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.
- CVSS 4.0
- 8.7
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 - CVSS 3.1
- 7.5
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H - EPSS
- 0.6% chance of exploitation in the next 30 days; higher than 50% of CVEs (scores of 2026-10-25)
- CWEs
- CWE-20, CWE-787
- Published
- Modified
- Record from
- the NVD, synced
Affected
- vllm:vllm
Packages (OSV)
| Advisory | Ecosystem | Package | Affected | Fixed in |
|---|---|---|---|---|
| GHSA-mcmc-2m55-j8jj | PyPI | vllm | >=0.10.2 <0.13.0 | 0.13.0 |
| PYSEC-2026-250 | PyPI | vllm | >=0.10.2 <0.13.0 | 0.13.0 |
References
- https://github.com/vllm-project/vllm/security/advisories/GHSA-mcmc-2m55-j8jj
- https://www.vulncheck.com/advisories/vllm-denial-of-service-via-unvalidated-multimodal-embeddings
- https://access.redhat.com/security/cve/CVE-2026-56340
- https://bugzilla.redhat.com/show_bug.cgi?id=2491060
- https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-56340.json