CVE-2026-100841

Published: Set 27, 2026 Last Modified: Set 28, 2026
ExploitDB:
Other exploit source:
Google Dorks:
HIGH 8,5
Attack Vector: local
Attack Complexity: low
Privileges Required: low
User Interaction: none
Confidentiality: N/A
Integrity: N/A
Availability: N/A
HIGH 7,8
Attack Vector: local
Attack Complexity: low
Privileges Required: low
User Interaction: none
Scope: unchanged
Confidentiality: high
Integrity: high
Availability: high

Description

AI Translation Available

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.

502

Deserialization of Untrusted Data

Draft
Common Consequences
Security Scopes Affected:
Integrity Availability Other
Potential Impacts:
Modify Application Data Unexpected State Dos: Resource Consumption (Cpu) Varies By Context
Applicable Platforms
Languages: Java, Ruby, PHP, Python, JavaScript
Technologies: Not Technology-Specific, ICS/OT, AI/ML
View CWE Details
https://github.com/Project-MONAI/MONAI/security/advisories/GHSA-636w-j999-g7x5
https://www.vulncheck.com/advisories/monai-1.6.0-persistentdataset-remote-code-…