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Description

This analytic is to detect a suspicious high frequency copying/moving of files in network share as part of information sabotage. This anomaly event can be a good indicator of insider trying to sabotage data by transfering classified or internal files within network share to exfitrate it after or to lure evidence of insider attack to other user. This behavior may catch several noise if network share is a common place for classified or internal document processing.

  • Type: Anomaly
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud

  • Last Updated: 2021-11-16
  • Author: Teoderick Contreras, Splunk
  • ID: 40925f12-4709-11ec-bb43-acde48001122

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1537 Transfer Data to Cloud Account Exfiltration
Kill Chain Phase
  • Actions On Objectives
NIST
  • DE.AE
CIS20
  • CIS 10
CVE
1
2
3
4
5
6
7
8
`wineventlog_security` EventCode=5145 Relative_Target_Name IN ("*.doc","*.docx","*.xls","*.xlsx","*.ppt","*.pptx","*.log","*.txt","*.db","*.7z","*.zip","*.rar","*.tar","*.gz","*.jpg","*.gif","*.png","*.bmp","*.pdf","*.rtf","*.key") Object_Type=File Share_Name IN ("\\\\*\\C$","\\\\*\\IPC$","\\\\*\\admin$") Access_Mask= "0x2" 
|  bucket _time span=5m 
| stats values(Relative_Target_Name) as valRelativeTargetName, values(Share_Name) as valShareName, values(Object_Type) as valObjectType, values(Access_Mask) as valAccessmask, values(src_port) as valSrcPort, values(Source_Address) as valSrcAddress count as numShareName by dest, _time, EventCode, user 
| eventstats avg(numShareName) as avgShareName, stdev(numShareName) as stdShareName, count as numSlots by dest, _time, EventCode, user 
|  eval upperThreshold=(avgShareName + stdShareName *3) 
|  eval isOutlier=if(avgShareName > 20 and avgShareName >= upperThreshold, 1, 0) 
|  search isOutlier=1 
| `high_frequency_copy_of_files_in_network_share_filter`

Macros

The SPL above uses the following Macros:

:information_source: high_frequency_copy_of_files_in_network_share_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
  • EventCode
  • Share_Name
  • Relative_Target_Name
  • Object_Type
  • Access_Mask
  • user
  • src_port
  • Source_Address

How To Implement

o successfully implement this search, you need to be ingesting Windows Security Event Logs with 5145 EventCode enabled. The Windows TA is also required. Also enable the object Audit access success/failure in your group policy.

Known False Positives

this behavior may seen in normal transfer of file within network if network share is common place for sharing documents.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
9.0 30 30 high frequency copy of document in network share $Share_Name$ from $Source_Address$ by $user$

: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: 1