AI-based Infrastructure-as-Code security focuses on identifying and mitigating security weaknesses in configuration files used to provision and manage infrastructure resources. It involves analyzing infrastructure definitions, detecting exposed sensitive information and insecure access-control settings, evaluating the severity of identified risks, and recommending appropriate configuration-level remediation. By combining AI-assisted code analysis with machine learning-based risk classification and automated security validation tools, this approach helps identify potentially unsafe configurations before deployment, prioritize remediation efforts, and verify whether corrective changes address the original security findings. The resulting assessment supports secure infrastructure provisioning, reduces configuration-related security risks, and promotes consistent application of security controls throughout the infrastructure development lifecycle.