CVE-2026-54235 vLLM: temperature=NaN and temperature=Infinity bypass validation and propagate to GPU kernels

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 propagat...

CVE-2026-48746 vLLM: OpenAI auth bypass

vLLM is an inference and serving engine for large language models LLMs. From 0.3.0 until 0.22.0, a vulnerability in ASGI web servers and starlette's trust on those web servers enables an authentication bypass of the OpenAI API AuthenticationMiddleware. It allows to use the API without providing t...

CVE-2026-48746 vLLM: OpenAI auth bypass

vLLM is an inference and serving engine for large language models LLMs. From 0.3.0 until 0.22.0, a vulnerability in ASGI web servers and starlette's trust on those web servers enables an authentication bypass of the OpenAI API AuthenticationMiddleware. It allows to use the API without providing t...

CVE-2026-48746

vLLM is an inference and serving engine for large language models LLMs. From 0.3.0 until 0.22.0, a vulnerability in ASGI web servers and starlette's trust on those web servers enables an authentication bypass of the OpenAI API AuthenticationMiddleware. It allows to use the API without providing t...

CVE-2026-48746

vLLM OpenAI auth bypass (CVE-2026-48746) affects vLLM versions 0.3.0 through 0.21.0. Root cause: ASGI servers and Starlette trust the Host header from the request scope, enabling manipulation of the reconstructed URL path and bypassing the OpenAI API AuthenticationMiddleware for routes beginning ...

CVE-2026-53923

vLLM is an inference and serving engine for large language models LLMs. From 0.5.5 until 0.23.1rc0, integer truncation of tensor dimensions in vLLM's GGUF dequantize kernels csrc/quantization/gguf/ggufkernel.cu causes partial tensor processing. The output tensor is allocated at full size via...

CVE-2025-71379

vLLM versions = 0.6.3 and 0.9.0 contain multiple regular expression denial of service ReDoS vulnerabilities. Several regex patterns — in vllm/lora/utils.py, the phi4mini tool parser, and the OpenAI-compatible serving chat endpoint — are susceptible to catastrophic backtracking. An attacker...

CVE-2026-56340 vLLM - Denial of Service via Unvalidated Multimodal Embeddings

vLLM versions = 0.10.2 and 0.13.0 are missing sparse tensor validation in multimodal embeddings processing. Because PyTorch disables sparse tensor invariant checks by default, an attacker can submit crafted embedding requests with malformed negative or out-of-bounds tensor indices, when the...

CVE-2026-56340

vLLM versions = 0.10.2 and 0.13.0 are missing sparse tensor validation in multimodal embeddings processing. Because PyTorch disables sparse tensor invariant checks by default, an attacker can submit crafted embedding requests with malformed negative or out-of-bounds tensor indices, when the...

CVE-2026-56340 vLLM - Denial of Service via Unvalidated Multimodal Embeddings

vLLM versions = 0.10.2 and 0.13.0 are missing sparse tensor validation in multimodal embeddings processing. Because PyTorch disables sparse tensor invariant checks by default, an attacker can submit crafted embedding requests with malformed negative or out-of-bounds tensor indices, when the...

CVE-2026-56340

vLLM versions >= 0.10.2 and

EUVD-2026-38129

vLLM versions = 0.10.2 and 0.13.0 are missing sparse tensor validation in multimodal embeddings processing. Because PyTorch disables sparse tensor invariant checks by default, an attacker can submit crafted embedding requests with malformed negative or out-of-bounds tensor indices, when the...

EUVD-2025-210290

vLLM versions = 0.6.3 and 0.9.0 contain multiple regular expression denial of service ReDoS vulnerabilities. Several regex patterns — in vllm/lora/utils.py, the phi4mini tool parser, and the OpenAI-compatible serving chat endpoint — are susceptible to catastrophic backtracking. An attacker...

CVE-2025-71379

vLLM versions = 0.6.3 and 0.9.0 contain multiple regular expression denial of service ReDoS vulnerabilities. Several regex patterns — in vllm/lora/utils.py, the phi4mini tool parser, and the OpenAI-compatible serving chat endpoint — are susceptible to catastrophic backtracking. An attacker...

CVE-2025-71379

CVE-2025-71379 affects vLLM versions 0.6.3 through 0.8.x (before 0.9.0). The vulnerability is a set of regular expression denial of service (ReDoS) flaws in multiple components: (1) regex patterns in vllm/lora/utils.py, (2) the phi4mini tool parser, and (3) the OpenAI-compatible serving chat endp...

CVE-2025-71379 vllm - Regular Expression Denial of Service in Multiple Components

vLLM versions = 0.6.3 and 0.9.0 contain multiple regular expression denial of service ReDoS vulnerabilities. Several regex patterns — in vllm/lora/utils.py, the phi4mini tool parser, and the OpenAI-compatible serving chat endpoint — are susceptible to catastrophic backtracking. An attacker...

PT-2026-51172

Name of the Vulnerable Software and Affected Versions vLLM versions 0.10.2 through 0.12.x Description Multimodal embeddings processing lacks sparse tensor validation. Since PyTorch disables sparse tensor invariant checks by default, an attacker can submit crafted embedding requests containing...

GHSA-M6QW-4CW2-HM4M vulnerabilities

Vulnerabilities for packages: py3.13-scanner-test-libraries-aiohttp, tritonserver-backend-vllm-cuda-12.9, py3-vllm-cuda-12.9, py3-vllm-cuda-12.4, py3-vllm-cuda-13.0...

CVE-2026-50269 vulnerabilities

Vulnerabilities for packages: py3.13-scanner-test-libraries-aiohttp, tritonserver-backend-vllm-cuda-12.9, py3-vllm-cuda-12.9, py3-vllm-cuda-12.4, py3-vllm-cuda-13.0...

Improper Handling of Highly Compressed Data (Data Amplification)

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 Handling of Highly Compressed Data Data Amplification through the audio.py file. An attacker can cause excessive memory consumption by...