Skip to main content

Deserialization of Untrusted Data

CVE-2025-58756

High
8.8/10

Summary

MONAI (Medical Open Network for AI) is an AI toolkit for health care imaging. In versions through 1.5.0, insecure loading methods exists in "CheckpointLoader" module 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.

  • LOW
  • NETWORK
  • HIGH
  • UNCHANGED
  • NONE
  • LOW
  • HIGH
  • HIGH

CWE-502 - Deserialization of Untrusted Data

Deserialization of untrusted data vulnerabilities enable an attacker to replace or manipulate a serialized object, replacing it with malicious data. When the object is deserialized at the victim's end the malicious data is able to compromise the victim’s system. The exploit can be devastating, its impact may range from privilege escalation, broken access control, or denial of service attacks to allowing unauthorized access to the application's internal code and logic which can compromise the entire system.

References

Advisory Timeline

  • Published