CVE-2026-115913
vLLM: Phi-4 multimodal audio encoder materializes and retains full attention matrices: a single max-length audio OOM-crashes the vLLM engine
- State
- Published
- Severity
- 6.5 Medium
- Published
- Oct 26, 2026
- Updated
- Oct 26, 2026
- Reserved
- Oct 23, 2026
Description
vLLM is an inference and serving engine for large language models. Prior to 0.32.0, the Phi-4 multimodal audio encoder in phi4mm_audio.py and phi4mm_utils.py uses eager attention by default, allowing a remote client to submit one legal long audio clip that causes MultiHeadedAttention.forward_attention to materialize and retain full attention matrices in self.attn. The scaled dot-product attention branch does not materialize these matrices. The resulting quadratic GPU-memory use can cause an out-of-memory condition and terminate EngineCore for all users. This issue is fixed in version 0.32.0.
Scores
| CVSS | Score | Vector | Source |
|---|---|---|---|
| 3.1 | 6.5 Medium | CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H | GitHub_M |
Weaknesses
- CWE-770 Allocation of Resources Without Limits or Throttling
Affected Products
| Product | Versions |
|---|---|
vllmvllm-project |
|
References
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