vLLM - Denial of Service via Unvalidated Multimodal Embeddings
21Vexday Risk Score
No sign of exploitation. No public exploitation artifact known so far.
ssvc Trackcvss 8.7epss 0.4%
exploitation probability
0.4%top 72% of all CVEs
observed exploitation
nono source reports it
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.
CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N
Affected products
vLLM · vLLMReferences
https://access.redhat.com/security/cve/CVE-2026-56340https://bugzilla.redhat.com/show_bug.cgi?id=2491060https://github.com/vllm-project/vllm/security/advisories/GHSA-mcmc-2m55-j8jjhttps://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-56340.jsonhttps://www.vulncheck.com/advisories/vllm-denial-of-service-via-unvalidated-multimodal-embeddings