The Four Pillars of Detection Excellence
Building a Detection Program That Actually Works
Founder / CEO
Creating a detection program is complex, with hidden pitfalls that can undermine your efforts. When building your detection program, focusing on four foundational pillars greatly improves your chances of success while avoiding common traps.
The Foundation: Why Most Detection Programs Struggle
Most security teams understand what makes a good detection program. They know they need comprehensive coverage, reliable alerting, and continuous improvement. The challenge isn't knowing what to do—it's having the operational framework to actually implement these concepts at scale.
Without a systematic approach, even well-intentioned detection programs devolve into chaos. You end up with scattered rules across multiple platforms with no central visibility, static detections that degrade over time without review, and no clear understanding of coverage gaps or performance metrics. Manual processes that worked fine for a dozen rules completely break down when you're managing hundreds, leaving you unable to scale with growing threats.
The Four Pillars of Detection Excellence
1. Reliability: Trust in Your Detections
What it means:
The ability of a detection to fire when intended conditions occur—and only then.
Why it matters:
If your team doesn't trust your detections, they'll either ignore alerts (missing real threats) or waste time on false positives. Reliability is the foundation of operational efficiency.
How to achieve it:
Start by implementing version control for all detection logic—no more "DetectionRules_final_v2.xlsx" chaos. Create comprehensive testing frameworks before deployment so you know your rules work before they hit production. Monitor detection performance metrics continuously because what you can't measure, you can't improve. And validate detections through regular adversary simulation, because the only way to know if your detections actually catch attacks is to run attacks against them.
Where teams fail:
Most organizations deploy detections and assume they'll keep working. Without continuous validation and performance monitoring, detection accuracy degrades over time as environments change.
2. Coverage: Know Your Blind Spots
What it means:
Systematic visibility into what threats you can and cannot detect across your environment.
Why it matters:
You can't defend against what you can't see. Understanding coverage gaps allows you to make informed decisions about where to invest resources.
How to achieve it:
Map all detections to frameworks like MITRE ATT&CK so you can visualize what you're covering. Document data source requirements and availability. Identify gaps between available telemetry and detection needs—this is where your blind spots live. Most importantly, prioritize coverage based on your threat model, not what's easiest to implement or what the vendor demo showed you.
Where teams fail:
Teams often focus on quantity over quality, deploying hundreds of detections without understanding which threats remain unaddressed. This creates a false sense of security.
3. Maturity: Evolution Through Lifecycle
What it means:
The progression of detections through defined stages, from experimental to production-ready.
Why it matters:
Not all detections are created equal. Understanding maturity helps you allocate resources appropriately and set proper expectations for detection performance.
How to achieve it:
Define clear maturity levels like Experimental, Testing, and Production so everyone knows what to expect from each detection. Establish criteria for advancement between levels—a detection shouldn't graduate to production just because it's been around for six months. Track time-in-stage to identify stalled detections that are consuming resources without progressing. Then allocate tuning resources based on maturity and value, not whoever complains loudest about false positives.
Where teams fail:
Without maturity tracking, teams treat all detections equally. This leads to wasted effort tuning experimental rules while production detections degrade unnoticed.
4. Adaptability: Responding to Change
What it means:
The ability to rapidly respond to new threats while maintaining quality and reliability.
Why it matters:
The threat landscape evolves daily. Your detection program must be agile enough to incorporate new intelligence without sacrificing stability.
How to achieve it:
Streamline deployment processes across all platforms so you can push updates quickly when threats evolve. Integrate threat intelligence feeds systematically—not just when someone remembers to check the feeds. Maintain detection templates for common patterns because you shouldn't reinvent the wheel every time you need to detect lateral movement. Build feedback loops from incident response to detection engineering so lessons learned from real attacks immediately improve your detection capabilities.
Where teams fail:
Manual deployment processes create bottlenecks. By the time new detections are deployed, the threat has often evolved or the window of opportunity has closed.
Bringing It All Together: The Multiplication Effect
These pillars don't exist in isolation—they multiply each other's effectiveness:
When Reliability meets Coverage, you gain confidence in your security posture. Coverage plus Maturity leads to efficient resource allocation. Maturity combined with Adaptability creates sustainable detection operations. And Adaptability paired with Reliability enables rapid, trustworthy threat response.
When all four pillars are strong, you create a detection program that not only identifies threats effectively but also improves continuously without burning out your team.
The Path Forward
Building these pillars requires more than good intentions.
You need executive support for the initial investment in processes and tools because this transformation doesn't happen for free. You need dedicated resources for detection engineering—not just people who respond to alerts when they have spare time. You need systematic tooling that enforces these principles by default rather than depending on human discipline. And most critically, you need a cultural commitment to continuous improvement over checkbox compliance.
Most importantly, it requires acknowledging that detection engineering is a discipline unto itself—not a side project for overworked analysts.
Start Where You Are
You don't need to perfect all four pillars simultaneously. Assess your current state:
Ask yourself: Which pillar is weakest in your organization? What's the single change that would have the most impact? How can you build momentum with early wins? These questions will guide your improvement efforts more effectively than trying to fix everything at once.
Remember: A detection program with strong foundations in these four pillars will outperform a larger program built on shaky ground. Focus on building sustainably, and the results will follow.
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