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Vulnerability record/PUBLISHED/Published Jun 20, 2026 18:27:10 UTC

CVE-2026-56340

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.

Base score8.7/ 10
SeverityHighCVSS 4.0

Exploitability / impact

CVSS metric breakdown

Vector-derived attributes
Base severityHigh
Attack vectorNetworkAV
Attack complexityLowAC
Attack requirementsNoneAT
Privileges requiredLowPR
User interactionNoneUI
Vulnerable system confidentialityHighVC
Vulnerable system integrityHighVI
Vulnerable system availabilityHighVA
Subsequent system confidentialityNoneSC
Subsequent system integrityNoneSI
Subsequent system availabilityNoneSA
CVSS vector stringCVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N

CVSS communicates standardized severity and impact characteristics. It does not establish whether a system is exploitable in your specific environment.

Record context

CVE Numbering AuthorityVulnCheck
Last updatedNov 8, 2026 14:06:02 UTC
PublishedJun 20, 2026 18:27:10 UTC
ReservedJun 20, 2026 13:13:56 UTC