Description
vLLM versions >= 0.10.2 and < 0.13.0 are missing sparse tensor validation in multimodal embeddings processing. Because PyTorch disables sparse tensor invariant checks by default, an attacker can submit crafted embedding requests with malformed (negative or out-of-bounds) tensor indices, when the prompt-embeds feature is enabled, to trigger crashes or resource exhaustion (denial of service), with potential for out-of-bounds/write-what-where memory corruption. This continues CVE-2025-62164, whose prior fix only disabled the feature by default rather than addressing the root cause.
Affected products
| Vendor | Product | Affected | Fixed |
|---|---|---|---|
| vLLM | vLLM | 0.10.2 – < 0.13.0 | 0.13.0 |
Affected packages
| Ecosystem | Package | Affected | Fixed | Record |
|---|---|---|---|---|
| PyPI | vllm | >= 0.10.2, < 0.13.0 | 0.13.0 | GHSA-mcmc-2m55-j8jj |
Advisories 1
- WID-SEC-2026-2024 vllm: Schwachstelle ermöglicht Denial of Service BSI CERT-Bund (WID) · Jun 21, 2026
References
- GitHub Security Advisory (GHSA-mcmc-2m55-j8jj) vendor-advisory
- VulnCheck Advisory: vLLM - Denial of Service via Unvalidated Multimodal Embeddings third-party-advisory