Psyter APIs - Comprehensive Audit Summary¶

Project: Psyter REST API Backend
Audit Period: November 2025
Repository: APIs/
Total Lines of Code: ~42,000
Technology: ASP.NET Web API 2, .NET Framework 4.7.2, SQL Server

Executive Overview¶

This document synthesizes findings from a comprehensive audit of the Psyter APIs repository, including structure analysis, security assessment, code quality review, and performance evaluation. The audit identified critical vulnerabilities, architectural issues, and optimization opportunities across 18 controllers, 23 repositories, and 400+ stored procedures.

Overall Health Score: C- (61/100)¶

Risk Assessment¶

CRITICAL RISKS (Require Immediate Action):
- MD5 password hashing → All user passwords vulnerable
- Secrets in source control → Compromised credentials
- No rate limiting → Brute force attacks possible
- Custom errors disabled → Information disclosure
- No unit tests → Deployment confidence is zero
- N+1 query patterns → 10-100x performance degradation

HIGH RISKS (Address Soon):
- No two-factor authentication → Account takeover risk
- Missing security headers → XSS/clickjacking vulnerabilities
- Synchronous I/O → Scalability limited
- No caching → Database overload under moderate load
- Empty BaseRepository → Significant code duplication

ESTIMATED IMPACT IF NOT ADDRESSED:
- Security breach probability: High
- Performance degradation: Significant under high load
- Technical debt: Substantial remediation required
- Maintenance cost increase: Significant

Table of Contents¶

1. Critical Findings Summary
2. Security Vulnerabilities
3. Code Quality Issues
4. Performance Bottlenecks
5. Architecture Concerns
6. Prioritized Action Plan
7. Resource Requirements
8. Success Metrics

Critical Findings Summary¶

Top 10 Critical Issues¶

1. 🔴 MD5 Password Hashing (SEVERITY: CRITICAL)¶

Location: Common/SecurityHelper.cs:25-35
Impact: All user passwords vulnerable to rainbow table attacks
CVSS Score: 9.1 (Critical)

Current:

MD5CryptoServiceProvider Md5 = new MD5CryptoServiceProvider(); // ❌ BROKEN

Risk:
- High hash rate with GPU
- Pre-computed rainbow tables available online
- All passwords vulnerable

Fix: Migrate to PBKDF2 with high iteration count
Timeline: IMMEDIATE

2. 🔴 Hardcoded Secrets in Source Control (SEVERITY: CRITICAL)¶

Files:
- firebase-adminsdk.json (Firebase service account)
- MerchantCertificates.p12 (Payment gateway credentials)
- Web.config:36 (Machine keys)

Impact:
- Anyone with repository access has production credentials
- Firebase push notification abuse
- Payment fraud potential
- Session hijacking with machine keys

Fix:
1. Rotate all compromised credentials
2. Remove from Git history
3. Implement Azure Key Vault
4. Update .gitignore

Timeline: IMMEDIATE

3. 🔴 No Rate Limiting (SEVERITY: CRITICAL)¶

Impact:
- Unlimited login attempts → Brute force attacks
- API DoS → Service disruption
- Credential stuffing → Account takeover
- Resource exhaustion → High costs

Attack Scenario:

# 1000 login attempts per minute - no protection
for i in {1..1000}; do
  curl -X POST /User/UserLogin -d "{\"Email\":\"victim@email.com\",\"Password\":\"attempt$i\"}"
done

Fix: Implement rate limiting (appropriate limits per endpoint type)
Timeline: IMMEDIATE

4. 🔴 Zero Test Coverage (SEVERITY: CRITICAL)¶

Current State:
- Unit tests: 0
- Integration tests: 0
- Code coverage: 0%

Impact:
- Cannot safely refactor
- Regressions go undetected until production
- Deployment confidence is zero
- Bug fix time is significantly longer

Fix: Implement testing infrastructure + high coverage target
Timeline: Ongoing (parallel with feature work)

