Detection as code: Revolutionizing security operations through automated, intelligent threat detection

by Bill Brenner

In an era of increasingly sophisticated cyber threats, security teams are seeking more intelligent and agile approaches to threat detection. Detection as code represents a transformative strategy that applies software development principles to security monitoring, enabling organizations to create more robust, flexible, and precise detection mechanisms.

Gary Harrison, Staff Detection Engineer at Fastly, and his colleagues, Marcus Young, Senior Security Engineer (Detection Engineering), and Simran Khalsa, Staff Security Researcher, unpacked what detection as code entails in a May 21 SC webcast hosted by Adrian Sanabria, Host of Enterprise Security Weekly.

The challenge of traditional detection methods

Traditional security detection approaches often rely on out-of-the-box rules that quickly become outdated or irrelevant. Young emphasized that these pre-configured rules frequently fail to address an organization’s unique technological landscape. The key is not to simply implement existing rules, but to develop targeted detections that specifically address an organization’s risk profile and technological ecosystem.

Core principles of detection as code

Detection as code fundamentally reimagines threat monitoring as a software development process. This approach involves:Version controlling detection rulesImplementing peer review processesUtilizing automated testingCreating reproducible and scalable detection mechanisms

By treating detection rules like software code, security teams can:Track changes systematicallyMaintain clear documentation of rule modificationsContinuously validate and improve detection capabilities

Testing and validation strategies

A critical component of detection as code is rigorous testing. Khalsa highlighted the importance of:Creating proof-of-concept exploitsDeveloping both positive and negative test casesSimulating potential attack variationsImplementing automated testing through tools like WAF simulators

The goal is not just to detect known threats, but to anticipate and model potential evasion techniques that attackers might employ.

Automation and continuous improvement

Harrison emphasized the potential for automation in detection processes. By establishing feedback loops and monitoring detection performance, teams can:Automatically adjust rules based on performance metricsGenerate alerts for high-false-positive scenariosCreate systematic processes for detection refinement

Skills and cultural transformation

Implementing detection as code requires a cultural shift. While not every security professional needs to be a expert programmer, understanding code and being comfortable with version control systems is increasingly important. Young suggested that security teams focus on:Being able to read and understand codeCollaborating closely with engineering teamsMaintaining a data-driven approach to detection development

Practical implementation recommendations

For organizations considering detection as code, the Fastly experts recommended:Starting small and focusing on specific teams or processesGathering leadership support through demonstrable metricsContinuously measuring and communicating the value of new detection approachesInvesting in training and tools that support this methodology

Conclusion

Detection as code represents more than a technical approach—it’s a strategic reimagining of security operations. By treating detection rules with the same rigor as software development, organizations can create more adaptive, precise, and effective threat monitoring capabilities.

The future of cybersecurity lies not in static, one-size-fits-all solutions, but in intelligent, continuously evolving detection mechanisms that can rapidly respond to emerging threats.