CVE-2026-56340Vllm · Vllm
Vulnerability data via NVD (ingested)
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.
External references
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Shodan + Censys queries derived from NVD's CPE data. The vuln tag catches assets Shodan has explicitly linked to this CVE; the product / banner fingerprints find exposed instances even when the vuln tag was never applied (which is common).
vuln:CVE-2026-56340product:"Vllm Vllm"http.html:"Vllm"More intel sources (5)
vuln:CVE-2026-56340vulnerabilities.cve_id: CVE-2026-56340CVE-2026-56340CVE-2026-56340"CVE-2026-56340" exploit -site:nvd.nist.gov