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 affine matrix without validation. An unauthenticated attacker who can upload a crafted DICOM to a default MONAILabel deployment can propagate NaN or infinity values through LoadImaged, Spacingd, model inference, and output writing, causing inference failures, persistent datastore poisoning, or geometrically corrupted results. This issue is fixed in version 1.6.1.
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History
Fri, 06 Nov 2026 19:30:00 +0000
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Thu, 05 Nov 2026 22:00:00 +0000
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Project-monai
Project-monai monai |
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Project-monai
Project-monai monai |
Thu, 05 Nov 2026 20:45:00 +0000
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| Description | 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 affine matrix without validation. An unauthenticated attacker who can upload a crafted DICOM to a default MONAILabel deployment can propagate NaN or infinity values through LoadImaged, Spacingd, model inference, and output writing, causing inference failures, persistent datastore poisoning, or geometrically corrupted results. This issue is fixed in version 1.6.1. | |
| Title | MONAI: MONAILabel Server Crash and Silent Inference Corruption via Crafted DICOM (pydicom DS/IS Validation Bypass) | |
| Weaknesses | CWE-20 CWE-682 |
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| Metrics |
cvssV3_1
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Status: PUBLISHED
Assigner: GitHub_M
Published: 2026-11-05T20:44:30.681Z
Updated: 2026-11-05T21:14:11.035Z
Reserved: 2026-05-22T18:47:27.754Z
Link: CVE-2026-48705
Updated: 2026-11-05T21:13:56.822Z
Status : Deferred
Published: 2026-11-05T21:18:50.270
Modified: 2026-11-05T22:18:44.013
Link: CVE-2026-48705
No data.