漏洞信息
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Vulnerability Title
vLLM - Denial of Service via Unvalidated Multimodal Embeddings
Vulnerability Description
vLLM versions >= 0.10.2 and < 0.13.0 are missing sparse tensor validation in multimodal embeddings processing. Because PyTorch disables sparse tensor invariant checks by default, an attacker can submit crafted embedding requests with malformed (negative or out-of-bounds) tensor indices, when the prompt-embeds feature is enabled, to trigger crashes or resource exhaustion (denial of service), with potential for out-of-bounds/write-what-where memory corruption. This continues CVE-2025-62164, whose prior fix only disabled the feature by default rather than addressing the root cause.
CVSS Information
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H
Vulnerability Type
输入验证不恰当
Vulnerability Title
vLLM 输入验证错误漏洞
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 0.10.2版本至0.11.1之前版本存在输入验证错误漏洞,该漏洞源于多模态嵌入处理中缺少稀疏张量验证,可能导致攻击者在prompt-embeds功能启用时发送特制嵌入请求,触发崩溃或资源耗尽,并存在越界内存破坏风险。
CVSS Information
N/A
Vulnerability Type
N/A