Developed a security-focused notebook scanning solution for the Red-Hat-AI-Innovation-Team/sdg_hub repository, enabling automated vulnerability detection within Jupyter Notebooks. Leveraging Python scripting and Snyk integration, the solution performs dependency and code vulnerability checks, generating detailed reports to guide remediation. The implementation included robust Python path resolution, reliable notebook discovery, and safe PATH handling to ensure cross-platform compatibility. By scanning only git-tracked notebooks and respecting .gitignore, the script reduces false positives and noise. This work accelerated security feedback for developers, reduced risk in notebook-driven workflows, and established a reusable, scalable approach to notebook security analysis across collaborative data science environments.