AURORALAOrg/aurora-backend

AI Summary: Implement input validation for the `getAllQuestions` API endpoint in the AURORA language learning platform's backend. This involves creating a Joi schema to define and validate allowed query parameters (type, category, subCategory, englishLevel, difficulty, page, limit), sanitizing inputs, preventing SQL injection, and adding validation middleware to the route. The goal is to enhance security and prevent unexpected behavior caused by invalid or malicious input.

AI Summary: Enhance the password validation in the AURORA backend to include complexity requirements (minimum length, uppercase, lowercase, number, special character), improve error messages, and consider a grandfather clause for existing users. This involves modifying the `auth.validators.ts` file and potentially updating the README.

AI Summary: Implement a cleanup mechanism in the AURORA backend's WalletService to remove expired verification challenges from the database. This involves adding a cleanup method to the `wallet.service.ts` and potentially the `wallet.controller.ts`, considering options like cleanup on challenge generation or a scheduled task, and potentially adding a database index on the `expiresAt` column for performance.

AI Summary: The task involves refactoring the user registration and wallet creation process in the AURORA backend to ensure atomicity. This requires wrapping both operations within a single database transaction using Prisma, adding rollback functionality to handle failures, and updating related controller and service files (auth.controller.ts, user.service.ts, wallet.service.ts) to maintain data consistency. Email sending should only occur after successful completion of both operations.

AI Summary: Remove sensitive data (like tokens and passwords) from console logs within the AURORA backend's authentication controller and middleware. Implement structured logging using the project's existing logger configuration (backend/src/core/config/logger.ts) to replace insecure logging practices. Thoroughly test changes to ensure no sensitive information is exposed.

AI Summary: Implement automatic expiration and cleanup for wallet verification challenges in the AURORA backend. This involves adding an expiration time to challenge storage, validating challenges against this expiration time, and implementing a mechanism (periodic job or on-verification cleanup) to remove expired challenges. The `WalletVerificationChallenge` model already has an `expiresAt` field that needs to be utilized.

AI Summary: Refactor the question controller in the AURORA backend to use a consistent error handling pattern. This involves replacing manual try/catch blocks with the asyncHandler wrapper, utilizing SuccessResponse and BadRequestResponse classes for consistent responses, and removing manual res.json() calls. The goal is to align the error handling with the pattern used in other controllers, ensuring all errors are managed by the global error handler while maintaining existing functionality.