Vulnerability Description
vLLM is an inference and serving engine for large language models. Prior to 0.26.0, the MiMoV2OmniMultiModalProcessor in vllm/transformers_utils/processors/mimo_v2_omni.py passes attacker-controlled image and audio strings through _fetch_image, requests.get, and Image.open instead of MediaConnector, bypassing allowed_media_domains and allowed_local_media_path protections and allowing server-side requests and reads of arbitrary files accessible to the vLLM process. This issue is fixed in version 0.26.0.
CVSS Score
MEDIUM
Related Weaknesses (CWE)
References
- https://github.com/vllm-project/vllm/commit/54503ecec0f3ac31e5ecfc5f28652e4cc423
- https://github.com/vllm-project/vllm/pull/43117
- https://github.com/vllm-project/vllm/releases/tag/v0.26.0
- https://github.com/vllm-project/vllm/security/advisories/GHSA-4hhp-h66f-j5j7
- https://github.com/vllm-project/vllm/security/advisories/GHSA-4hhp-h66f-j5j7
FAQ
What is CVE-2026-73560?
CVE-2026-73560 is a vulnerability with a CVSS score of 6.5 (MEDIUM). vLLM is an inference and serving engine for large language models. Prior to 0.26.0, the MiMoV2OmniMultiModalProcessor in vllm/transformers_utils/processors/mimo_v2_omni.py passes attacker-controlled i...
How severe is CVE-2026-73560?
CVE-2026-73560 has been rated MEDIUM with a CVSS base score of 6.5/10. Review the CVSS metrics above for detailed severity breakdown.
Is there a patch for CVE-2026-73560?
Check the references section above for vendor advisories and patch information. Review vendor security bulletins for remediation guidance.