CVE Catalog

CVE-2026-73557

MediumCVSS 6.3
Published: Updated: Translated: NVD NIST

Exploitation Probability (EPSS)

Low risk
0.25%

17th percentile - higher than 17% of all known CVEs

Summary

In vLLM 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.

Risk Assessment

The risk is the possibility of data integrity compromise or incorrect processing of input data, which could lead to erroneous results or potential information leakage.

Recommendation

It is recommended to upgrade vLLM to version 0.26.0 or later, which includes a fix for this vulnerability.

Original NVD description (English source)

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.

Vulnerability data from NVD (NIST) · CISA KEV · EPSS