Detection: Baseline of DNS Query Length - MLTK

REMOVED DETECTION

This detection has been removed from the Splunk Threat Research content library and is no longer maintained or supported.

Reason: All detection(s) which leverage this baseline have been deprecated. As such, this baseline has been deprecated as well.

Removed in version: 5.26.0

If you have any questions or concerns, please reach out to us at research@splunk.com.

Updated Date: 2026-05-13 ID: c914844c-0ff5-4efc-8d44-c063443129ba Author: Rico Valdez, Splunk Type: Baseline Product: Splunk Enterprise Security

Description

This search is used to build a Machine Learning Toolkit (MLTK) model to characterize the length of the DNS queries for each DNS record type observed in the environment. By default, the search uses the last 30 days of data to build the model. The model created by this search is then used in the corresponding detection search, which uses it to identify outliers in the length of the DNS query.

Search

1
2| tstats `security_content_summariesonly` count from datamodel=Network_Resolution by DNS.query DNS.record_type 
3| search DNS.record_type=* 
4| `drop_dm_object_name("DNS")` 
5| eval query_length = len(query) 
6| fit DensityFunction query_length by record_type into dns_query_pdfmodel

Data Source

No data sources specified for this detection.

Macros Used

Name	Value
security_content_summariesonly	`summariesonly=`summariesonly_config `allow_old_summaries=`oldsummaries_config `fillnull_value=`fillnull_config``

Annotations

- MITRE ATT&CK

+ Kill Chain Phases

+ NIST

+ CIS

- Threat Actors

ID	Technique	Tactic

Default Configuration

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

Setting	Value
Disabled	true
Cron Schedule	`N/A`
Earliest Time	`N/A`
Latest Time	`N/A`
Schedule Window	`N/A`
Creates Finding (Notable)	No
Creates Intermediate Finding (Risk Event)	No

Implementation

To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model. In addition, you must have the Machine Learning Toolkit (MLTK) version >= 4.2 installed, along with any required dependencies. By default, the search builds the model using the past 30 days of data. You can modify the search window to build the model over a longer period of time, which may give you better results. You may also want to periodically re-run this search to rebuild the model with the latest data. More information on the algorithm used in the search can be found at https://help.splunk.com/en/splunk-enterprise/apply-machine-learning/use-splunk-machine-learning-toolkit/5.5.0/algorithms-and-scoring-metrics-in-mltk/algorithms-in-the-splunk-machine-learning-toolkit#densityfunction-0.

Known False Positives

No false positives have been identified at this time.

Associated Analytic Story

Detection Testing

Test Type	Status	Dataset	Source	Sourcetype
Validation	Not Applicable	N/A	N/A	N/A
Unit	Not Applicable	N/A	`N/A`	`N/A`
Integration	Not Applicable	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: 3