Detection Engineering 5: Taking Action

The goal of detection engineering isn’t just to identify potential threats but to take meaningful action based on those findings. After documenting and analyzing your results, it is time to determine which findings require escalation, how to initiate an effective response, and how to use what you’ve learned to continuously improve detection capabilities. In this final post, we’ll cover the essentials of moving from detection to response and integrating feedback for ongoing refinement.

Making Findings Actionable

Not all detection results need immediate action. Prioritizing findings based on severity, potential impact, and alignment with known adversary tactics helps ensure that your team responds efficiently.

1. Evaluate Severity and Scope
   Begin by assessing the seriousness of each finding. A suspicious network connection from an isolated user’s device might be low-priority, while a privilege escalation on a critical server demands immediate attention. Severity should take into account both the type of behavior detected and its potential consequences.
2. Check Against Known Threats
   Referencing cyber threat intelligence (CTI) again here can help confirm if observed behaviors match known attack patterns or adversary tactics. If your findings align closely with specific threat actor behaviors, escalating the issue quickly is critical. CTI serves as a guide, helping to prioritize which detections are most likely to be part of a broader threat campaign.
3. Determine Escalation Path
   Once findings are prioritized, identify the appropriate escalation path. For low-level alerts, further monitoring or enrichment of the detection may be sufficient. For high-severity events, initiate immediate response actions, which may include notifying the incident response team or triggering containment protocols.

Coordinating an Effective Response

Effective response relies on well-documented findings and coordinated actions. Each detection should provide clear context and actionable information for responders, reducing the time spent interpreting raw data.

1. Prepare Detailed Handoffs
   Include all relevant context from your documentation. Summarize the behavior detected, systems involved, user activity, and any links to CTI. Providing this context in a concise report enables responders to act without delay, focusing their efforts on containment and remediation.
2. Engage Incident Response Early
   For high-priority findings, bring the incident response (IR) team in as soon as possible. An early handoff ensures that IR has the lead time to gather resources and coordinate actions with minimal disruption. Close collaboration between detection engineering and IR helps create a seamless workflow from detection to response.
3. Support with Continuous Monitoring
   While IR is handling the containment, maintain continuous monitoring to track related events or new behaviors that might emerge. The ability to pivot quickly and adjust monitoring in real time supports a more comprehensive response and helps spot any signs of lateral movement or escalation.

Continuous Improvement and Feedback

Detection engineering thrives on iteration. Each response effort provides insights that can improve analytics, reduce false positives, and increase detection accuracy.

1. Gather Lessons Learned
   After the response, conduct a review to gather lessons from what went well and what could be improved. Documenting these insights will help you make targeted improvements to your detection analytics, refining thresholds, and reducing noise in future incidents.
2. Refine Analytics Based on Feedback
   Use response findings to adjust analytics. If an attack bypassed existing detection, modify or add new conditions that could capture similar behaviors in the future. Keep an eye out for repeated patterns that indicate a gap in coverage and adjust accordingly to close those gaps.
3. Maintain Continuous Communication with IR and CTI Teams
   Detection engineering benefits significantly from ongoing input from both IR and CTI teams. Regularly consult with these teams to incorporate their feedback into your analytics. This collaboration helps detection engineering stay aligned with evolving threat tactics and ensures analytics remain relevant as threats change.

Building a Cycle of Detection, Response, and Improvement

Detection engineering operates best in a continuous cycle of improvement. Analytics should evolve with each incident, informed by real-world findings and refined to stay effective against emerging threats. By focusing on the cycle—detect, respond, refine—you create a detection capability that adapts, learns, and becomes more effective with every iteration.

Conclusion

Transitioning from detection to response is where detection engineering proves its value, moving from theory to practice. Through clear prioritization, effective response coordination, and an ongoing cycle of refinement, you can build a detection program that not only identifies adversary activity but also drives meaningful action to mitigate risks. With these foundations in place, detection engineering becomes a powerful tool for proactive security and ongoing operational improvement.