Answer in brief
CVE-2026-48705 records a Critical severity (CVSS 9.3) vulnerability in MONAI: MONAILabel Server Crash and Silent Inference Corruption via Crafted DICOM (pydicom DS/IS Validation Bypass). The current sources do not mark it as known exploited. The current feed maps Project-MONAI/MONAI (generic), monai (pip), monai (pypi). Check affected ranges and fixed versions before updating.
Analysis pending evidence review
HOL Guard separates source facts from reviewed analysis. See the methodology.
CVSS is 9.3. The current sources do not mark it as known exploited. Treat this as a source-backed prioritization signal, not a statement about your environment.
Analysis status
Analysis pending evidence review
Factual feed record only; HOL analysis is not approved for indexing. Read the methodology.
The current feed maps Project-MONAI/MONAI (generic), monai (pip), monai (pypi). Check affected ranges and fixed versions before updating.
| Package | Affected range | Fixed version |
|---|---|---|
| Project-MONAI/MONAIgeneric | <1.6.1 | 1.6.1 |
| monaipip | <1.6.1 | 1.6.1 |
| monaipypi | >=0 <1.6.1 | 1.6.1 |
Published upstream
Nov 5, 2026
Evidence: source:cvelist:source_dates:source-dates:recordSource modified
Nov 5, 2026
Evidence: source:cvelist:source_dates:source-dates:recordFirst seen by HOL
Oct 27, 2026
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.
Quoted source text, attributed separately from HOL analysis.