code-review

To find security issues and bugs in a pull request before merging, you can run an automated code review using six audit lenses including security, multi-tenant data leaks, and race conditions. This process analyzes PR diffs across multiple languages to generate a prioritized issue report for developers to fix.

Multi-tenant data leak detection in code review is an audit lens that identifies cross-tenant data exposure vulnerabilities in backend code changes. It operates by scanning diffs and pull requests to ensure tenant boundaries are strictly enforced before merging.

To check API and frontend boundary issues in code diffs, apply the API frontend boundary audit lens during your code review. This mechanism evaluates commits across multiple languages and frameworks to catch contract mismatches and state machine violations before generating a structured report.

Automated code review does work for race conditions and money precision errors by applying dedicated audit lenses to the changed files. It scans pull requests and commits to detect these specific anti-patterns, providing a standardized score and detailed report to prevent flawed merges.

The best way to audit code changes for anti-patterns across multiple frameworks is to use a structured multi-lens code review approach. By enforcing automated grep recipes and six audit lenses on PRs and diffs, you get a comprehensive risk assessment and prioritized issue report.

Yes, you can use automated code review for both backend and frontend commits. The review workflow applies its six audit lenses to diffs across multiple languages and frameworks, outputting a standardized scoring system and detailed issue report for any code changes.