LMDeploy vulnerable to arbitrary code execution via eval() of untrusted quant_dtype in model config loading
Default status is the baseline for the product, each version can override it (e.g. patched versions marked unaffected).
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| InternLM | lmdeploy | affected |
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| Vendor | Product | Versions | ||||||||
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| Internlm | Lmdeploy |
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| Source | ID | Title |
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Github GHSA |
GHSA-3hmm-rh5q-gwwr | LMDeploy vulnerable to arbitrary code execution via eval() of untrusted quant_dtype in model config loading |
No CVSS v4.0
No CVSS v3.0
No CVSS v2
This CVE is not in the KEV list.
Exploit prediction score: < 1% (0.442% probability within 30 days)
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| Metrics |
ssvc
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| First Time appeared |
Internlm
Internlm lmdeploy |
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| Vendors & Products |
Internlm
Internlm lmdeploy |
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| Description | LMDeploy is a toolkit for compressing, deploying, and serving large language models. Versions 012.1 through 0.12.2 contain a code injection vulnerability in `lmdeploy/pytorch/config.py` line 620 that allows an attacker to execute arbitrary Python code by publishing a malicious HuggingFace model with a crafted `quantization_config.quant_dtype` value. When a user loads the model with lmdeploy, the `quant_dtype` is passed to `eval(f'torch.{quant_dtype}')` without any validation. Version 0.12.3 contains a patch. | |
| Title | LMDeploy vulnerable to arbitrary code execution via eval() of untrusted quant_dtype in model config loading | |
| Weaknesses | CWE-400 | |
| References |
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| Metrics |
cvssV3_1
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