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CVE-2025-46722

vLLM has a Weakness in MultiModalHasher Image Hashing Implementation

vLLM is an inference and serving engine for large language models (LLMs). In versions starting from 0.7.0 to before 0.9.0, in the file vllm/multimodal/hasher.py, the MultiModalHasher class has a security and data integrity issue in its image hashing method. Currently, it serializes PIL.Image.Image objects using only obj.tobytes(), which returns only the raw pixel data, without including metadata such as the image’s shape (width, height, mode). As a result, two images of different sizes (e.g., 30x100 and 100x30) with the same pixel byte sequence could generate the same hash value. This may lead to hash collisions, incorrect cache hits, and even data leakage or security risks. This issue has been patched in version 0.9.0.

CVSS 3.1 · 4.2 Medium EPSS < 1% KEV · Not listed
Vendors
Vllm Vllm-project
Products
Vllm Vllm
CVE-2025-48942

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

vLLM is an inference and serving engine for large language models (LLMs). In versions 0.8.0 up to but excluding 0.9.0, hitting the /v1/completions API with a invalid json_schema as a Guided Param kills the vllm server. This vulnerability is similar GHSA-9hcf-v7m4-6m2j/CVE-2025-48943, but for regex instead of a JSON schema. Version 0.9.0 fixes the issue.

CVSS 3.1 · 6.5 Medium EPSS < 1% KEV · Not listed
Vendors
Vllm Vllm-project
Products
Vllm Vllm
CVE-2025-48943

vLLM allows clients to crash the openai server with invalid regex

vLLM is an inference and serving engine for large language models (LLMs). Version 0.8.0 up to but excluding 0.9.0 have a Denial of Service (ReDoS) that causes the vLLM server to crash if an invalid regex was provided while using structured output. This vulnerability is similar to GHSA-6qc9-v4r8-22xg/CVE-2025-48942, but for regex instead of a JSON schema. Version 0.9.0 fixes the issue.

CVSS 3.1 · 6.5 Medium EPSS < 1% KEV · Not listed
Vendors
Vllm Vllm-project
Products
Vllm Vllm