Turn emerging threats into tested, deployable detections across your existing stack.
Native APIs · CrowdStrike · SentinelOne · Splunk · Sentinel
defenderlens://detection-ops
Traditional Way
Manual threat research, baseline tuning, and peer reviews lag days behind active CTI releases.
[AUTHORING VELOCITY & EXPOSURE WINDOWS]
Instantly convert raw CTI into structured, deployable Detection-as-Code artifacts—slashing your exposure window from days to minutes.
Traditional Way
Unannounced vendor schema shifts and missing log fields quietly break production queries.
[TELEMETRY & SCHEMAS]
Pre-flight schema validation checks log dependencies before deployment, ensuring rules fail closed rather than failing silently.
Traditional Way
Unvalidated queries ship directly to production, causing false-positive storms and analyst fatigue.
[TESTING & VALIDATION]
Every rule undergoes static syntax analysis, behavioral testing, and historical telemetry backtesting in CI/CD before logic reaches production.
Traditional Way
Engineers spend over half their time manually rewriting identical logic across Splunk, Sentinel, and EDR consoles.
[MULTI-SIEM DEPLOYMENT]
Maintain logic in one declarative syntax; compile and deploy directly to target consoles via native platform APIs without middleware.
Traditional Way
Detections decay over time as environments evolve, leading to coverage gaps and unmaintained rules.
[LIFECYCLE DRIFT]
Automated drift detection continuously aligns live rules against underlying schema shifts, maintaining long-term fidelity.
DefenderLens connects the work between threat intelligence and operational detection.
DEFINE
Turn a threat, technique, behavior, or detection requirement into a structured detection objective.
Scope & IntelBUILD
Create detection logic in a structured, version-controlled workflow.
Git VersioningTEST
Validate detection logic and the requirements needed to support it.
Test PipelinesDEPLOY
Release validated detections to supported environments.
Native DeployMAINTAIN
Track changes and update detections as threats and environments evolve.
Continuous SyncGartner, Forrester, and SANS benchmark detection-as-code and automated testing as necessary practices.
Gartner Research Report
“Gartner identifies detection-as-code and CI/CD automation as foundational pillars of modern, scalable detection engineering.”
Modern Security Operations Centers (SOCs) are moving away from manually entering queries in consoles. Instead, they use version-controlled Git repositories, automated testing pipelines, and declarative detection definitions.
Forrester Wave Analysis
“Forrester defines detection engineering as a rigorous software lifecycle spanning ideation, design, build, test, release, and continuous monitoring.”
Continuous monitoring without automated testing and release management often creates too many false alarms. Over time, teams get alert fatigue, and detections quietly break as cloud log formats change.
SANS SOC Survey
“SANS research identifies time, fragmented telemetry, and cross-vendor data formatting as the primary friction points for detection teams.”
Detection engineers spend more than 60% of their time dealing with schema mismatches, checking for missing log fields, and manually translating queries between SIEM and EDR consoles.
From initial threat intel ingestion to continuous schema validation and automated multi-SIEM deployment.
WORKS WITH YOUR STACK
Rules deploy in your platform's native syntax via native API integrations.
No rip-and-replace.
Deploy detection rules directly via native SentinelOne Singularity API
Deploy detection rules directly via native Falcon API integrations
Generate and deploy SPL rules to your Splunk environment
Deploy detection rules via native CrowdStrike NG-SIEM integrations
Deploy detection rules to Microsoft Defender XDR via native APIs
KQL detection rules and Sentinel ARM template deployments
