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 0.26.0之前版本存在信息泄露漏洞,该漏洞源于validation_exception_handler和sanitize_message处理不当,未移除traceback风格文件路径,可能导致未经身份验证的攻击者通过向/v1/chat/completions、/v1/completions、/tokenize和/detokenize发送畸形JSON请求,泄露操作系统用户名、主目录和虚拟环境路径、Python版
| Vendor | Product | Version Range | Status |
|---|---|---|---|
| vllm-project | vllm | < 0.26.0 |
affected |
Although we use advanced large model technology, its output may still contain inaccurate or outdated information.Shenlong tries to ensure data accuracy, but please verify and judge based on the actual situation.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 | < 0.26.0 | - |
|
| # | POC Description | Source Link | Shenlong Link |
|---|
No public POC found.
Login to generate AI POC| CVE-2026-73559 | 6.5 MEDIUM | vLLM: Completion prompt lists fan out into unbounded engine requests |
| CVE-2026-73557 | 6.3 MEDIUM | vLLM: Incomplete CVE-2025-62164 remediation can be bypassed by concurrent prompt parts |
| CVE-2026-73556 | 5.3 MEDIUM | vLLM: ReDoS via structured_outputs.regex in the lm-format-enforcer backend (no compile tim |
| CVE-2026-73558 | 5.3 MEDIUM | vLLM: Cross-User Data Leak Vulnerability |
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