Detection Coverage That Actually Means Something for MDR Teams

Security teams have always tracked detection coverage through things like rule counts, alert volumes, or MITRE ATT&CK mappings. But those numbers don’t answer a simple question: are we actually covered against the threats that matter? That’s the gap Binary Defense is trying to close with its NightBeacon Detect update and the new Detection Coverage Index.

Starting with real threats, not frameworks

What’s different here is where the measurement starts. Instead of mapping detections to a framework and assuming that equals coverage, the model starts with real-world threat types like ransomware or business email compromise. Then it checks whether existing detections would actually catch those attacks.

Chris Chevalier, Technical Product Owner at Binary Defense, explained it to MSSP Alert, “Most tools stop at mapping detections to a generalized framework like MITRE ATT&CK and assume that even coverage equals good coverage. Our Detection Coverage Index starts from a different premise: what actually attacks your environment. We first model real-world threat profiles based on the tactics, techniques, and execution patterns we actively observe in customer environments, then select only the profiles that are relevant to a specific client. We analyze that against the client’s actual defensive stack, the tools in place, how they’re configured, and which detections truly fire in practice, to measure how well those defenses would perform against the threats they’re statistically most likely to face.”

“The result isn’t a checklist or a compliance view, but a threat-informed confidence score that shows whether you’re protected where it matters, which is something static SIEM mappings or detection engineering pipelines aren’t designed to deliver.”

Making the score useful in real work

That shift matters because the environment has changed. Attacks move faster, systems are more complex, and teams are dealing with more alerts than ever. A flat coverage model doesn’t help much in that reality.

The confidence score is meant to be something teams can actually use. Chevalier explains:
“The confidence score is meant to be read as a living indicator, not a static verdict. In practice, teams should look at it as a trend line that reflects how well current detection capabilities align with the threats they actually face over time.”

“Small dips are expected and meaningful. They signal changes such as new attacker techniques, shifts in the threat landscape, telemetry gaps, tool configuration changes, or newly introduced detections that haven’t yet matured. What keeps it from becoming an abstract metric is that it’s explicitly operationalized on our side. Our detection engineering team investigates those changes, determines why confidence moved, and takes concrete steps to restore or improve coverage.”

From gaps to action

Another piece that stands out is how this connects visibility to action. It’s one thing to spot a gap. It’s another to fix it quickly.

Chevalier describes how that works in practice. “From the customer’s perspective, coverage is shown as a monthly summary, typically the trailing three months plus the current month-to-date, so they can clearly see the progress being made to improve and sustain their protection over time," he says.

“Behind the scenes, our Detection Engineering team works from a continuously updated view of coverage that refreshes multiple times per day. That allows us to identify and act on coverage changes immediately when a gap is flagged. Closing a gap often involves expert detection engineering work, such as tuning existing detections, adding new logic, or adapting to shifts in attacker behavior or telemetry, but the timing and execution of those actions are handled directly by our team.”

For MDR providers and MSSPs, this lines up with how services are evolving. Customers don’t just want to know what tools are running. They want to know how well they’re protected and how that’s improving over time. A model like this gives providers a clearer way to show that. It ties detection work to real threats, shows progress in a way that makes sense, and helps prioritize what actually reduces risk. Over time, that kind of visibility becomes part of how providers prove value, not just deliver alerts.