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 0.28.0之前版本存在代码注入漏洞,该漏洞源于LlavaOnevision2处理器加载器在加载远程处理器类时忽略trust_remote_code参数,攻击者可构造在processing_llava_onevision2.py中包含任意代码的恶意模型,即使trust_remote_code设置为False也会以vLLM进程权限执行任意代码。
| Vendor | Product | Version Range | Status |
|---|---|---|---|
| vllm-project | vLLM | < 0.28.0 |
affected |
0.28.0 |
unaffected |
Although we use advanced large model technology, its output may still contain inaccurate or outdated information.Shenlong tries to ensure data accuracy, but please verify and judge based on the actual situation.
| Vendor | Product | Affected Versions | CPE | Subscribe |
|---|---|---|---|---|
| vllm-project | vLLM | 0 ~ 0.28.0 | - |
|
| # | POC Description | Source Link | Shenlong Link |
|---|
No public POC found.
Login to generate AI POC| CVE-2026-90555 | 6.5 MEDIUM | vLLM before 0.28.0 Denial of Service via Audio Header |
| CVE-2026-90554 | 6.2 MEDIUM | vLLM before 0.28.0 Denial of Service via audio extraction |
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