Report Structure
A KafkaCode report consists of three main sections:1
Scan Summary
High-level overview of the scan results
2
Issue Listings
Detailed findings grouped by severity
3
Recommendations
Actionable advice for each issue
Understanding the Scan Summary
Key Metrics Explained
Privacy Grade Interpretation
🟢 A+ / A / A-
Excellent✅ Production-ready
- Minimal to no issues
- Safe to deploy
- Maintain current practices
🔵 B+ / B / B-
Good⚠️ Minor improvements needed
- Generally safe
- Address issues when convenient
- Review before major releases
🟡 C+ / C / C-
Moderate⚠️ Action required
- Notable privacy concerns
- Fix before production
- Not recommended for deployment
🔴 D / F
Critical❌ Must fix immediately
- Security vulnerabilities
- Block all deployments
- Emergency response needed
Reading Issue Listings
Issues are organized by severity level:Critical Issues 🔴
- Severity: Critical (100 points)
- File:
src/config.js - Line: 12
- Issue: Hardcoded AWS access key
- Code: Actual problematic code shown
- Action: Move to environment variables immediately
- Exposed credentials can be exploited
- Direct access to cloud resources
- Potential for data breaches
- Compliance violations
High Severity Issues 🟠
- Severity: High (50 points)
- Issue: Hardcoded API key (Stripe, GitHub, etc.)
- Risk: Potential unauthorized access
- Priority: Fix before next release
Medium Severity Issues 🟡
- Severity: Medium (10 points each)
- Issue: PII or configuration data in code
- Risk: Privacy compliance concerns
- Priority: Address when convenient
Low Severity Issues 🔵
- Severity: Low (1 point)
- Issue: Minor configuration concerns
- Risk: Minimal
- Priority: Optional cleanup
Common Issue Types
1. Hardcoded Secrets
- Problem
- Solution
- Prevention
2. PII in Code
- Problem
- Solution
- Compliance
3. Connection Strings
- Problem
- Solution
- Security
4. High Entropy Strings
- String has high randomness (entropy > 4.5)
- Likely a generated secret or token
- May be a legitimate random value
- Is it a secret? → Move to env var or vault
- Is it a hash? → OK to keep if public
- Is it a test fixture? → Add comment explaining
Action Priority Matrix
False Positives
Sometimes KafkaCode may flag non-issues:Example 1: Test Data
Example 2: Public Information
Example 3: Placeholder Values
- Review the context
- Determine if it’s a real issue
- If false positive, add a comment
- Consider refactoring for clarity
Report Examples
Clean Project (A+)
Minor Issues (A-)
Moderate Concerns (C)
Critical Problems (F)
Next Steps
CI/CD Integration
Automate scanning in your pipeline
Privacy Grading
Deep dive into the grading system
Detection Methods
Understand what’s being detected
Examples
See real-world examples

