The increasing reliance of financial institutions on cloud infrastructures has amplified concerns surrounding regulatory compliance and cybersecurity, particularly in light of the EU’s Digital Operational Resilience Act (DORA). This paper presents an experimental, empirical model designed to assess security misconfigurations in Amazon Web Services (AWS) and evaluate their alignment with DORA compliance requirements. Leveraging a Python-based scanning script built with the AWS Boto3 SDK, the study programmatically inspects critical AWS services—S3, Elastic Compute Cloud (EC2), Identity and Access Management (IAM), and Virtual Private Cloud (VPC) —within a controlled environment configured with known vulnerabilities. Each misconfiguration is automatically mapped to relevant DORA articles (Articles 5, 9, and 10), and accompanied by actionable remediation strategies. The results, visualized through a Streamlit dashboard and exportable PDF reports, demonstrate the tool’s ability to detect compliance gaps in real-time. Unlike previous work based on theoretical models or manual audits, this research offers a replicable, data-driven approach that bridges the gap between technical vulnerabilities and regulatory mandates. By doing so, it empowers financial institutions to strengthen their operational resilience and proactively align with emerging regulatory standards in dynamic cloud ecosystems.