CVE-2026-48705

What it is

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.

At a glance

Exploitability

Can be exploited over the network without logging in. High risk of data tampering.

Fix

A patch, advisory or fixed version is referenced. Upgrade or apply it.

Timeline

1. 2026-05-22 18:47 UTC ReservedThe CVE id was reserved by its CNA
2. 2026-11-05 21:18 UTC PublishedDisclosed publicly on CVE.org and NVD
3. 2026-11-05 22:18 UTC Last updatedMost recent change to the record

Details

Published

2026-11-05 21:18 UTC

Last modified

2026-11-05 22:18 UTC

Weakness

CWE-20 · Improper input validation

Record status

Deferred

Attack profile CVSS 3.1 · 9.3

Attack vector

Network

Complexity

Low

Privileges needed

None

User interaction

None

Scope

Changed

Confidentiality

None

Integrity

High

Availability

Low