CVE-2026-56340: vLLM - Denial of Service via Unvalidated Multimodal Embeddings
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 Software
Remediation
Recommended actions to resolve this vulnerability, in priority order.
- Upgrade
Upgrade
vLLMto a version that resolves this vulnerability.Fixed in 0.13.0 - Compensating control
If upgrading is not immediately possible, disable/avoid the vLLM prompt-embeds feature so that crafted embedding requests with malformed (negative or out-of-bounds) tensor indices cannot reach multimodal embeddings processing (which is affected for vLLM versions >= 0.10.2 and < 0.13.0).
Event History
Frequently Asked Questions
What is the severity of CVE-2026-56340?
The severity of CVE-2026-56340 is rated high with a score of 8.8.
How do I fix CVE-2026-56340?
To fix CVE-2026-56340, upgrade vLLM to a version greater than 0.13.0.
What is the risk associated with CVE-2026-56340?
CVE-2026-56340 has a risk score of 79, indicating a significant potential for impact.
What versions of vLLM are affected by CVE-2026-56340?
vLLM versions from 0.10.2 to 0.12.9 are affected by CVE-2026-56340.
What type of vulnerability is CVE-2026-56340?
CVE-2026-56340 is an input validation vulnerability that can lead to Denial of Service.