data-storage-review

Review data storage mechanisms by analyzing code, configuration files, and documentation to evaluate data persistence, retrieval, transformation, retention, and protection. This process identifies trust boundaries, traces data flows, reviews key functions, and reports structured findings.

Data flow tracing in repository analysis tracks data from input to durable storage and back out again. It identifies storage trust boundaries like databases, files, and caches to ensure data is protected effectively throughout its lifecycle.

Identify trust boundaries for data persistence by analyzing storage mechanisms such as databases, files, and caches within the codebase. This boundary identification isolates where data crosses security domains and requires protection validation.

Code review for data storage requires configuration file analysis alongside documentation and code evaluation. Analyzing configurations is necessary to accurately trace data flows, verify retention policies, and validate storage protection mechanisms.

The best way to trace data from input to durable storage is by reviewing key functions involved in the storage flow while simultaneously analyzing configuration files. This combination maps the complete data lifecycle and identifies trust boundaries.

You can analyze data retention and transformation policies in a repository by reviewing the codebase and its documentation. This analysis evaluates how data is stored, transformed, and protected throughout its lifecycle.