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This search is used to examine web sessions to identify those where the clicks are occurring too quickly for a human or are occurring with a near-perfect cadence (high periodicity or low standard deviation), resembling a script driven session.

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

  • Last Updated: 2018-10-08
  • Author: Jim Apger, Splunk
  • ID: 31337bbb-bc22-4752-b599-ef192df2dc7a


ID Technique Tactic
T1078 Valid Accounts Defense Evasion, Initial Access, Persistence, Privilege Escalation
Kill Chain Phase
  • Actions on Objectives
  • DE.AE
  • DE.CM
  • CIS 6
`stream_http` http_content_type=text* 
| rex field=cookie "form_key=(?<session_id>\w+)" 
| streamstats window=2 current=1 range(_time) as TimeDelta by session_id 
| where TimeDelta>0 
|stats count stdev(TimeDelta) as ClickSpeedStdDev avg(TimeDelta) as ClickSpeedAvg by session_id 
| where count>5 AND (ClickSpeedStdDev<.5 OR ClickSpeedAvg<.5) 
| `web_fraud___anomalous_user_clickspeed_filter`


The SPL above uses the following Macros:

Note that web_fraud_-_anomalous_user_clickspeed_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Required field

  • _time
  • http_content_type
  • cookie

How To Implement

Start with a dataset that allows you to see clickstream data for each user click on the website. That data must have a time stamp and must contain a reference to the session identifier being used by the website. This ties the clicks together into clickstreams. This value is usually found in the http cookie. With a bit of tuning, a version of this search could be used in high-volume scenarios, such as scraping, crawling, application DDOS, credit-card testing, account takeover, etc. Common data sources used for this detection are customized Apache logs, customized IIS, and Splunk Stream.

Known False Positives

As is common with many fraud-related searches, we are usually looking to attribute risk or synthesize relevant context with loosly written detections that simply detect anamoluous behavior.

Associated Analytic story


Risk Score Impact Confidence Message
25.0 50 50 tbd


Test Dataset

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

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