MONAI (Medical Open Network for AI) is an AI toolkit for health care imaging.
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.
Read at NIST National Vulnerability Database (CVE API 2.0)
- Vendor
- Project-MONAI
- Product
- MONAI
- CVSS v3.1
- 9.3 AV:N/AC:L/PR:N/UI:N/S:C/C:N/I:H/A:L
- Exploitation
- SSVC poc, automatable yes, impact partial
- Fix
- available
- Weakness
- CWE-20, CWE-682
- Exposure class
- OT / ICS
- NVD status
- Deferred
Why it ranks 59 (High)
- Public exploit code reported
- CVSS v3.1 9.3 critical
- SSVC: automatable
- Product class: OT / ICS
- Fix available
- Recency: items published within 24 hours gain 15, within 72 hours 6, within 7 days 2.
Links
- NIST National Vulnerability Database (CVE API 2.0) (nvd.nist.gov)
- CVE-2026-48705 on this site · NVD · CVE.org · Vulnpedia