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CVE-2026-115913

nvd nist
Published: Oct 26, 2026Modified: Oct 28, 2026

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6.5
Vector
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
Exploitability: 2.8 / Impact: 3.6
Source: security-advisories@github.com (Secondary)

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.

Affected (1)

Products: Vllm: Vllm
1 product
Vllm
Configuration A
1 vulnerable
Vulnerable SoftwareAffected Versions
0.31.0 ≤ version < 0.32.0

References (4)

Source: security-advisories@github.com
Patch
Source: security-advisories@github.com
Release Notes
Source: security-advisories@github.com
ExploitPatchVendor Advisory

Timeline

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