Is CVE-2026-115913 exploited in the wild?

No. Junglewise Threat Intelligence has no report of CVE-2026-115913 being exploited in the wild.

How severe is CVE-2026-115913?

Medium severity, with a CVSS score of 6.5, published 26 October 2026.

Which products and versions are affected?

vllm (PyPI) < 0.32.0, ECOSYSTEM:introduced=0,fixed=0.32.0; vLLM Project vllm before 0.32.0.

How is CVE-2026-115913 attacked?

It is attacked over the network, in a software library.

Am I affected by CVE-2026-115913?

Check whether you run vllm (PyPI) or vLLM Project vllm at an affected version. Junglewise does that check for you around the clock: connect your code, cloud and domains, and it matches new vulnerabilities like this one against what you actually run and tells you when one reaches you.

CVE-2026-115913: vLLM Phi-4 multimodal audio encoder GPU memory exhaustion

Q: Which products and versions are affected?

vllm (PyPI) < 0.32.0, ECOSYSTEM:introduced=0,fixed=0.32.0; vLLM Project vllm before 0.32.0.

Q: Is there a fix for CVE-2026-115913?

Yes. vllm (PyPI): upgrade to 0.32.0 or later. Until then: Disable the eager attention path or explicitly configure the Phi-4 audio encoder to use PyTorch scaled-dot-product attention instead of eager attention evaluation. Junglewise finds every place you run it, drafts the upgrade and applies it once you approve.

Q: How is CVE-2026-115913 attacked?

It is attacked over the network, in a software library.

Q: Am I affected by CVE-2026-115913?

Check whether you run vllm (PyPI) or vLLM Project vllm at an affected version. Junglewise does that check for you around the clock: connect your code, cloud and domains, and it matches new vulnerabilities like this one against what you actually run and tells you when one reaches you.

CVE-2026-115913 · Severity: medium · CVSS 6.5 · Published 2026-10-26

vLLM is an inference engine for large language models that processes audio and other multimodal inputs. A remote attacker can send a single legitimate long audio file that causes the Phi-4 audio encoder to retain full attention matrices in GPU memory, exhausting GPU resources and crashing the service for all other users.

Technologies: vllm (PyPI), vLLM Project vllm. Vendors: PyPI, vLLM Project.

Quick answers

Is CVE-2026-115913 exploited in the wild?: No. Junglewise Threat Intelligence has no report of CVE-2026-115913 being exploited in the wild.
How severe is CVE-2026-115913?: Medium severity, with a CVSS score of 6.5, published 26 October 2026.
Which products and versions are affected?: vllm (PyPI) < 0.32.0, ECOSYSTEM:introduced=0,fixed=0.32.0; vLLM Project vllm before 0.32.0.
Is there a fix for CVE-2026-115913?: Yes. vllm (PyPI): upgrade to 0.32.0 or later. Until then: Disable the eager attention path or explicitly configure the Phi-4 audio encoder to use PyTorch scaled-dot-product attention instead of eager attention evaluation. Junglewise finds every place you run it, drafts the upgrade and applies it once you approve.
How is CVE-2026-115913 attacked?: It is attacked over the network, in a software library.
Am I affected by CVE-2026-115913?: Check whether you run vllm (PyPI) or vLLM Project vllm at an affected version. Junglewise does that check for you around the clock: connect your code, cloud and domains, and it matches new vulnerabilities like this one against what you actually run and tells you when one reaches you.

How to fix

vllm (PyPI): upgrade to 0.32.0 or later
```
pip install "vllm>=0.32.0"
```

Disable the eager attention path or explicitly configure the Phi-4 audio encoder to use PyTorch scaled-dot-product attention instead of eager attention evaluation.

Technical details

The Phi-4 multimodal audio encoder in vLLM versions prior to 0.32.0 uses eager attention evaluation by default in MultiHeadedAttention.forward_attention(), which materializes and retains full attention probability matrices in memory across all 24 encoder layers. A remote client can send a maximal-length audio input that causes the conformer encoder to pin multi-gigabyte tensors, triggering GPU out-of-memory and terminating the EngineCore service. The scaled dot-product attention branch does not materialize these matrices; the fix switches the default to use PyTorch's scaled-dot-product attention and removes matrix retention from the eager path.

Affected products

vLLM Project vLLM before 0.32.0

Identifiers

CVE-2026-115913
GHSA-8397-8qf6-f2gm

Timeline

2026-10-26: disclosed
2026-10-09: patched

References

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