| Component | vLLM |
| Severity | medium (CVSS 6.5) |
| CVSS vector | CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H |
| Published (NVD) | 2026-05-12 |
| Last modified | 2026-06-17 |
| Affected versions | vllm >= 0.6.1, < 0.20.0 |
| Fixed in | 0.20.0 |
| Weakness | CWE-129 |
| CISA KEV | not listed |
NVD description
vLLM is an inference and serving engine for large language models (LLMs). From 0.6.1 to before 0.20.0, there is a a Token Injection vulnerability in vLLM’s multimodal processing. Unauthenticated, text-only prompts that spell special tokens are interpreted as control. Image and video placeholder sequences supplied without matching data cause vLLM to index into empty grids during input-position computation, raising an unhandled IndexError and terminating the worker or degrading availability. Multimodal paths that rely on image_grid_thw/video_grid_thw are affected. This vulnerability is fixed in 0.20.0.
What to do
- Upgrade vLLM to
0.20.0or later. - Do not expose the component's API or UI to the internet without authentication in front of it.
Sources
- NVD: CVE-2026-44222
- https://github.com/vllm-project/vllm/security/advisories/GHSA-hpv8-x276-m59f
- https://github.com/vllm-project/vllm/issues/32656
Read more
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