Quality Metrics for Cybersecurity Testing: Defining Benchmarks for Secure Code

Abstract

Software security cannot be ensured by merely a few ad hoc vulnerability scans; it needs to be measured systematically with clearly defined quality measures. This study describes the evolution and use of quantitative standards against cybersecurity testing, which aims to establish consistency in assessing the secure code in various settings. It looks at such important metrics as vulnerability density, the percentage of security tests passed, false positive and false negative rates, and the mean time to detect and fix vulnerability. This work offers a systematic approach to defining baseline thresholds and on-going improvement practices, by mapping such metrics against industry standards and frameworks including OWASP, NIST and ISO/IEC. The issues raised during the study include the trade-off between the speed of development and security, context-specific requirements, and optimization of metrics because of the changes in the landscape of threats. Results indicate that the implementation of regular data-driven quality indicators helps organizations to increase software resilience, decrease security debt, and create a more proactive cybersecurity stance.