vllm vulnerabilities

CVEs whose affected-version data names the vllm package (pip). Each record lists the affected and patched versions; check a specific version with the dependency checker or POST /api/sbom.

129 CVEsRSS

CVE-2026-5497High· 7.5

4mo ago

vLLM versions 0.8.0 and later are vulnerable to an Out-of-Memory (OOM) Denial of Service (DoS) attack due to unbounded frame count processing in the `VideoMediaIO.load_base64()` method

vLLM versions 0.8.0 and later are vulnerable to an Out-of-Memory (OOM) Denial of Service (DoS) attack due to unbounded frame count processing in the `VideoMediaIO.load_base64()` method. When processing `video/jpeg` data URLs, the method …

▾ Twilightvllm · vllmEPSS 0.54%via NVD

CVE-2026-9540Medium· 5.3

5mo ago

vllm has Improper Resource Shutdown or Release

▾ Sunlitvllm · vllmEPSS 0.43%via OSV

CVE-2026-7141Medium· 5.6

6mo ago

vLLM makes Use of Uninitialized Resource

▾ Sunlitvllm · vllmEPSS 0.29%via OSV

CVE-2026-34756Medium· 6.5

7mo ago

vLLM is an inference and serving engine for large language models (LLMs)

vLLM is an inference and serving engine for large language models (LLMs). From 0.1.0 to before 0.19.0, a Denial of Service vulnerability exists in the vLLM OpenAI-compatible API server. Due to the lack of an upper bound validation on the…

▾ Sunlitvllm · vllmEPSS 0.42%via NVD

CVE-2026-34755Medium· 6.5

7mo ago

vLLM is an inference and serving engine for large language models (LLMs)

vLLM is an inference and serving engine for large language models (LLMs). From 0.7.0 to before 0.19.0, the VideoMediaIO.load_base64() method at vllm/multimodal/media/video.py splits video/jpeg data URLs by comma to extract individual JPE…

▾ Sunlitvllm · vllmEPSS 0.46%via NVD

CVE-2026-34753Medium· 5.4PoC

7mo ago

vLLM: Server-Side Request Forgery (SSRF) in `download_bytes_from_url `

▾ Twilightvllm · vllmEPSS 0.25%via OSV

CVE-2026-34760High· 7.1

7mo ago

vLLM is an inference and serving engine for large language models (LLMs). From version 0.5.5 to before version 0.18.0, Librosa defaults t…

vLLM is an inference and serving engine for large language models (LLMs). From version 0.5.5 to before version 0.18.0, Librosa defaults to using numpy.mean for mono downmixing (to_mono), while the international standard ITU-R BS.775-4 sp…

▾ Twilightvllm · vllmEPSS 0.27%via OSV

CVE-2026-27893High· 8.8

7mo ago

vLLM is an inference and serving engine for large language models (LLMs)

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 files hardcode `trust_remote_code=True` when loading sub-components, bypassing the…

▾ Twilightvllm · vllmEPSS 1.4%via NVD

CVE-2026-25960Medium· 5.4

7mo ago

vLLM has SSRF Protection Bypass

▾ Sunlitvllm · vllmEPSS 0.57%via OSV

CVE-2026-22778Critical· 9.8PoC

9mo ago

vLLM is an inference and serving engine for large language models (LLMs)

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 endpoint, PIL throws an error. vLLM returns this error to the client, leaking a hea…

▾ Abyssalvllm · vllmEPSS 19%via NVD

CVE-2026-24779High· 7.1

9mo ago

vLLM is an inference and serving engine for large language models (LLMs)

vLLM is an inference and serving engine for large language models (LLMs). Prior to version 0.14.1, a Server-Side Request Forgery (SSRF) vulnerability exists in the `MediaConnector` class within the vLLM project's multimodal feature set. …

▾ Twilightvllm · vllmEPSS 0.58%via NVD

CVE-2026-22807High· 8.8PoC

9mo ago

vLLM is an inference and serving engine for large language models (LLMs)

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_map` dynamic modules during model resolution without gating on `trust_remote_…

▾ Midnightvllm · vllmEPSS 0.98%via NVD

CVE-2026-22773Medium· 6.5

9mo ago

vLLM is an inference and serving engine for large language models (LLMs)

vLLM is an inference and serving engine for large language models (LLMs). In versions from 0.6.4 to before 0.12.0, users can crash the vLLM engine serving multimodal models that use the Idefics3 vision model implementation by sending a s…

▾ Sunlitvllm · vllmEPSS 0.44%via NVD

CVE-2025-62372Medium· 6.5

11mo ago

vLLM vulnerable to DoS with incorrect shape of multimodal embedding inputs

▾ Sunlitvllm · vllmEPSS 0.41%via OSV

CVE-2025-62164High· 8.8

vllm vulnerabilities

vLLM versions 0.8.0 and later are vulnerable to an Out-of-Memory (OOM) Denial of Service (DoS) attack due to unbounded frame count processing in the `VideoMediaIO.load_base64()` method

vllm has Improper Resource Shutdown or Release

vLLM makes Use of Uninitialized Resource

vLLM is an inference and serving engine for large language models (LLMs)

vLLM is an inference and serving engine for large language models (LLMs)

vLLM: Server-Side Request Forgery (SSRF) in `download_bytes_from_url `

vLLM is an inference and serving engine for large language models (LLMs). From version 0.5.5 to before version 0.18.0, Librosa defaults t…

vLLM is an inference and serving engine for large language models (LLMs)

vLLM has SSRF Protection Bypass

vLLM is an inference and serving engine for large language models (LLMs)

vLLM is an inference and serving engine for large language models (LLMs)

vLLM is an inference and serving engine for large language models (LLMs)

vLLM is an inference and serving engine for large language models (LLMs)

vLLM vulnerable to DoS with incorrect shape of multimodal embedding inputs

vLLM deserialization vulnerability leading to DoS and potential RCE

vLLM: Resource-Exhaustion (DoS) through Malicious Jinja Template in OpenAI-Compatible Server

vLLM is vulnerable to Server-Side Request Forgery (SSRF) through `MediaConnector` class

vLLM has remote code execution vulnerability in the tool call parser for Qwen3-Coder

vLLM has a Regular Expression Denial of Service (ReDoS, Exponential Complexity) Vulnerability in `pythonic_tool_parser.py`

vLLM has a Weakness in MultiModalHasher Image Hashing Implementation

vLLM allows clients to crash the openai server with invalid regex

vLLM DOS: Remotely kill vllm over http with invalid JSON schema

Potential Timing Side-Channel Vulnerability in vLLM’s Chunk-Based Prefix Caching

vLLM Tool Schema allows DoS via Malformed pattern and type Fields

vLLM Allows Remote Code Execution via PyNcclPipe Communication Service

Remote Code Execution Vulnerability in vLLM Multi-Node Cluster Configuration

vLLM Vulnerable to Remote Code Execution via Mooncake Integration

phi4mm: Quadratic Time Complexity in Input Token Processing​ leads to denial of service

Data exposure via ZeroMQ on multi-node vLLM deployment

CVE-2025-24357 Malicious model remote code execution fix bypass with PyTorch < 2.6.0

phi4mm: Quadratic Time Complexity in Input Token Processing leads to denial of service