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CVE-2026-48705

MONAI: MONAILabel Server Crash and Silent Inference Corruption via Crafted DICOM (pydicom DS/IS Validation Bypass)

Critical9.3
Published
Updated
Reserved
Assigned by
GitHub_M

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.

Scores

CVSS scores of CVE-2026-48705, by who scored it
Scored byCVSSScoreVector
GitHub_MCNA (assigner)3.1Critical9.3CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:N/I:H/A:L
NVDNVD · Deferred3.1Critical9.3CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:N/I:H/A:L
EPSS (exploitation in 30 days)
Not scored
CISA SSVC
Exploitation: poc · Automatable: yes · Technical impact: partial

The list uses the assigner's score when there is one, then CISA's, then NVD's: Critical 9.3.

Weakness

Affected products

Affected packages

From reviewed advisories of the GitHub Advisory Database.

References (4)

Sources

The same CVE in the primary databases and aggregators, to check against.

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Record last updated .