ModelAudit vs ModelScan: Comparing ML Model Security Scanners

As organizations prioritize the security of machine learning models, two tools, Promptfoo's ModelAudit and Protect AI's ModelScan, have emerged to assist with identifying vulnerabilities. A comparison of these tools was conducted using 11 test files with known security issues, revealing significant differences in format support and detection capabilities. ModelAudit analyzed all 11 files, identifying 16 security issues, while ModelScan focused on pickle-based formats, detecting only 3 issues across 6 files. ModelAudit demonstrated broader format coverage, including configuration files and ONNX models, and provided more detailed vulnerability detection and risk scoring. In contrast, ModelScan excelled in pickle security scanning with a lightweight implementation suitable for environments using pickle-based models. Both tools offer command-line interfaces and JSON outputs for automation, but ModelAudit also includes a UI and additional security insights. Organizations are encouraged to evaluate their specific needs and possibly use both tools complementarily to address diverse ML framework requirements and security considerations.