CVE-2026-105754
Fixed in a distro release EPSS <1%CVSS 6.5
vLLM is an inference and serving engine for large language models. Prior to 0.30.0, the /inference/v1/generate endpoint in the disaggregated scale-out path accepts caller-supplied tensors in the features.kwargs_data field, cache identifiers in the features.mm_hashes field, ranges in the features.mm_placeholders field, and wire-selected multimodal field processors without rebinding them to the active model renderer contract. Forged grid geometry, field types, or non-positive placeholder lengths can terminate the shared EngineCore; when an attacker knows or can induce a victim's content hash, forged cache hashes can poison or retrieve cross-request encoder-cache state; and dropped sparse placeholder masks can alter replayed transport semantics. This issue is fixed in version 0.30.0.
Products: vllm-project vllm
Fixed upstream
| Ecosystem | Package | Fixed in |
|---|---|---|
| PyPI | vllm | 0.30.0 |
Distro releases
| Release | Package | Fixed in |
|---|---|---|
| Chainguard | kserve-huggingfaceserver-cuda-13.3 | no fix |
| Chainguard | lmcache-cuda-12.8 | 0 |
| Chainguard | nemo-rl-cuda-13.0-vllm | no fix |
| Chainguard | py3.10-vllm-cuda-12.4 | 0 |
| Chainguard | py3.12-vllm-cuda-12.4 | 0 |
| Chainguard | tritonserver-backend-vllm-cuda-13.0 | 25.11-r17 |
| Chainguard | vllm-cuda-13.2 | 0.32.0-r0 |
| Chainguard | vllm-openai-cuda-13.0 | 0.31.0-r0 |