Improper Validation of Specified Quantity in Input Affecting vllm package, versions [,0.29.0)
Threat Intelligence
Snyk has a proof-of-concept or detailed explanation of how to exploit this vulnerability.
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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Test your applications- Snyk IDSNYK-PYTHON-VLLM-20158368
- published27 Sept 2026
- disclosed26 Sept 2026
- creditUnknown
Introduced: 26 Sep 2026
NewCVE-2026-100650 (opens in a new tab)How to fix?
Upgrade vllm to version 0.29.0 or higher.
Overview
vllm is an A high-throughput and memory-efficient inference and serving engine for LLMs
Affected versions of this package are vulnerable to Improper Validation of Specified Quantity in Input in allreduce_rms_fusion.py when registering pattern replacements for mixed-dtype allreduce RMSNorm quantization fusions. The pm.register_replacement calls lack a dtype-match guard, allowing an attacker to trigger a crash by supplying inputs whose norm input and weight tensors have mismatched dtypes, causing the fused kernel to fail at runtime.