Detection: O365 Email Hard Delete Excessive Volume

Updated Date: 2026-05-13 ID: c7fe0949-348a-41ce-8f17-a09a7fe5fd7d Author: Steven Dick Type: Anomaly Product: Splunk Enterprise Security

Description

The following analytic identifies when an O365 email account hard deletes an excessive number of emails within a short period (within 1 hour). This behavior may indicate a compromised account where the threat actor is attempting to permanently purge a large amount of items from the mailbox. Threat actors may attempt to remove evidence of their activity by purging items from the compromised mailbox. --- Some account owner legitimate behaviors can trigger this alert, however these actions may not be aligned with organizational expectations / best practice behaviors.

Search

 1`o365_management_activity` Workload=Exchange (Operation IN ("HardDelete") AND Folder.Path IN ("\\Sent Items","\\Recoverable Items\\Deletions"))
 2
 3| eval user = lower(UserId), sender = lower(CASE(isnotnull(SendAsUserSmtp),SendAsUserSmtp,isnotnull(SendOnBehalfOfUserSmtp),SendOnBehalfOfUserSmtp,true(),MailboxOwnerUPN)), subject = trim(CASE(Operation IN ("Send","SendAs","SendOnBehalf"),'Item.Subject',Operation IN ("SoftDelete","HardDelete"),'AffectedItems{}.Subject')), -time = _time,file_name = CASE(Operation IN ("Send","SendAs","SendOnBehalf"),split('Item.Attachments',"; "),Operation IN ("SoftDelete","HardDelete"),split('AffectedItems{}.Attachments',"; ")), file_size = CASE(Operation IN ("Send","SendAs","SendOnBehalf"),round(tonumber('Item.SizeInBytes')/1024/1024,2),true(),round(tonumber(replace(file_name, "(.+)\s\((\d+)(b\)$)", "\2"))/1024/1024,2))
 4
 5| bin _time span=1hr
 6
 7| stats values(sender) as sender, values(ClientIPAddress) as src, values(ClientInfoString) as http_user_agent, values(Operation) as signature, latest(file_name) as file_name, sum(file_size) as file_size, values(Folder.Path) as file_path, min(-time) as firstTime, max(-time) as lastTime, dc(subject) as count by _time,user
 8
 9| where count > 50 OR file_size > 10
10
11| `security_content_ctime(firstTime)`
12
13| `security_content_ctime(lastTime)`
14
15| `o365_email_hard_delete_excessive_volume_filter`

Data Source

Name	Platform	Sourcetype	Source
Office 365 Universal Audit Log	Other	`'o365:management:activity'`	`'o365'`

Macros Used

Name	Value
o365_management_activity	`sourcetype=o365:management:activity`
o365_email_hard_delete_excessive_volume_filter	`search *`

o365_email_hard_delete_excessive_volume_filter is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Annotations

- MITRE ATT&CK

+ Kill Chain Phases

+ NIST

+ CIS

- Threat Actors

ID	Technique	Tactic
T1070.008	Clear Mailbox Data	Stealth
T1485	Data Destruction	Impact

Exploitation

Actions on Objectives

DE.AE

CIS 10

Default Configuration

This detection is configured by default in Splunk Enterprise Security to run with the following settings:

Setting	Value
Disabled	true
Cron Schedule	`0 * * * *`
Earliest Time	`-70m@m`
Latest Time	`-10m@m`
Schedule Window	`auto`
Creates Finding (Notable)	No
Creates Intermediate Finding (Risk Event)	Yes

Anomaly detections generate Intermediate Findings (Risk Events). They do not generate a Finding (Notable) directly.

Implementation

You must install the Splunk Microsoft Office 365 Add-on and ingest Office 365 management activity events.

Known False Positives

Users that habitually/proactively cleaning the recoverable items folder may trigger this alert.

Associated Analytic Story

Intermediate Findings

Message	Entity Field	Entity Type	Risk Score
The user $user$ deleted an excessing number of emails [$count$] within a short timeframe	user	user	20

Threat Objects

Field	Type
src	ip_address

References

Detection Testing

Test Type	Status	Dataset	Source	Sourcetype
Validation	✅ Passing	N/A	N/A	N/A
Unit	✅ Passing	Dataset	`o365`	`o365:management:activity`
Integration	✅ Passing	Dataset	`o365`	`o365:management:activity`

Replay any dataset to Splunk Enterprise by using our replay.py tool or the UI. Alternatively you can replay a dataset into a Splunk Attack Range

Source: GitHub | Version: 6