https://vulnfeed.org/Every disclosure, as it lands. Critical-only feed available.enhttps://vulnfeed.org/cve/CVE-2026-48705/https://vulnfeed.org/cve/CVE-2026-48705/Thu, 05 Nov 2026 20:44:30 +0000MONAI (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.https://vulnfeed.org/cve/CVE-2026-119578/https://vulnfeed.org/cve/CVE-2026-119578/Fri, 30 Oct 2026 14:16:47 +0000MONAI from 1.6.0 before 1.6.1 contains a remote code execution vulnerability in Auto3DSeg algo_from_json() that allows attackers to run Python code via a crafted work directory's algo_object.json. Attackers can ship a malicious algorithm_templates module plus a _target_ name that is imported and instantiated when victims call AutoRunner or import_bundle_algo_history, executing code under default configuration.