CVE-2026-48705

CRITICAL 9.3

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

CVSS Score

9.3

EPSS Score

0.0%

EPSS Percentile

0th

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.

CWE	CWE-20 CWE-682
Vendor	project-monai
Product	monai
Published	Nov 5, 2026
Last Updated	Nov 5, 2026

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CVSS v3 Breakdown

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:N/I:H/A:L

Attack Vector

Network

Attack Complexity

Low

Privileges Required

None

User Interaction

None

Scope

Changed

Confidentiality

None

Integrity

High

Availability

Low

Affected Versions

Project-MONAI / MONAI

< 1.6.1

References

NVD ↗ CVE.org ↗ EPSS Data ↗

github.com: https://github.com/Project-MONAI/MONAI/security/advisories/GHSA-6hp3-vr39-rqw8 github.com: https://github.com/Project-MONAI/MONAI/pull/9087 github.com: https://github.com/Project-MONAI/MONAI/commit/434c094a3e6b84cca5b6e81da51e0d18a0100607 github.com: https://github.com/Project-MONAI/MONAI/releases/tag/1.6.1