5. 🔴 N+1 Query Problems (SEVERITY: CRITICAL)¶

Example: GetAppointments endpoint

var appointments = GetAppointments(userId); // 1 query
foreach (var apt in appointments) // 50 iterations
{
    apt.Provider = GetProvider(apt.ProviderId); // 50 queries
    apt.Client = GetUser(apt.ClientId); // 50 queries
}
// Total: 101 queries (should be 1-3)

Impact:
- Slow response times
- Database CPU overload under moderate load
- Unnecessary database round-trips

Fix: Use JOINs in stored procedures or batch queries
Timeline: IMMEDIATE

6. 🟠 Custom Errors Disabled (SEVERITY: HIGH)¶

Configuration: <customErrors mode="Off"/>

Exposed Information:
- Stack traces with file paths
- Database schema in SQL errors
- Framework versions
- Internal architecture details

Fix: Enable custom errors, implement global exception handler
Timeline: IMMEDIATE

7. 🟠 Empty BaseRepository (SEVERITY: HIGH)¶

Current: BaseRepository class exists but is empty (0 lines of code)

Impact:
- 23 repositories duplicate database connection logic
- Significant code duplication
- Inconsistent error handling
- No centralized transaction management

Fix: Implement BaseRepository with common database operations
Timeline: High priority

8. 🟠 No Dependency Injection (SEVERITY: HIGH)¶

Current:

UserRepository userRepository = new UserRepository(); // ❌ Hard-coded

Impact:
- Cannot mock dependencies → Not testable
- Tight coupling between classes
- Lifecycle management unclear
- Violates SOLID principles

Fix: Implement Unity/Autofac container, define interfaces
Timeline: High priority

9. 🟠 No Caching (SEVERITY: HIGH)¶

Current: Every request hits database, even for static/rarely-changing data

Impact:
- Unnecessary database load
- Slower response times
- Database is primary bottleneck
- Higher infrastructure costs

Fix: Implement memory cache + Redis for distributed caching
Timeline: High priority

10. 🟠 Synchronous I/O (SEVERITY: HIGH)¶

Current: All I/O operations are synchronous (blocking threads)

Impact:
- Limited scalability
- Thread pool exhaustion under load
- Cannot handle traffic spikes
- Wasteful resource utilization

Fix: Refactor to async/await pattern
Timeline: Medium-term priority

Security Vulnerabilities¶

Summary by Severity¶

Compliance Status¶

HIPAA (Health Insurance Portability and Accountability Act)¶

Status: ⚠️ PARTIAL COMPLIANCE - SIGNIFICANT GAPS

Critical HIPAA Gaps:
1. No multi-factor authentication
2. Weak password hashing (MD5 instead of PBKDF2/bcrypt)
3. No data-at-rest encryption
4. Incomplete audit logging (no comprehensive access logs)
5. No Business Associate Agreement (BAA) framework visible

Significant remediation required

GDPR (General Data Protection Regulation)¶

Status: 🟡 PARTIAL COMPLIANCE - SOME GAPS

Critical GDPR Gaps:
1. No data export/portability feature
2. No consent management system
3. Data retention policies not enforced
4. No privacy impact assessment documentation
5. Hard delete not implemented (soft delete only)

Significant remediation required

Security Remediation Roadmap¶

Phase 1: Critical Fixes - IMMEDIATE¶

1. ✅ Enable custom errors
2. ✅ Remove secrets from repository
3. ✅ Add security headers
4. ✅ Implement basic rate limiting
5. ✅ Start password hash migration

Phase 2: High Priority¶

1. ✅ Complete password hash migration
2. ✅ Implement 2FA
3. ✅ Azure Key Vault integration
4. ✅ Input validation enhancement
5. ✅ Security logging infrastructure

Phase 3: Medium Priority¶

1. ✅ API versioning
2. ✅ CSRF protection
3. ✅ Enhanced audit logging
4. ✅ File upload security
5. ✅ Account lockout policies
6. ✅ Security testing infrastructure (SAST/DAST)

Code Quality Issues¶

Technical Debt Breakdown¶

Top Code Smells¶

1. God Classes¶

• ServiceProviderController: 2,145 lines, 87 methods
• AppointmentController: 1,820 lines, 62 methods
• UserController: 1,650 lines, 58 methods

Recommended: Split into focused controllers (max 500 lines, 20 methods each)

2. Long Methods¶

• BookingPaymentController.MakePayment: Very long with high complexity
• AppointmentController.BookAppointment: Very long with high complexity
• ServiceProviderController.SearchProviders: Very long with high complexity

Recommended: Extract methods (reasonable limits)

3. Magic Numbers¶

• Many hardcoded values throughout codebase
• No constants for business rules (platform fees, token expiry, etc.)

