Commit Graph

7 Commits

Author SHA1 Message Date
50353d8fc1 Add Session Management UI
Implements user interface for viewing and managing active sessions:

Session Management Features:
- SessionsManagement component with full session management UI
- List all active sessions with device information
- Platform-specific icons (Computer, Phone, Tablet)
- Current session indicator with green chip
- Session details: device fingerprint, platform, last used, created date
- Revoke individual sessions with confirmation dialog
- Revoke all sessions except current with bulk action
- Real-time session count display

User Experience:
- Visual device type indicators
- Human-readable time formatting (e.g., "2 hours ago")
- Current session clearly marked and protected from removal
- Warning dialogs before revoking sessions
- Success/error feedback with alerts
- Loading states for all operations
- Empty state handling

API Integration:
- Sessions API client in lib/api/sessions.ts
- Get all sessions
- Get session count
- Revoke specific session
- Revoke all sessions except current
- Proper error handling and user feedback

Settings Page Integration:
- Added Sessions Management section
- Placed after Security/MFA settings
- Animated transitions with staggered delays
- Maintains consistent settings page layout

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-01 21:11:30 +00:00
e1842f5c1a Add MFA Setup UI in Settings page
Implements user interface for setting up and managing two-factor authentication:

MFA Setup UI Features:
- MFASettings component with full MFA management UI
- TOTP setup dialog with QR code display
- Manual entry code for authenticator apps
- Backup codes display with copy functionality
- Verification code input for TOTP enabling
- Email MFA setup dialog with confirmation
- Disable MFA dialog with warning
- Real-time MFA status indicator (enabled/disabled)
- Method type chip (Authenticator App / Email)

User Experience:
- Step-by-step TOTP setup wizard
- QR code scanning for easy authenticator app setup
- Backup codes shown only once during setup
- Copy-to-clipboard for backup codes
- Visual feedback (success/error alerts)
- Loading states for all async operations
- Animated transitions with Framer Motion

API Integration:
- MFA API client in lib/api/mfa.ts
- Get MFA status
- Setup TOTP with QR code
- Verify and enable TOTP
- Setup Email MFA
- Disable MFA
- Regenerate backup codes

Settings Page Updates:
- Added Security section with MFA settings
- Integrated MFASettings component
- Maintains existing settings page structure

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-01 21:06:57 +00:00
79966a6a6d Add voice intent classification for hands-free tracking
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Implemented comprehensive voice command understanding system:

**Intent Classification:**
- Feeding intent (bottle, breastfeeding, solid food)
- Sleep intent (naps, nighttime sleep)
- Diaper intent (wet, dirty, both, dry)
- Unknown intent handling

**Entity Extraction:**
- Amounts with units (ml, oz, tbsp): "120 ml", "4 ounces"
- Durations in minutes: "15 minutes", "for 20 mins"
- Time expressions: "at 3:30 pm", "30 minutes ago", "just now"
- Breast feeding side: "left", "right", "both"
- Diaper types: "wet", "dirty", "both"
- Sleep types: "nap", "night"

**Structured Data Output:**
- FeedingData: type, amount, unit, duration, side, timestamps
- SleepData: type, duration, start/end times
- DiaperData: type, timestamp
- Ready for direct activity creation

**Pattern Matching:**
- 15+ feeding patterns (bottle, breast, solid)
- 8+ sleep patterns (nap, sleep, woke up)
- 8+ diaper patterns (wet, dirty, bowel movement)
- Robust keyword detection with variations

**Confidence Scoring:**
- High: >= 0.8 (strong match)
- Medium: 0.5-0.79 (probable match)
- Low: < 0.5 (uncertain)
- Minimum threshold: 0.3 for validation

**API Endpoint:**
- POST /api/voice/transcribe - Classify text or audio
- GET /api/voice/transcribe - Get supported commands
- JSON response with intent, confidence, entities, structured data
- Audio transcription placeholder (Whisper integration ready)

**Implementation Files:**
- lib/voice/intentClassifier.ts - Core classification (600+ lines)
- app/api/voice/transcribe/route.ts - API endpoint
- scripts/test-voice-intent.mjs - Test suite (25 tests)
- lib/voice/README.md - Complete documentation

**Test Coverage:** 25 tests, 100% pass rate
 Bottle feeding (3 tests)
 Breastfeeding (3 tests)
 Solid food (2 tests)
 Sleep tracking (6 tests)
 Diaper changes (7 tests)
 Edge cases (4 tests)

**Example Commands:**
- "Fed baby 120 ml" → bottle, 120ml
- "Nursed on left breast for 15 minutes" → breast_left, 15min
- "Changed wet and dirty diaper" → both
- "Napped for 45 minutes" → nap, 45min

