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.
Metrics
Affected Vendors & Products
References
History
Thu, 13 Aug 2026 19:00:00 +0000
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Vllm-project
Vllm-project vllm |
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Vllm-project
Vllm-project vllm |
Thu, 13 Aug 2026 15:15:00 +0000
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| Description | 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. | |
| Title | vLLM: Incomplete CVE-2025-62164 remediation can be bypassed by concurrent prompt parts | |
| Weaknesses | CWE-362 | |
| References |
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| Metrics |
cvssV4_0
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Status: PUBLISHED
Assigner: GitHub_M
Published:
Updated: 2026-08-13T17:52:52.386Z
Reserved: 2026-08-12T20:53:46.380Z
Link: CVE-2026-73557
No data.
Status : Received
Published: 2026-08-13T15:20:18.080
Modified: 2026-08-13T18:18:18.360
Link: CVE-2026-73557
No data.
OpenCVE Enrichment
Updated: 2026-08-13T18:45:04Z