Impersonation Detections by Detection Technology Trend
Description
This query visualises total emails with Phish (BEC) Impersonation detections by Detection Technology over time
Query · kql
let TimeStart = startofday(ago(30d)); let TimeEnd = startofday(now()); let baseQuery = EmailEvents | where DetectionMethods has "Phish"; let bimp=baseQuery | project Timestamp,RecipientEmailAddress,NetworkMessageId, DT=parse_json(DetectionMethods) | evaluate bag_unpack(DT) | where Phish has 'Impersonation brand' | make-series Count= count() default = 0 on Timestamp from TimeStart to TimeEnd step 1d | extend Details = "Impersonation brand"; let dimp=baseQuery | project Timestamp,RecipientEmailAddress,NetworkMessageId, DT=parse_json(DetectionMethods) | evaluate bag_unpack(DT) | where Phish has 'Impersonation domain' | make-series Count= count() default = 0 on Timestamp from TimeStart to TimeEnd step 1d | extend Details = "Impersonation domain"; let uimp=baseQuery | project Timestamp,RecipientEmailAddress,NetworkMessageId, DT=parse_json(DetectionMethods) | evaluate bag_unpack(DT) | where Phish has 'Impersonation user' | make-series Count= count() default = 0 on Timestamp from TimeStart to TimeEnd step 1d | extend Details = "Impersonation user"; let mimp=baseQuery | project Timestamp,RecipientEmailAddress,NetworkMessageId, DT=parse_json(DetectionMethods) | evaluate bag_unpack(DT) | where Phish has 'Mailbox intelligence impersonation' | make-series Count= count() default = 0 on Timestamp from TimeStart to TimeEnd step 1d | extend Details = "Mailbox intelligence impersonation"; union bimp,dimp,uimp,mimp | project Count, Details, Timestamp | render timechart