Vllm-Project Vllm
97 CVEs affecting Vllm-Project Vllm. Latest disclosed: 2026-10-12. Critical: 6, High: 24.
| CVE | Severity | Score | Published | Summary |
|---|---|---|---|---|
CVE-2025-32444 | Critical | 10.0 | 2025-04-30 | vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs. Versions starting from 0.6.5 and prior to 0.8.5, having vLLM integration… |
CVE-2026-22778 | Critical | 9.8 | 2026-02-02 | vLLM is an inference and serving engine for large language models (LLMs). From 0.8.3 to before 0.14.1, when an invalid image is sent to vLLM's multimodal endpo… |
CVE-2025-47277 | Critical | 9.8 | 2025-05-20 | vLLM, an inference and serving engine for large language models (LLMs), has an issue in versions 0.6.5 through 0.8.4 that ONLY impacts environments using the `… |
CVE-2024-9053 | Critical | 9.8 | 2025-03-20 | vllm-project vllm version 0.6.0 contains a vulnerability in the AsyncEngineRPCServer() RPC server entrypoints. The core functionality run_server_loop() calls t… |
CVE-2026-48746 | Critical | 9.1 | 2026-06-22 | 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… |
CVE-2025-29783 | Critical | 9.0 | 2025-03-19 | vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs. When vLLM is configured to use Mooncake, unsafe deserialization exposed d… |
CVE-2026-54232 | High | 8.8 | 2026-06-22 | vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.22.1, the vLLM Dockerfile is vulnerable to a dependency confusion attack t… |
CVE-2026-27893 | High | 8.8 | 2026-03-27 | vLLM is an inference and serving engine for large language models (LLMs). Starting in version 0.10.1 and prior to version 0.18.0, two model implementation file… |
CVE-2026-22807 | High | 8.8 | 2026-01-21 | vLLM is an inference and serving engine for large language models (LLMs). Starting in version 0.10.1 and prior to version 0.14.0, vLLM loads Hugging Face `auto… |
CVE-2025-62164 | High | 8.8 | 2025-11-21 | vLLM is an inference and serving engine for large language models (LLMs). From versions 0.10.2 to before 0.11.1, a memory corruption vulnerability could lead t… |
CVE-2025-30165 | High | 8.0 | 2025-05-06 | vLLM is an inference and serving engine for large language models. In a multi-node vLLM deployment using the V0 engine, vLLM uses ZeroMQ for some multi-node co… |
CVE-2026-90553 | High | 7.8 | 2026-09-12 | vLLM before 0.28.0 contains a remote code execution vulnerability in the LlavaOnevision2 processor loader that ignores the trust_remote_code parameter when loa… |
CVE-2026-94627 | High | 7.5 | 2026-09-21 | vLLM Mooncake connector through 0.29.0 fails to properly manage GPU KV cache block ownership when concurrent child requests share a single transfer ID in prefi… |
CVE-2026-94626 | High | 7.5 | 2026-09-21 | vLLM through 0.29.0 fails to validate the tp_size parameter in kv_transfer_params on OpenAI-compatible completion endpoints, allowing attackers to allocate unb… |
CVE-2026-94624 | High | 7.5 | 2026-09-21 | vLLM through 0.29.0 contains a denial of service vulnerability in P2P KV offloading when OffloadingConnector is configured with TieringOffloadingSpec and a pee… |
CVE-2026-94623 | High | 7.5 | 2026-09-21 | vLLM through 0.29.0 contains a denial of service vulnerability in the NIXL connector's prefix caching implementation that fails to properly validate block coun… |
CVE-2026-94622 | High | 7.5 | 2026-09-21 | vLLM versions through 0.29.0 contain a denial of service vulnerability in the NIXL connector's metadata handling for prefill/decode disaggregated deployments… |
CVE-2026-93592 | High | 7.5 | 2026-09-18 | vLLM versions before 0.28.0 fail to validate the lower bound of token IDs in the /v1/embeddings and /pooling endpoints, allowing unauthenticated attackers to c… |
CVE-2026-93436 | High | 7.5 | 2026-09-17 | vLLM through 0.29.0 fails to properly clean up decode-side metadata for rejected inference requests in prefill/decode disaggregated deployments. Remote attacke… |
CVE-2026-55574 | High | 7.5 | 2026-07-06 | vLLM is a high-throughput and memory-efficient inference and serving engine for LLMs. Prior to 0.24.0, the structured_outputs.regex API parameter passes a user… |