CVE-2026-100843High· 7.8▾ TwilightMONAI versions before 1.6.0 contain a remote code execution vulnerability in the algo_from_pickle() function due to unsafe pickle.loads() deserialization in monai/auto3dseg/utils.py. Attackers can craft malicious pickle files that execut…
▾ Twilight zone — High severity, or a signal on a lesser flaw
impact 42.9 · likelihood 0 · exploitation 0
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MONAI versions before 1.6.0 contain a remote code execution vulnerability in the algo_from_pickle() function due to unsafe pickle.loads() deserialization in monai/auto3dseg/utils.py. Attackers can craft malicious pickle files that execute arbitrary system commands when deserialized by the vulnerable function.
Refer to the linked advisories for vendor-supplied fixes and affected version ranges.
Connected by shared product, vendor, weakness, or advisory.
GHSA-qxq5-qhx6-94qwHigh· 7.8Incomplete Fix in MONAI: algo_from_pickle() pickle.loads() RCE still present in v1.5.2 despite GHSA-89gg-p5r5-q6r4 claiming patch
CVE-2026-100846High· 7.6MONAI before 1.5.2 contains a deserialization of untrusted data vulnerability in the algo_from_pickle function in monai/auto3dseg/utils.py
CVE-2026-100845High· 7.8MONAI before 1.6.0 contains an unsafe deserialization vulnerability in the NumpyReader class that unconditionally uses numpy.load with allow_pickle=True when loading .npy and .npz files
CVE-2026-100841High· 7.8In MONAI 1.6.0, PersistentDataset (monai/data/dataset.py) explicitly rejects the combination track_meta=True with weights_only=True, forcing users who cache MetaTensors (the default tensor type in MONAI >= 1.0) to run torch.load(hashfile…
GHSA-wg9g-w2j2-8pgrHigh· 7.8MONAI: Unsafe deserialization in NumpyReader allows arbitrary code execution via malicious .npy files
CVE-2026-100844High· 8.4MONAI before 1.6.0 is vulnerable to OS command injection in the nnUNetV2Runner component (monai.apps.nnunet.nnunetv2_runner)