Vendor
Project-MONAI
17 known vulnerabilities.
Project-MONAI at a glance
- Last 12 months
- 14
- Critical · all time
- 1
- Exploited · all time
- 0
- Public exploit · all time
- 0
Show as table
| Month | Vulnerabilities | Critical |
|---|---|---|
| Nov 2026 | 1 | 1 |
| Oct 2026 | 5 | 0 |
| Sep 2026 | 7 | 0 |
| Aug 2026 | 0 | 0 |
| Jul 2026 | 0 | 0 |
| Jun 2026 | 0 | 0 |
| May 2026 | 0 | 0 |
| Apr 2026 | 0 | 0 |
| Mar 2026 | 0 | 0 |
| Feb 2026 | 0 | 0 |
| Jan 2026 | 1 | 0 |
| Dec 2025 | 0 | 0 |
| Nov 2025 | 0 | 0 |
| Oct 2025 | 0 | 0 |
| Sep 2025 | 3 | 0 |
| Aug 2025 | 0 | 0 |
| Jul 2025 | 0 | 0 |
| Jun 2025 | 0 | 0 |
| May 2025 | 0 | 0 |
| Apr 2025 | 0 | 0 |
| Mar 2025 | 0 | 0 |
| Feb 2025 | 0 | 0 |
| Jan 2025 | 0 | 0 |
| Dec 2024 | 0 | 0 |
Products
17 results · Feed
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Critical 9.3
MONAI: MONAILabel Server Crash and Silent Inference Corruption via Crafted DICOM (pydicom DS/IS Validation Bypass)
MONAI (Medical Open Network for AI) is an AI toolkit for health care imaging. Prior to 1.6.1, PydicomReader._get_affine() trusts non-finite values in the DICOM PixelSpacing, ImagePositionPatient, and ImageOrientationPatient fields and composes them into an af…
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High 7.8
MONAI 1.6.0 before 1.6.1 Code Execution via Auto3DSeg algo_from_json()
MONAI from 1.6.0 before 1.6.1 contains a remote code execution vulnerability in Auto3DSeg algo_from_json() that allows attackers to run Python code via a crafted work directory's algo_object.json. Attackers can ship a malicious algorithm_templates module plus…
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Medium 5.9
MONAI before 1.6.1 Missing Integrity Verification via check_hash in Downloads
MONAI before 1.6.1 contains an insufficient integrity verification vulnerability in check_hash() that silently returns True when hash_val is None, with MD5 as the default hash type. Attackers performing man-in-the-middle or registry compromise can substitute …
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High 8.8
MONAI 1.2.0 before 1.6.1 Code Execution via bundle configs/logging.conf
MONAI from 1.2.0 before 1.6.1 contains a remote code execution vulnerability in ConfigWorkflow.__init__, which passes a bundle's configs/logging.conf to logging.config.fileConfig that eval()s handler class and args fields. Attackers can publish a malicious bu…
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High 7.3
MONAI 1.2.0 before 1.6.1 Insecure Deserialization RCE via nnUNetV2Runner postprocessing_file Path
MONAI 1.2.0 before 1.6.1 contains an insecure deserialization vulnerability in nnUNetV2Runner that unpickles the postprocessing_file path read from inference_information.json without confining it to the results directory. Attackers who can modify inference_in…
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High 7.5
MONAI 0.4.0 before 1.6.1 RCE via SENet Pretrained Weights Over Plaintext HTTP
MONAI 0.4.0 before 1.6.1 contains a remote code execution vulnerability that allows on-path attackers to execute code by tampering with SENet pretrained weights fetched over plaintext HTTP. Attackers can substitute a crafted .pth file that load_state_dict_fro…
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High 7.6
MONAI before 1.5.2 Remote Code Execution via Pickle Deserialization
MONAI before 1.5.2 contains a deserialization of untrusted data vulnerability in the algo_from_pickle function in monai/auto3dseg/utils.py. The function reads a .pkl file and passes its contents to pickle.loads without validating the data source or content. I…
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High 7.8
MONAI before 1.6.0 Remote Code Execution via NumpyReader
MONAI before 1.6.0 contains an unsafe deserialization vulnerability in the NumpyReader class that unconditionally uses numpy.load with allow_pickle=True when loading .npy and .npz files. Attackers can craft malicious .npy files with pickle payloads that execu…
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High 8.4
MONAI before 1.6.0 OS Command Injection via dataset_name_or_id
MONAI before 1.6.0 is vulnerable to OS command injection in the nnUNetV2Runner component (monai.apps.nnunet.nnunetv2_runner). User-controlled values taken from the YAML configuration file (notably dataset_name_or_id) and from CLI/kwargs arguments are concaten…
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High 7.8
MONAI before 1.6.0 Remote Code Execution via algo_from_pickle
MONAI versions before 1.6.0 contain a remote code execution vulnerability in the algo_from_pickle() function due to unsafe pickle.loads() deserialization in monai/auto3dseg/utils.py. Attackers can craft malicious pickle files that execute arbitrary system com…
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High 7.0
MONAI through 1.6.0 _get_fake_spatial_shape eval() Sandbox Bypass via Attribute Chains
MONAI through 1.6.0 contains an eval injection vulnerability in _get_fake_spatial_shape() in monai/bundle/scripts.py. The function validates shape expressions with a helper that walks the AST and only collects ast.Name nodes, rejecting any name other than 'p'…
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High 7.8
MONAI through 1.6.0 PersistentDataset Remote Code Execution via Pickle Cache
In MONAI 1.6.0, PersistentDataset (monai/data/dataset.py) explicitly rejects the combination track_meta=True with weights_only=True, forcing users who cache MetaTensors (the default tensor type in MONAI >= 1.0) to run torch.load(hashfile, weights_only=False).…
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High 7.8
MONAI through 1.6.0 Remote Code Execution via bundle configuration
MONAI through 1.6.0 contains a remote code execution vulnerability in the bundle configuration engine that resolves _target_ values to arbitrary importable callables without an allow list and passes $ expressions to Python eval(). Attackers can publish a mali…
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Medium 5.3
MONAI has Path Traversal (Zip Slip) in NGC Private Bundle Download
MONAI (Medical Open Network for AI) is an AI toolkit for health care imaging. In versions up to and including 1.5.1, a Path Traversal (Zip Slip) vulnerability exists in MONAI's `_download_from_ngc_private()` function. The function uses `zipfile.ZipFile.extrac…
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High 8.8
MONAI's unsafe use of Pickle deserialization may lead to RCE
MONAI (Medical Open Network for AI) is an AI toolkit for health care imaging. In versions up to and including 1.5.0, the `pickle_operations` function in `monai/data/utils.py` automatically handles dictionary key-value pairs ending with a specific suffix and d…
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High 8.8
MONAI's unsafe torch usage may lead to arbitrary code execution
MONAI (Medical Open Network for AI) is an AI toolkit for health care imaging. In versions up to and including 1.5.0, in `model_dict = torch.load(full_path, map_location=torch.device(device), weights_only=True)` in monai/bundle/scripts.py , `weights_only=True`…
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High 8.8
MONAI has path traversal issue that may lead to arbitrary file writes
MONAI (Medical Open Network for AI) is an AI toolkit for health care imaging. The extractall function `zip_file.extractall(output_dir)` is used directly to process compressed files. It is used in many places in the project. In versions up to and including 1.5…