Most security leaders assume their SOC is more covered than it actually is. It is a natural assumption when alerts are firing and analysts are busy. But busyness is not the same as coverage. According to CardinalOps 2025, the average SIEM covers only 21% of MITRE ATT&CK techniques, even when the underlying data exists. That is a coverage crisis hiding behind the appearance of activity.

What Causes Intelligence Gaps to Persist

Cyber threat intelligence gaps do not exist because teams lack information. They persist because the process of converting intelligence into detection rules is slow, manual, and resource-intensive. A CTI report lands in an analyst's inbox. It gets read. Maybe it gets flagged for a detection engineer. That engineer is already working through a backlog. The rule gets written two weeks later, if at all.

In the meantime, that threat technique is active in the wild and completely undetected in your environment.

The Backlog That Never Shrinks

Detection engineering backlogs are one of the most common and least discussed problems in enterprise security. Teams produce solid threat research but cannot convert it into working detections fast enough to keep up with incoming intelligence. Every new advisory adds to the pile.

Hiring more engineers sounds like the answer, but at over $150K per engineer and with 1.4 million unfilled cybersecurity positions globally, hiring cannot solve a speed and scale problem. Cyber threat intelligence needs to be operationalized through automation, not additional headcount.

DefenderLens Fills the Gap

DefenderLens was designed specifically to eliminate the manual bottleneck between threat intelligence and deployed detection. You paste any CTI report, vendor advisory, threat article, or feed item directly into the platform. The AI analyzes the content, identifies detection opportunities, and generates production-ready YAML rules for CrowdStrike Falcon or Splunk within minutes.

Each rule is automatically mapped to MITRE ATT&CK, scored for severity, and accompanied by unit tests. The platform then manages peer review, schema validation, staging deployment, and one-click push to production. Version control and rollback are built in.

Closing ATT&CK Gaps Ten Times Faster

Enterprise SOCs using DefenderLens close MITRE ATT&CK coverage gaps ten times faster than teams relying on manual processes. Detection engineers stop spending 60% of their time maintaining old rules and start building new coverage instead.

The impact is measurable:

• More techniques covered across the ATT&CK framework

• Fewer stale or broken rules in production

• Shorter time from advisory to deployed detection

• Less noise from untested, generic vendor content

• More engineering time spent on strategy and new coverage

For cyber threat detection to work at the speed modern threats demand, the entire lifecycle must be automated, from rule generation through deployment.

MSSPs Face a Compounded Version of This Problem

For MSSPs and MDRs, coverage gaps are multiplied across every client tenant. Managing detection rules across dozens of environments manually is not sustainable. One platform, one AI-powered pipeline, and native API integrations with CrowdStrike and Splunk make it possible to maintain consistent, high-quality coverage across all tenants without proportionally increasing engineering effort.

Conclusion

Coverage gaps are not inevitable. They are the result of a detection process that has not kept pace with the volume and velocity of modern threat intelligence. DefenderLens changes that by automating the entire pipeline, from receiving intelligence to deploying detection rules, so your SOC is always working from current, tested, production-ready coverage.