High severity · published Jan 10, 2026
CVE-2026-22773
vLLM is an inference and serving engine for large language models (LLMs)
7.5
CVSS
0.4%
EPSS
No
On KEV
Description
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 specially crafted 1x1 pixel image. This causes a tensor dimension mismatch that results in an unhandled runtime error, leading to complete server termination. This issue has been patched in version 0.12.0.
CVSS vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
Attack vector
Network
Complexity
Low
Privileges
None
User interaction
None
Confidentiality
None
Integrity
None
Availability
High
Scope
Unchanged
Exploitation
Is it being used?
Exploit prediction (EPSS)0.4% · higher than 38% of CVEs
Exploited in the wildNo evidence yet
CISA KEVNot listed
Ransomware campaign useNot known
Affected products
Which versions
VL
Vllm · Vllm
0.6.4 before 0.12.0 · source: NVD
References
NVD
https://nvd.nist.gov/vuln/detail/CVE-2026-22773
CVE.org
https://www.cve.org/CVERecord?id=CVE-2026-22773
Exploit
https://github.com/vllm-project/vllm/security/advisories/GHSA-grg2-63fw-f2qr
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