Keras, Arbitrary Code Execution, CVE-2025-XXXX (Critical)

How the CVE Works:

The vulnerability in Keras, identified as CVE-2025-XXXX, resides in the `Model.load_model` function. This function is designed to load pre-trained machine learning models saved in the `.keras` format. Even when `safe_mode=True` is enabled, the function fails to properly sanitize the contents of the `.keras` archive. An attacker can exploit this by crafting a malicious `.keras` archive. By modifying the `config.json` file within the archive, the attacker can specify arbitrary Python modules and functions to be loaded and executed during the model loading process. This allows for arbitrary code execution on the victim’s system, potentially leading to full system compromise, data exfiltration, or further exploitation.

DailyCVE Form:

Platform: Keras
Version: All versions prior to 3.0.0
Vulnerability: Arbitrary Code Execution
Severity: Critical
Date: Mar 11, 2025

What Undercode Say:

Exploitation:

1. Crafting Malicious .keras Archive:

• Modify `config.json` to include malicious Python modules and functions.
• Example:

  {
  "class_name": "malicious_module",
  "config": {
  "module": "os",
  "function": "system",
  "args": [bash]
  }
  }
  

• Package the modified `config.json` into a `.keras` archive.

2. Triggering the Exploit:

• Use `Model.load_model` to load the malicious `.keras` archive.
• Example:

  from keras.models import load_model
  load_model('malicious_model.keras')
  

Protection:

1. Update Keras:

• Upgrade to Keras 3.0.0 or later, which includes patches for this vulnerability.
• Command:

  pip install --upgrade keras
  

2. Input Validation:

• Validate `.keras` archives before loading.
• Example:

  import zipfile
  def validate_keras_archive(file_path):
  with zipfile.ZipFile(file_path, 'r') as zip_ref:
  if 'config.json' in zip_ref.namelist():
  with zip_ref.open('config.json') as f:
  config = f.read()
  Add validation logic here
  

3. Sandboxing:

• Load models in a restricted environment to limit potential damage.
• Example using sandboxlib:

  from sandboxlib import Sandbox
  sandbox = Sandbox()
  sandbox.execute('from keras.models import load_model')
  sandbox.execute('load_model("model.keras")')
  

4. Monitoring:

• Monitor system logs for unusual activity during model loading.
• Example command:

  tail -f /var/log/syslog | grep 'python'
  

5. Code Review:

• Review custom code that interacts with `Model.load_model` for potential misuse.

Additional Commands:

• Check installed Keras version:

  pip show keras
  

• Remove vulnerable versions:

  pip uninstall keras
  

• Install specific patched version:

  pip install keras==3.0.0
  

  By following these steps, users can mitigate the risks associated with CVE-2025-XXXX and ensure their systems remain secure.

References:

Reported By: https://github.com/advisories/GHSA-5478-v2w6-c6q7
Extra Source Hub:
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