CVE Catalog

CVE-2026-100841

HighCVSS 7.8
Published: Updated: Translated: NVD NIST

Exploitation Probability (EPSS)

Low risk
0.13%

2th percentile - higher than 2% of all known CVEs

Summary

In MONAI 1.6.0, PersistentDataset explicitly rejects the combination track_meta=True with weights_only=True, forcing users who cache MetaTensors to run torch.load(hashfile, weights_only=False). Related cache helpers also call pickle.loads on cached content and use hashlib.md5 for cache keys. A local user with write access to a shared cache directory can place a malicious pickle file that is deserialized the next time another user's MONAI pipeline reads the cache, resulting in arbitrary code execution in that user's context.

Risk Assessment

A local attacker can execute arbitrary code in another user's context, potentially leading to data theft or privilege escalation.

Recommendation

Update MONAI to a patched version when available. Restrict permissions on cache directories and use secure permissions.

Other vulnerabilities in MONAI

See all
Original NVD description (English source)

In 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, weights_only=False). Related cache helpers in monai/data/utils.py also call pickle.loads on cached content and derive cache keys with hashlib.md5. As a result, a local user with write access to a shared or world-writable cache_dir (e.g. /tmp/monai_cache, HPC scratch, ~/.cache/monai) can place a malicious pickle file that is deserialized the next time another user's MONAI pipeline reads the cache, resulting in arbitrary code execution in that user's context. All released versions of the monai pip package are affected; no patched version is available as of the advisory.

Vulnerability data from NVD (NIST) · CISA KEV · EPSS