Vulnerability Information
Although we use advanced large model technology, its output may still contain inaccurate or outdated information.Shenlong tries to ensure data accuracy, but please verify and judge based on the actual situation.
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