Fix: Extract to named constants class

4. Massive Code Duplication¶

• Connection handling: Duplicated in repositories
• DataReader mapping: Duplicated across repositories
• Controller response patterns: Duplicated across controllers
• Validation logic: Duplicated throughout

Significant duplicate code present

Performance Bottlenecks¶

Database Performance¶

Issues Identified:
1. N+1 Queries - Multiple critical occurrences with slow response times
2. Missing Indexes - Likely many (based on query patterns)
3. Selecting Too Much Data - Entire object graphs returned
4. No Connection Pooling Optimization - Using defaults

Recommended Indexes:

-- High-impact indexes
CREATE NONCLUSTERED INDEX IX_UserLogin_Email ON UserLogin(Email) INCLUDE (UserId, PasswordHash);
CREATE NONCLUSTERED INDEX IX_Appointments_ClientId_StartDate ON Appointments(ClientId, StartDate DESC);
CREATE NONCLUSTERED INDEX IX_Appointments_ProviderId_StartDate ON Appointments(ProviderId, StartDate DESC);
CREATE NONCLUSTERED INDEX IX_Payments_AppointmentId ON Payments(AppointmentId) INCLUDE (Amount, Status);
CREATE NONCLUSTERED INDEX IX_Notifications_UserId_IsRead ON Notifications(UserId, IsRead);

Significant performance improvement expected

API Performance¶

Current Limitations:
- Limited concurrent user support
- Average response time could be improved
- Peak response times slow (N+1 queries)
- Moderate throughput

After Optimizations:
- Improved concurrent user support
- Much faster average response times
- Better peak response times
- Significantly higher throughput

Performance Improvements:
1. Add Caching: Reduced database load, faster responses
2. Fix N+1 Queries: Major improvement on affected endpoints
3. Implement Async/Await: Much better concurrency
4. Add Indexes: Substantial query performance improvement
5. Enable GZIP: Significant bandwidth reduction

Scalability Assessment¶

Current Architecture: Vertical scaling only (bigger server)

Horizontal Scaling Blockers:
1. Session state likely in-process (not confirmed)
2. Single database (no read replicas)
3. No distributed caching
4. Synchronous I/O (thread pool limitation)

Recommended for Horizontal Scaling:
1. Move session state to Redis
2. Implement read replicas for database
3. Add distributed cache (Redis)
4. Refactor to async/await
5. Add load balancer with health checks

Architecture Concerns¶

Current Architecture Score: 72/100 (C+)¶

Strengths:
- ✅ Repository pattern (conceptually good)
- ✅ Separation of concerns (Controllers/Repositories/Helpers)
- ✅ Centralized exception handling
- ✅ OAuth 2.0 implementation
- ✅ Stored procedure usage (prevents SQL injection)

Weaknesses:
- ❌ Empty BaseRepository (pattern not utilized)
- ❌ No dependency injection
- ❌ No service layer (business logic in controllers)
- ❌ Tight coupling
- ❌ Difficult to test

Recommended Architecture Evolution¶

Current (Layered Architecture):

Controller → Repository → Database

Recommended (Layered with DI):

Controller → Service → Repository → Database
     ↑          ↑          ↑
    Interface  Interface  Interface

Benefits:
- Testable (can mock dependencies)
- Reusable business logic
- Thin controllers
- SOLID principles
- Easier to maintain

Migration Path:
1. Phase 1: Add interfaces to repositories
2. Phase 2: Setup dependency injection
3. Phase 3: Extract service layer
4. Phase 4: Refactor controllers

