6.3
Medium
CVE-2026-73557 vLLM is an inference and serving engine for large language models
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.
Affected products and versions
| Product | Affected versions | Fixed in |
|---|---|---|
| vllm 0.20 | 0.20.2rc0 → < 0.26.0 | 0.26.0 |
References
- github.com github.com
- github.com github.com
- github.com github.com
- github.com github.com
Timeline
- Published
- Last modified
Other CVEs of vllm
The 121 CVEs of vllm →
CVE-2026-115918
vLLM is an inference and serving engine for large language models
6.5
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CVE-2026-115917
vLLM is an inference and serving engine for large language models
3.4
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CVE-2026-115916
vLLM is an inference and serving engine for large language models
6.5
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CVE-2026-115915
vLLM is an inference and serving engine for large language models
8.1
High