README.md

SEC1186C New High Score: How to Play RBA and Win!

Searches from Slides

Risk Score Check:

| from datamodel:"Risk" | table source risk_factor_add risk_factor_mult risk_score

Velocity Tracking:

| from datamodel:"Risk"."All_Risk" | search risk_notable_sources | stats count by search_name | eval avg=round(count/30) | eval velocity=case(avg<=1,1.25,avg>1 AND avg<=50,1,avg>50 AND avg<=100,0.75,avg>100 AND avg<=500,0.5,avg>500,0.25) | outputlookup risk_velocity.csv

Risk Score Limit:

| eval risk_ScoreSum=if(risk_ScoreSum>500, risk_ScoreSum/5, risk_ScoreSum)

Velocity Risk Score:

| eval new_risk_score=(usecase_weight+mitre_weight)*velocity

Alert Disposition Tracking:

get_notable_index | eval get_event_id_meval, rule_id=event_id, temp_time=time()+86400 | suppression_extract | search NOT suppression=* | lookup update=true correlationsearches_lookup _key as source OUTPUTNEW default_disposition | lookup update=true event_time_field=temp_time incident_review_lookup rule_id OUTPUT disposition as new_disposition | eval disposition=if(isnotnull(new_disposition),new_disposition,default_disposition) | get_notable_disposition | stats count as event_count by disposition_label, search_name, severity | eval closed_weighted_score = case(event_count <= 10, 1.5, event_count <= 20, 1, event_count > 20, 0.5) | outputlookup alert_disposition_tracking.csv

Risk Score Calcuation:

| eval new_risk_score=((usecase_weight+mitre_weight)*velocity)*closed_weighted_score