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
- Vendor
- Red Hat, Red Hat, vLLM, Red Hat, Red Hat, Red Hat, Red Hat, Red Hat, Red Hat, Red Hat, Red Hat, Red Hat, Red Hat, Red Hat, Red Hat, Red Hat, Red Hat, Red Hat, Red Hat, Red Hat, Red Hat, Red Hat, Red Hat, Red Hat, Red Hat, Red Hat, Red Hat
- Product
- Red Hat Enterprise Linux AI (RHEL AI) 3, Red Hat OpenShift AI (RHOAI), vLLM, Red Hat AI Inference Server, Red Hat OpenShift AI (RHOAI), Red Hat Enterprise Linux AI (RHEL AI) 3, Red Hat AI Inference Server, Red Hat AI Inference Server, Red Hat AI Inference Server, Red Hat OpenShift AI (RHOAI), Red Hat Enterprise Linux AI (RHEL AI) 3, Red Hat Enterprise Linux AI (RHEL AI) 3, Red Hat AI Inference Server, Red Hat AI Inference Server, Red Hat Enterprise Linux AI (RHEL AI) 3, Red Hat AI Inference Server, Red Hat OpenShift AI (RHOAI), Red Hat AI Inference Server, Red Hat AI Inference Server, Red Hat AI Inference Server, Red Hat AI Inference Server, Red Hat AI Inference Server, Red Hat OpenShift AI (RHOAI), Red Hat AI Inference Server, Red Hat Enterprise Linux AI (RHEL AI) 3, Red Hat Enterprise Linux AI (RHEL AI) 3, Red Hat OpenShift AI (RHOAI)
- Provider severity
- HIGH
- Conflicts
- 3