漏洞信息
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Vulnerability Title
vLLM: Incomplete CVE-2025-62164 remediation can be bypassed by concurrent prompt parts
Vulnerability 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.
CVSS Information
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
Vulnerability Type
使用共享资源的并发执行不恰当同步问题(竞争条件)
Vulnerability Title
vLLM 竞争条件问题漏洞
Vulnerability Description
vLLM是vLLM团队开源的一个适用于 LLM 的高吞吐量和内存高效推理和服务引擎。 vLLM 0.20.2rc0版本至0.26.0之前版本存在竞争条件问题漏洞,该漏洞源于并发提交的prompt_embeds部分与torch.sparse.check_sparse_tensor_invariants的进程全局状态保存、启用和恢复操作产生竞争,可能导致无效稀疏张量到达tensor.to_dense,绕过CVE-2025-62164防护。
CVSS Information
N/A
Vulnerability Type
N/A