CVE-2026-73557
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
Summary
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.
Affected Software
| Vendor | Product | Version Range | Status |
|---|---|---|---|
| vllm-project | vllm | >= 0.20.2rc0, < 0.26.0 | affected |
Weaknesses
- CWE-362: CWE-362: Concurrent Execution using Shared Resource with Improper Synchronization ('Race Condition')
ADP Enrichment
CISA ADP Vulnrichment
- SSVC:
- Exploitation: none
- Automatable: no
- Technical Impact: partial
References
- https://github.com/vllm-project/vllm/security/advisories/GHSA-pr7f-p5mw-fc87
- https://github.com/vllm-project/vllm/pull/48583
- https://github.com/vllm-project/vllm/commit/793cf79c89d4049124e756915468ac30318f2e50
- https://github.com/vllm-project/vllm/releases/tag/v0.26.0
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