:warning: THIS IS A EXPERIMENTAL DETECTION

This detection has been marked experimental by the Splunk Threat Research team. This means we have not been able to test, simulate, or build datasets for this detection. Use at your own risk. This analytic is NOT supported.

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Description

The following analytic detects emails containing attachments with suspicious file extensions. It leverages the Email data model in Splunk, using the tstats command to identify emails where the attachment filename is not empty. This detection is significant for SOC analysts as it highlights potential phishing or malware delivery attempts, which are common vectors for data breaches and malware infections. If confirmed malicious, this activity could lead to unauthorized access to sensitive information, system compromise, or data exfiltration. Immediate review and analysis of the identified emails and attachments are crucial to mitigate these risks.

  • Type: Anomaly
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Email
  • Last Updated: 2024-05-29
  • Author: David Dorsey, Splunk
  • ID: 473bd65f-06ca-4dfe-a2b8-ba04ab4a0084

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1566.001 Spearphishing Attachment Initial Access
T1566 Phishing Initial Access
Kill Chain Phase
  • Delivery
NIST
  • DE.AE
CIS20
  • CIS 13
CVE 


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| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Email where All_Email.file_name="*" by All_Email.src_user, All_Email.file_name All_Email.message_id 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)` 
| `drop_dm_object_name("All_Email")` 
| `suspicious_email_attachments` 
| `suspicious_email_attachment_extensions_filter`

Macros

The SPL above uses the following Macros:

:information_source: suspicious_email_attachment_extensions_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Required fields

List of fields required to use this analytic.

  • _time
  • All_Email.file_name
  • All_Email.src_user
  • All_Email.message_id

How To Implement

You need to ingest data from emails. Specifically, the sender's address and the file names of any attachments must be mapped to the Email data model. Splunk Phantom Playbook Integration If Splunk Phantom is also configured in your environment, a Playbook called "Suspicious Email Attachment Investigate and Delete" can be configured to run when any results are found by this detection search. To use this integration, install the Phantom App for Splunk https://splunkbase.splunk.com/app/3411/, and add the correct hostname to the "Phantom Instance" field in the Adaptive Response Actions when configuring this detection search. The notable event will be sent to Phantom and the playbook will gather further information about the file attachment and its network behaviors. If Phantom finds malicious behavior and an analyst approves of the results, the email will be deleted from the user's inbox.'

Known False Positives

None identified

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
25.0 50 50 tbd

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

Reference

Test Dataset

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 | version: 4