CVE-2026-54235

vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.23.1rc0, ll temperature validation gates use comparison operators (<, >), which silently evaluate to False for NaN and for positive Infinity in Python's IEEE 754 float semantics. Both values pass every guard and propagate to GPU sampling kernels, where they produce undefined behavior or CUDA errors that can crash the inference worker. This vulnerability is fixed in 0.23.1rc0.

vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.23.1rc0, ll temperature validation gates use comparison operators (<, >), which silently evaluate to False for NaN and for positive Infinity in Python's IEEE 754 float semantics. Both values pass every guard and propagate to GPU sampling kernels, where they produce undefined behavior or CUDA errors that can crash the inference worker. This vulnerability is fixed in 0.23.1rc0.

Summary

All temperature validation gates use comparison operators (<, >), which silently evaluate to False for NaN and for positive Infinity in Python's IEEE 754 float semantics. Both values pass every guard and propagate to GPU sampling kernels, where they produce undefined behavior or CUDA errors that can crash the inference worker. Note: -Infinity is correctly caught.

Root Cause

sampling_params.py:384:

if 0 < self.temperature < _MAX_TEMP:  # NaN → False; +Inf → False

sampling_params.py:462:

if self.temperature < 0.0:            # NaN → False; +Inf → False
    raise VLLMValidationError(...)

No math.isnan() or math.isinf() check exists anywhere in sampling_params.py.

Python semantics (verified): float('nan') < 0.0 → False, float('inf') < 0.0 → False.

Impact

Crash of inference worker on GPU kernel execution with NaN/Inf softmax input, degrading service for all concurrent users.

Remediation

Add math.isfinite(self.temperature) check in _verify_args(). Reject non-finite float values with a 400 error.

Fix

A fix for this vulnerability was merged here: https://github.com/vllm-project/vllm/pull/45116

vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.23.1rc0, ll temperature validation gates use comparison operators (<, >), which silently evaluate to False for NaN and for positive Infinity in Python's IEEE 754 float semantics. Both values pass every guard and propagate to GPU sampling kernels, where they produce undefined behavior or CUDA errors that can crash the inference worker. This vulnerability is fixed in 0.23.1rc0.

vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.23.1rc0, ll temperature validation gates use comparison operators (<, >), which silently evaluate to False for NaN and for positive Infinity in Python's IEEE 754 float semantics. Both values pass every guard and propagate to GPU sampling kernels, where they produce undefined behavior or CUDA errors that can crash the inference worker. This vulnerability is fixed in 0.23.1rc0.

Summary

All temperature validation gates use comparison operators (<, >), which silently evaluate to False for NaN and for positive Infinity in Python's IEEE 754 float semantics. Both values pass every guard and propagate to GPU sampling kernels, where they produce undefined behavior or CUDA errors that can crash the inference worker. Note: -Infinity is correctly caught.

Root Cause

sampling_params.py:384:

if 0 < self.temperature < _MAX_TEMP:  # NaN → False; +Inf → False

sampling_params.py:462:

if self.temperature < 0.0:            # NaN → False; +Inf → False
    raise VLLMValidationError(...)

No math.isnan() or math.isinf() check exists anywhere in sampling_params.py.

Python semantics (verified): float('nan') < 0.0 → False, float('inf') < 0.0 → False.

Impact

Crash of inference worker on GPU kernel execution with NaN/Inf softmax input, degrading service for all concurrent users.

Remediation

Add math.isfinite(self.temperature) check in _verify_args(). Reject non-finite float values with a 400 error.

Fix

A fix for this vulnerability was merged here: https://github.com/vllm-project/vllm/pull/45116

Summary

All temperature validation gates use comparison operators (<, >), which silently evaluate to False for NaN and for positive Infinity in Python's IEEE 754 float semantics. Both values pass every guard and propagate to GPU sampling kernels, where they produce undefined behavior or CUDA errors that can crash the inference worker. Note: -Infinity is correctly caught.

Root Cause

sampling_params.py:384:

if 0 < self.temperature < _MAX_TEMP:  # NaN → False; +Inf → False

sampling_params.py:462:

if self.temperature < 0.0:            # NaN → False; +Inf → False
    raise VLLMValidationError(...)

No math.isnan() or math.isinf() check exists anywhere in sampling_params.py.

Python semantics (verified): float('nan') < 0.0 → False, float('inf') < 0.0 → False.

Impact

Crash of inference worker on GPU kernel execution with NaN/Inf softmax input, degrading service for all concurrent users.

Remediation

Add math.isfinite(self.temperature) check in _verify_args(). Reject non-finite float values with a 400 error.

Fix

A fix for this vulnerability was merged here: https://github.com/vllm-project/vllm/pull/45116