Detection: Suspicious Email - UBA Anomaly

DEPRECATED DETECTION

This detection has been marked as deprecated by the Splunk Threat Research team. This means that it will no longer be maintained or supported. If you have any questions or concerns, please reach out to us at research@splunk.com.

Updated Date: 2024-10-17 ID: 56e877a6-1455-4479-ad16-0550dc1e33f8 Author: Bhavin Patel, Splunk Type: Anomaly Product: Splunk Enterprise Security

Description

This detection looks for emails that are suspicious because of their sender, domain rareness, or behavior differences. This is an anomaly generated by Splunk User Behavior Analytics (UBA).

Search

1
2|tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime values(All_UEBA_Events.category) as category from datamodel=UEBA where nodename=All_UEBA_Events.UEBA_Anomalies All_UEBA_Events.UEBA_Anomalies.uba_model = "SuspiciousEmailDetectionModel" by All_UEBA_Events.description All_UEBA_Events.severity All_UEBA_Events.user All_UEBA_Events.uba_event_type All_UEBA_Events.link All_UEBA_Events.signature All_UEBA_Events.url All_UEBA_Events.UEBA_Anomalies.uba_model 
3| `drop_dm_object_name(All_UEBA_Events)` 
4| `drop_dm_object_name(UEBA_Anomalies)`
5| `security_content_ctime(firstTime)`
6| `security_content_ctime(lastTime)` 
7| `suspicious_email___uba_anomaly_filter`

Data Source

No data sources specified for this detection.

Macros Used

Name	Value
security_content_ctime	`convert timeformat="%Y-%m-%dT%H:%M:%S" ctime($field$)`
suspicious_email___uba_anomaly_filter	`search *`

suspicious_email___uba_anomaly_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
T1566	Phishing	Initial Access

KillChainPhase.DELIVERY

NistCategory.DE_AE

Cis18Value.CIS_10

Axiom

GOLD SOUTHFIELD

INC Ransom

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 Risk Event	True

This configuration file applies to all detections of type anomaly. These detections will use Risk Based Alerting.

Implementation

You must be ingesting data from email logs and have Splunk integrated with UBA. This anomaly is raised by a UBA detection model called "SuspiciousEmailDetectionModel." Ensure that this model is enabled on your UBA instance.

Known False Positives

This detection model will alert on any sender domain that is seen for the first time. This could be a potential false positive. The next step is to investigate and add the URL to an allow list if you determine that it is a legitimate sender.

Associated Analytic Story

Suspicious Emails

Risk Based Analytics (RBA)

Risk Message	Risk Score	Impact	Confidence
tbd	25	50	50

The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

Detection Testing

Test Type	Status	Dataset	Source	Sourcetype
Validation	Not Applicable	N/A	N/A	N/A
Unit	❌ Failing	N/A	`N/A`	`N/A`
Integration	❌ Failing	N/A	`N/A`	`N/A`

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: 5