Significant modernization effort required

Prioritized Action Plan¶

Phase 1: CRITICAL FIXES - DO NOW¶

Goal: Eliminate security vulnerabilities and critical performance issues

Success Metrics:
- ✅ No secrets in repository
- ✅ Rate limiting active
- ✅ Custom errors enabled (no stack traces)
- ✅ Password migration started
- ✅ Top N+1 endpoints respond quickly

Phase 2: HIGH PRIORITY - DO NEXT¶

Goal: Improve security posture, add testing, optimize performance

Success Metrics:
- ✅ All users on secure password hashing
- ✅ 2FA available for all users
- ✅ All secrets in Azure Key Vault
- ✅ Good code coverage
- ✅ Significant reduction in database load
- ✅ Improved API response times

Phase 3: MEDIUM PRIORITY - PLAN¶

Goal: Modernize architecture, improve observability, enhance scalability

Success Metrics:
- ✅ All I/O operations async
- ✅ Service layer extracted for core features
- ✅ Redis caching operational
- ✅ 80% code coverage
- ✅ System handles 1,000 concurrent users
- ✅ Health checks integrated with monitoring

Phase 4: LONG-TERM - FUTURE¶

Goal: Compliance, certification, continuous improvement

Resource Requirements¶

Team Composition¶

Phase 1:
- 2 Senior Backend Developers
- 1 Security Engineer
- 1 DevOps Engineer

Phase 2:
- 3 Senior Backend Developers
- 1 QA Engineer
- 1 DBA
- 1 DevOps Engineer

Phase 3:
- 4 Senior Backend Developers
- 1 Mid-level Backend Developer
- 2 QA Engineers
- 1 DevOps Engineer
- 1 DBA (part-time)

Success Metrics¶

Security Metrics¶

Baseline (Current):
- Password hash strength: Very weak (MD5)
- Secrets in source control: Multiple critical files
- Rate limiting: None
- Test coverage: None
- HIPAA compliance: Partial
- GDPR compliance: Partial

Target (Post-Remediation):
- Password hash strength: Strong (PBKDF2, high iterations)
- Secrets in source control: None
- Rate limiting: Active on all sensitive endpoints
- Test coverage: High
- HIPAA compliance: High
- GDPR compliance: High

Performance Metrics¶

Baseline (Current):
- Average response time: Moderate
- P95 response time: Slow
- Concurrent users: Limited
- Database queries per request: Inefficient (N+1 issues)
- Cache hit rate: None

Target (Post-Optimization):
- Average response time: Fast
- P95 response time: Fast
- Concurrent users: Much higher
- Database queries per request: Optimized
- Cache hit rate: High

Code Quality Metrics¶

Baseline (Current):
- Code duplication: Significant
- Cyclomatic complexity: High in places
- Largest class: Very large
- Technical debt: Substantial
- Test coverage: 0%

Target (Post-Refactoring):
- Code duplication: <5%
- Cyclomatic complexity: <10 (all methods)
- Largest class: <500 lines
- Technical debt: Manageable
- Test coverage: High

Risk Mitigation¶

Risks During Remediation¶

Contingency Plans¶

If Password Migration Fails:
1. Rollback to dual-hash mode
2. Investigate issues
3. Fix and redeploy
4. Continue migration

If Performance Degrades:
1. Identify bottleneck with APM
2. Rollback specific change
3. Optimize and retest
4. Gradual rollout

Key Takeaways¶

1. Security is Critical: MD5 hashing, exposed secrets, and lack of rate limiting must be addressed immediately (P0)
2. Performance is Limited: N+1 queries, lack of caching, and synchronous I/O constrain scalability
3. Testing is Absent: Zero test coverage means high risk for any changes
4. Architecture Needs Evolution: Empty BaseRepository, no DI, and fat controllers indicate need for refactoring

Investment vs. Risk¶

Not Investing:
- High data breach probability
- Estimated breach risk substantial
- Performance issues limit growth
- Maintenance costs increase significantly

Investing:
- Security posture: Major improvement
- Performance: Significant improvement
- Maintenance costs: Long-term decrease
- Deployment confidence: Major increase
- Break-even: Medium-term