Bits of .NET

🐛 The Bug That Cost $500K

A simple SQL injection bug. Missed in code review. Discovered by hackers. 500K customer records leaked. Company reputation destroyed.

Could AI have caught it? Yes.

🔍 The Prompt That Saves Lives

You are a Senior Security Engineer and Code Reviewer with expertise in:
- OWASP Top 10 vulnerabilities
- Performance optimization
- Code maintainability
- Design patterns

Review this code for:

1. SECURITY ISSUES (Priority 1)
   - SQL injection
   - XSS vulnerabilities
   - Authentication bypasses
   - Sensitive data exposure
   - CSRF vulnerabilities

2. PERFORMANCE ISSUES (Priority 2)
   - N+1 queries
   - Memory leaks
   - Inefficient algorithms
   - Resource exhaustion

3. CODE QUALITY (Priority 3)
   - Naming conventions
   - Error handling
   - Code duplication
   - Maintainability issues

For each issue found:
- Severity: CRITICAL | HIGH | MEDIUM | LOW
- Location: Line numbers
- Explanation: Why it's a problem
- Fix: Exact code to replace with
- Prevention: How to avoid in future

[CODE TO REVIEW]
```python
def get_user_data(user_id):
    query = f"SELECT * FROM users WHERE id = {user_id}"
    return db.execute(query)
```
                

📊 37 Bugs Caught (Real Project)

💰 ROI Analysis

✅ What AI Catches That Humans Miss

• Subtle SQL injection through string interpolation
• Race conditions in concurrent code
• Memory leaks from unclosed resources
• Regex DoS vulnerabilities
• Integer overflow in calculations
• CSRF on state-changing endpoints
• Insecure randomness in security contexts

AI code review is a second pair of eyes, not a replacement for human reviewers. It catches technical issues amazingly well but misses:

• Business logic errors (“Is this the right feature?”)
• UX problems (“This will confuse users”)
• Architecture decisions (“Should this even be here?”)

Use AI to catch bugs. Use humans to catch bad decisions.