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.
Metrics
Affected Vendors & Products
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| Vllm |
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References
History
Sat, 20 Jun 2026 18:45:00 +0000
| Type | Values Removed | Values Added |
|---|---|---|
| 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. | |
| Title | vLLM - Denial of Service via Unvalidated Multimodal Embeddings | |
| First Time appeared |
Vllm
Vllm vllm |
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| Weaknesses | CWE-20 | |
| CPEs | cpe:2.3:a:vllm:vllm:*:*:*:*:*:*:*:* | |
| Vendors & Products |
Vllm
Vllm vllm |
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| References |
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| Metrics |
cvssV3_1
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MITRE
Status: PUBLISHED
Assigner: VulnCheck
Published:
Updated: 2026-06-20T18:27:10.148Z
Reserved: 2026-06-20T13:13:56.012Z
Link: CVE-2026-56340
Vulnrichment
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NVD
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Redhat
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OpenCVE Enrichment
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