From Reactive to Proactive Detection
Traditional SOC workflows are largely reactive. An alert fires. An analyst investigates. A rule gets updated after the fact. This model made sense when threats were slower and fewer. Today, it creates a dangerous lag between when a threat is known and when it is detectable.
The smarter approach is feeding threat intelligence directly into the detection pipeline and letting automation handle the conversion. Instead of analysts reading a CTI report and hoping someone eventually writes a rule, the platform reads the report and generates the rule automatically.
The Numbers That Demand Change
CardinalOps 2025 research shows that the average SIEM covers just 21% of MITRE ATT&CK techniques, even when the data exists to support broader coverage. 13% of SIEM rules are already broken or never firing. And writing a single detection rule manually takes an average of five days.
These numbers are not anomalies. They reflect structural problems in how most SOCs are built. Cyber threat intelligence that takes five days to become a detection rule provides almost no protection against fast-moving threats.
DefenderLens: Built for SOC Speed
DefenderLens was designed specifically for security teams that cannot afford to wait. The platform accepts any threat source, including CTI reports, vendor advisories, news articles, and RSS feeds, and uses AI to identify what is detectable. Within minutes, it produces YAML detection rules for CrowdStrike Falcon or Splunk, with MITRE ATT&CK mapping, severity scoring, and unit tests included.
The deployment workflow is equally streamlined. Schema validation, peer review, staging tests, and one-click production push are all managed inside the platform. Version control and rollback come standard.
Designed for MSSPs and Enterprise SOCs
For MSSPs and MDRs, managing detection across multiple client tenants is one of the biggest operational challenges. Cyber threat detection at scale requires consistency, speed, and the ability to push tuned rules across environments without manual rework for each client.
DefenderLens handles this through a single platform that generates and deploys rules across all tenants simultaneously. Detection engineering effort stops growing faster than revenue. Teams scale their coverage without scaling their headcount.
For enterprise SOCs, the win is different but equally significant. Detection engineers reclaim the 60% of their time currently consumed by maintaining old rules. Instead, they build new MITRE ATT&CK coverage daily, closing gaps that have been open for months.
What Good Looks Like
Here is what a modern, intelligence-driven SOC detection workflow looks like with DefenderLens:
- A new threat advisory is published
- The team pastes it into DefenderLens
- AI identifies detection opportunities within the advisory
- YAML rules are generated for CrowdStrike Falcon or Splunk
- Rules are validated, reviewed, and staged automatically
- One-click deployment pushes rules to production
- Version control logs everything for audit and rollback
The entire process takes minutes, not days.
Integrations That Fit Your Stack
DefenderLens currently integrates natively with CrowdStrike Falcon and Splunk via direct API. No middleware required. Upcoming integrations include Microsoft Sentinel, Elastic, and Palo Alto, which means your existing stack does not need to change to benefit from the platform.
Conclusion
The future of SOC operations is intelligence-driven and automation-powered. Teams that continue to write detection rules by hand will fall further behind with every advisory that goes unactioned. DefenderLens closes that gap by turning raw cyber threat intelligence into production-ready detections in minutes, giving your team the speed to match modern threats.