CVE intelligence and bounded remediation

CVE-2025-58756 — MONAI (Medical Open Network for AI) is an AI toolkit for health care imaging

High CVSS 8.8

MONAI (Medical Open Network for AI) is an AI toolkit for health care imaging. In versions up to and including 1.5.0, in `model_dict = torch.load(full_path, map_location=torch.device(device), weights_only=True)` in monai/bundle/scripts.py , `weights_only=True` is loaded securely. However, insecure loading methods still exist elsewhere in the project, such as when loading checkpoints. This is a common practice when users want to reduce training time and costs by loading pre-trained models downloaded from other platforms. Loading a checkpoint containing malicious content can trigger a deserialization vulnerability, leading to code execution. As of time of publication, no known fixed versions are available.

Severity
High
CVSS
8.8 (3.1)
Published
2025-09-09
CISA KEV
Not currently listed
Ecosystem
software/application
Weaknesses
CWE-502

Affected products

  • monai / medical_open_network_for_ai

Matched remediation archetype

Unsafe deserialization and object reconstruction

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Check exposure

  • Inventory serialization formats accepted from requests, queues, caches, files, cookies, and cross-service messages.
  • Trace whether untrusted input can select classes, types, callbacks, constructors, or object hooks during decoding.
  • Identify signing, schema validation, trust-boundary, and compatibility settings for each decoder.

Remediate safely

  • Replace native object deserialization with a data-only format and explicit schema validation.
  • If replacement is not immediate, use a safe decoder with a minimal type allowlist and disable polymorphic or executable hooks.
  • Update the affected library and add inert tests for unknown types, extra fields, malformed nesting, and unsigned data.

Authoritative sources

Complete CVE record and remediation plan

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