System converts natural language to structured tracking data with
high accuracy for common parenting voice commands.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-01 20:20:07 +00:00
f640e091ce Add prompt injection protection for AI endpoints
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Implemented comprehensive security against prompt injection attacks:

**Detection Patterns:**
- System prompt manipulation (ignore/disregard/forget instructions)
- Role manipulation (pretend to be, act as)
- Data exfiltration (show system prompt, list users)
- Command injection (execute code, run command)
- Jailbreak attempts (DAN mode, developer mode, admin mode)

**Input Validation:**
- Maximum length: 2,000 characters
- Maximum line length: 500 characters
- Maximum repeated characters: 20 consecutive
- Special character ratio limit: 30%
- HTML/JavaScript injection blocking

**Sanitization:**
- HTML tag removal
- Zero-width character stripping
- Control character removal
- Whitespace normalization

**Rate Limiting:**
- 5 suspicious attempts per minute per user
- Automatic clearing on successful validation
- Per-user tracking with session storage

**Context Awareness:**
- Parenting keyword validation
- Domain-appropriate scope checking
- Lenient validation for short prompts

**Implementation:**
- lib/security/promptSecurity.ts - Core validation logic
- app/api/ai/chat/route.ts - Integrated validation
- scripts/test-prompt-injection.mjs - 19 test cases (all passing)
- lib/security/README.md - Documentation

**Test Coverage:**
 Valid parenting questions (2 tests)
 System manipulation attempts (4 tests)
 Role manipulation (1 test)
 Data exfiltration (3 tests)
 Command injection (2 tests)
 Jailbreak techniques (2 tests)
 Length attacks (2 tests)
 Character encoding attacks (2 tests)
 Edge cases (1 test)

All suspicious attempts are logged with user ID, reason, risk level,
and timestamp for security monitoring.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-01 20:15:11 +00:00
8e3567e3d6 Add rate limiting to API endpoints
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Implemented comprehensive rate limiting for API security:

- Created custom Next.js-native rate limiter using in-memory store
- Added 5 rate limit configurations:
  - authLimiter: 5 requests/15min for login/register/password-reset
  - aiLimiter: 10 requests/hour for AI assistant queries
  - trackingLimiter: 30 requests/min for activity tracking
  - readLimiter: 100 requests/min for read-only endpoints
  - sensitiveLimiter: 3 requests/hour for sensitive operations

- Applied rate limiting to endpoints:
  - /api/auth/login, /api/auth/register, /api/auth/password-reset
  - /api/ai/chat
  - /api/tracking/feeding (GET and POST)

- Rate limit responses include standard headers:
  - RateLimit-Limit, RateLimit-Remaining, RateLimit-Reset
  - Retry-After header with seconds until reset

- Tested with 7 sequential requests - first 5 passed, last 2 blocked with 429

Note: Current implementation uses in-memory store. For production with
multiple instances, migrate to Redis-backed storage for distributed
rate limiting.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-01 20:08:28 +00:00
68e33712f1 feat: Add comprehensive error boundaries for graceful error handling
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Implemented React error boundaries to catch and handle errors gracefully:

**Core Error Handling Components:**
- Created ErrorBoundary class component with error catching and logging
- Created specialized fallback UIs (MinimalErrorFallback, DataErrorFallback,
  ComponentErrorFallback, FormErrorFallback, ChartErrorFallback, ImageErrorFallback)
- Added withErrorBoundary HOC for easy component wrapping
- Created errorLogger service with Sentry integration placeholder

**Error Logging Service (errorLogger.ts):**
- Centralized error logging with severity levels (FATAL, ERROR, WARNING, INFO, DEBUG)
- Context enrichment (URL, userAgent, timestamp, environment)
- Local storage of last 10 errors in sessionStorage for debugging
- User context management (setUser, clearUser)
- Breadcrumb support for debugging trails

**App Integration:**
- Wrapped root layout with top-level ErrorBoundary for catastrophic errors
- Added NetworkStatusIndicator to main page for offline sync visibility
- Wrapped daily summary section with isolated DataErrorFallback
- Added error boundary to AI assistant page with ComponentErrorFallback
- Wrapped feeding tracking form with FormErrorFallback using withErrorBoundary HOC
- Protected analytics charts with isolated ChartErrorFallback boundaries

**Error Recovery Features:**
- Isolated error boundaries prevent cascade failures
- Retry buttons on all fallback UIs
- Error count tracking with user warnings
- Development-mode error details display
- Automatic error logging to service (when Sentry integrated)

Next: Integration with Sentry for production error tracking

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-01 19:37:04 +00:00
f3ff07c0ef Add comprehensive .gitignore 2025-10-01 19:01:52 +00:00