This objective focuses on enhancing code security by monitoring several crucial metrics. The first metric, Vulnerability Density, identifies areas in the codebase with higher vulnerability risk, directing efforts to where they are most needed. For instance, a low vulnerability density suggests robust, secure coding practices are in place.
Mean Time to Resolve Vulnerabilities (MTTR) measures the efficiency of addressing identified vulnerabilities. A lower MTTR indicates a responsive security protocol. For example, reducing the MTTR to less than 30 days means faster protection against potential exploits.
The Percentage of Code Covered by Security Testing ensures thorough testing of the codebase, aiming for 90% or higher coverage. This high percentage minimizes the risk of undetected vulnerabilities. Additionally, a Zero Incident benchmark for the Number of Security Incidents aims to prevent breaches entirely, ensuring robust preventive measures.
Lastly, keeping the False Positive Rate of Security Tools below 5% helps avoid unnecessary distractions and ensures that resources are used efficiently, concentrating effort on genuine threats.
Top 5 metrics for Code Security
1. Vulnerability Density
Measures the number of vulnerabilities per thousand lines of code. It helps to identify vulnerable areas in the codebase that need attention.
What good looks like for this metric: 0-1 vulnerabilities per KLOC
How to improve this metric:- Conduct regular code reviews
- Use static analysis tools
- Implement secure coding practices
- Provide security training for developers
- Perform security-focused testing
2. Mean Time to Resolve Vulnerabilities (MTTR)
The average time it takes to resolve vulnerabilities from the time they are identified.
What good looks like for this metric: Less than 30 days
How to improve this metric:- Prioritise vulnerabilities based on severity
- Automate vulnerability management processes
- Allocate dedicated resources for vulnerability remediation
- Establish a clear vulnerability response process
- Regularly monitor and report on MTTR
3. Percentage of Code Covered by Security Testing
The proportion of the codebase that is covered by security tests, helping to ensure code is thoroughly tested for vulnerabilities.
What good looks like for this metric: 90% or higher
How to improve this metric:- Increase the frequency of security tests
- Use automated security testing tools
- Integrate security tests into the CI/CD pipeline
- Regularly update and expand test cases
- Provide training on writing effective security tests
4. Number of Security Incidents
The total count of security incidents, including breaches, detected within a given period.
What good looks like for this metric: Zero incidents
How to improve this metric:- Implement continuous monitoring
- Conduct regular penetration testing
- Deploy intrusion detection systems
- Educate employees on security best practices
- Establish a strong incident response plan
5. False Positive Rate of Security Tools
The percentage of security alerts that are not true threats, which can lead to resource wastage and alert fatigue.
What good looks like for this metric: Less than 5%
How to improve this metric:- Regularly update security tool configurations
- Train security teams to properly interpret alerts
- Use machine learning to improve tool accuracy
- Combine multiple security tools for better context
- Implement regular reviews of alerts to refine rules
How to track Code Security metrics
It's one thing to have a plan, it's another to stick to it. We hope that the examples above will help you get started with your own strategy, but we also know that it's easy to get lost in the day-to-day effort.
That's why we built Tability: to help you track your progress, keep your team aligned, and make sure you're always moving in the right direction.
Give it a try and see how it can help you bring accountability to your metrics.
