In versions from 0.22.1 through 0.28.0, the operator-supplied model revision pin (--revision / --code-revision) is not propagated to several Hugging Face artifact loads for the FunAudioChat and Tarsier2 architectures: the WhisperFeatureExtractor and speech_tokenizer PreTrainedTokenizerFast loads in vllm/model_executor/models/funaudiochat.py and the Qwen2VLConfig.from_pretrained call used by Tarsier2ProcessingInfo in vllm/model_executor/models/qwen2_vl.py. As a result, deployments pinned to a reviewed revision still resolve these behavior-affecting processor, tokenizer, and config artifacts from the repository's default revision, so a later change to the upstream default branch can alter audio preprocessing, speech tokenizer behavior, or Tarsier2 configuration without any change to the operator's configured pin. This is a supply-chain integrity and reproducibility failure for pinned deployments; it is residual to the earlier fix tracked as GHSA-3ww4-5jv9-j5gm / CVE-2026-47155 and does not constitute remote code execution or a trust_remote_code=False bypass. The issue is fixed in version 0.28.0.
Tags
- CVE
- CVE-2026-100653
- cvss:MEDIUM
Classification
Rationale: CVE describes a reproducibility failure in vLLM LLM serving engine where pinned model revisions are not fully propagated to dependent artifacts.
Classifier: Qwen/Qwen3.5-35B-A3B-FP8