DeepKeep Model Scanning is a security solution that inspects AI models before deployment to identify threats and vulnerabilities. The platform performs both static and dynamic analysis of models to detect security issues that traditional tools cannot catch. The solution examines model files, weights, and runtime behavior to identify embedded malware, vulnerabilities in model dependencies, signs of tampering, and unexpected behavior triggered by edge-case inputs. Static analysis provides structural insights into the model composition, while dynamic testing evaluates the model against known threat patterns to understand behavioral characteristics. The platform supports scanning of open-source models, fine-tuned foundation models, and custom-built models. It aims to prevent security risks from entering the production stack by identifying threats early in the development lifecycle. DeepKeep Model Scanning uses multi-engine static analysis combined with dynamic testing to provide comprehensive security assessment of AI model assets. The solution surfaces security gaps specific to AI models that cannot be detected through conventional security scanning approaches.