vLLM is an inference and serving engine for large language models. From 0.20.2rc0 until 0.26.0, safe_load_prompt_embeds in vllm/renderers/embed_utils.py uses torch.sparse.check_sparse_tensor_invariants, whose process-global save, enable, and restore state can be raced by concurrent prompt_embeds parts submitted to POST /v1/chat/completions through AsyncMultiModalItemTracker.resolve_items, asyncio.gather, and the default executor, allowing an invalid sparse tensor to reach tensor.to_dense despite the CVE-2025-62164 guard when enable_prompt_embeds is enabled. This issue is fixed in version 0.26.0.
https://github.com/vllm-project/vllm/security/advisories/GHSA-pr7f-p5mw-fc87
https://github.com/vllm-project/vllm/releases/tag/v0.26.0
https://github.com/vllm-project/vllm/pull/48583
https://github.com/vllm-project/vllm/commit/793cf79c89d4049124e756915468ac30318f2e50
Published: 2026-08-13
Updated: 2026-09-09
Base Score: 6.4
Vector: CVSS2#AV:N/AC:L/Au:N/C:P/I:P/A:N
Severity: Medium
Base Score: 7.5
Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:H/A:N
Severity: High
Base Score: 6.3
Vector: CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N
Severity: Medium
EPSS: 0.00404