ModelScan

ModelScan is an enterprise-grade AI model security scanning solution developed by Protect AI that detects malicious code, unsafe operations, and serialization-based threats hidden within machine learning model files. Designed for MLOps teams, AI engineers, security professionals, and enterprises, ModelScan helps secure AI supply chains by identifying potentially dangerous model artifacts before deployment into production environments.

Features of ModelScan:

• Scans machine learning model files for malicious code, unsafe functions, and serialization attacks.
• Supports popular model formats including Pickle, H5, TensorFlow SavedModel, and other AI model artifacts.
• Detects suspicious operations that could lead to credential theft, data exfiltration, model poisoning, or remote code execution.
• Provides automated model risk assessment for secure AI and MLOps workflows.
• Integrates easily into CI/CD pipelines, DevSecOps processes, and AI governance frameworks.
• Generates detailed scan results to help security teams review and validate model integrity.
• Enhances AI supply chain security by identifying threats before models are deployed.
• Supports on-premises, private cloud, and enterprise security environments.

ModelScan usage:

$ sudo su
$ cd /tmp
$ conda activate modelscan

# Verify installation:
$ which modelscan
$ pip show modelscan
$ modelscan --version
$ python -c "import modelscan; print('ModelScan OK')"

Disclaimer: ModelScan is provided under its applicable open-source licensing terms. Users are responsible for ensuring compliance with organizational security policies, software supply chain requirements, and applicable regulatory standards when scanning, distributing, or deploying machine learning models. ModelScan assists in identifying potential security risks but should be used as part of a comprehensive AI security and risk management strategy.