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AI agent vulnerability · vLLM

CVE-2026-56340: vLLM introduced enhanced protection for CVE-2025-62164

highCVSS 3.1 8.8GHSA-mcmc-2m55-j8jj

Summary The fix here for CVE-2025-62164 is not sufficient. The fix only disables prompt embeds by default rather than addressing the root cause, so the DoS vulnerability remains when the feature is enabled. Details vLLM's pending change attempts to fix the root cause, which is the missing sparse tensor validation.

Published Jan 8, 2026 · Updated Sep 11, 2026

Affected packages

vllm

Ecosystem
PyPI
Affected
>= 0.10.2, < 0.13.0
Fixed in
0.13.0
Check
pip show vllm

Advisory details

From the GitHub Advisory Database (CC BY 4.0).

Summary

The fix here for CVE-2025-62164 is not sufficient. The fix only disables prompt embeds by default rather than addressing the root cause, so the DoS vulnerability remains when the feature is enabled.

Details

vLLM's pending change attempts to fix the root cause, which is the missing sparse tensor validation. PyTorch (~v2.0) disables sparse tensor validation (specifically, sparse tensor invariants checks) by default for performance reasons. vLLM is adding the sparse tensor validation to ensure indices are valid, non-negative, and within bounds. These checks help catch malformed tensors.

PoC

NA

Impact

Current fix only added a flag to disable/enable prompt embeds, so by default, prompt embeds feature is disabled in vLLM, which stops DoS attacks through the embeddings. However, It doesn’t address the problem when the flag is enabled and there is still potential for DoS attacks.

Changes

  • https://github.com/vllm-project/vllm/pull/30649

References

How this page is made: the data panel comes from the GitHub Advisory Database, CISA’s KEV catalog, the NVD and FIRST EPSS, and updates twice a day. No analysis has been written for this entry yet. Methodology

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