CVE-2026-7669— sglang 注入漏洞

sgl-project SGLang HuggingFace Transformer hf_transformers_utils.py get_tokenizer code injection

A vulnerability was detected in sgl-project SGLang up to 0.5.9. Impacted is the function get_tokenizer of the file python/sglang/srt/utils/hf_transformers_utils.py of the component HuggingFace Transformer Handler. The manipulation of the argument trust_remote_code with the input False as part of Boolean results in code injection. The attack can be executed remotely. A high complexity level is associated with this attack. The exploitability is considered difficult. In get_tokenizer(), when the caller passes trust_remote_code=False and HuggingFace transformers v5 returns a TokenizersBackend instance (the generic fallback for tokenizer classes not in the registry), SGLang silently re-invokes AutoTokenizer.from_pretrained with trust_remote_code=True, overriding the caller's explicit security setting. A model repository containing a malicious tokenizer.py referenced via auto_map in tokenizer_config.json will execute arbitrary Python in the SGLang process during this second call. No log line or warning is emitted. The override affects all current SGLang versions because transformers==5.3.0 is pinned in pyproject.toml. Both tokenizer_mode="auto" and tokenizer_mode="slow" are affected. The exploit is now public and may be used. The vendor was contacted early about this disclosure but did not respond in any way.

CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:L/I:L/A:L

对生成代码的控制不恰当(代码注入)

sglang 注入漏洞

sglang是sgl-project开源的一个用于加速大模型推理的编程语言与运行时系统。 SGLang 0.5.9及之前版本存在注入漏洞，该漏洞源于python/sglang/srt/utils/hf_transformers_utils.py文件中get_tokenizer函数对参数trust_remote_code的操作，可能导致代码注入。

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