Coverage
Does your logic see meaningful suspicious behavior or only one very narrow pattern? Understand missing data and blind spots.
ENGINEERING / SECURITY LAB / DETECTION
FIND THE
SIGNAL.
Correlate DLP detections with identity, email, web and endpoint evidence across three financial-sector exfiltration investigations. This is a safe, browser-only SPL-inspired simulator—not a live Splunk instance.
01 / INVESTIGATE
Detection workbench.
Run a supported query, inspect the matching events, and refine the detection. Try a scenario preset to get started.
Supported: index=security, field filters (e.g. case_id=ssn), !=, | search, | stats count by field, | sort - count, | head 10, | table field1 field2. No arbitrary SPL execution.
EVENTS SCANNED0
RESULTS0
DATASETSYNTHETIC
Training simulation: every event, subject, host, timestamp, identifier and incident is fictional. No customer PII, payment-card data, real source code or employer control configurations are included. Query syntax and results are simplified and are not a substitute for real Splunk evaluation, enterprise detection validation, or threat attribution.
02 / ENGINEERING DECISIONS
What makes a detection useful?
Noise reduction
Aggregate related events, compare expected activity, and avoid declaring every anomaly malicious.
Actionability
Every useful alert should include enough context for an analyst to evaluate scope, urgency, and next steps.