Jason is a sales data analyst who reports to the regional sales manager. It’s Jason’s job to generate reports for his manager’s sales calls. On March 27, 2019, Jason’s account was used to generate a report. Alia, the administrator for Jason’s org, noticed a ReportAnomalyEvent about this report generation activity.
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The event contained this information.
ReportAnomalyEvent Field
Value
Score
0.9
SourceIp
96.43.144.30
EventDate
2019-03-27T07:45:07.192Z
UserId
00530000009M946
Report
00OD0000001leVCMAY
SecurityEventData
(see next table)
The SecurityEventData field contained this information.
featureName
featureValue
featureContribution
rowCount
17234
60.2%
dayOfWeek
0
25.6%
numberColumns
12
12.5%
numberFilters
11
1.04%
periodOfDay
Night
0.65%
Alia notices that this report had approximately 17k rows generated on a Sunday. She decides
to investigate further. Using the UserId field value, Alia identifies Jason as the user. She
then looks through Jason’s past report generation activity using the ReportEvent event. She
notices that Jason, a sales data analyst, generates reports of varying sizes, ranging from
just a handful of rows to 20k rows. Alia also notices that Jason often accompanies his manager
on road shows, which often involves working Sundays and nights.
Alia concludes that this detection event wasn’t anomalous because the report generation activity is well within Jason's typical activity.
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