This search allows you to identify DNS requests and compute the standard deviation on the length of the names being resolved, then filter on two times the standard deviation to show you those queries that are unusually large for your environment.
- Type: Anomaly
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Network_Resolution
- Last Updated: 2021-10-06
- Author: Bhavin Patel, Splunk
- ID: 1a67f15a-f4ff-4170-84e9-08cf6f75d6f5
Kill Chain Phase
- Actions On Objectives
- CIS 13
1 2 3 4 5 6 7 8 9 10 11 12 13 | tstats `security_content_summariesonly` count from datamodel=Network_Resolution where NOT DNS.message_type IN("Pointer","PTR") by DNS.query host | `drop_dm_object_name("DNS")` | eval tlds=split(query,".") | eval tld=mvindex(tlds,-1) | eval tld_len=len(tld) | search tld_len<=24 | eval query_length = len(query) | table host query query_length record_type count | eventstats stdev(query_length) AS stdev avg(query_length) AS avg p50(query_length) AS p50 | where query_length>(avg+stdev*2) | eval z_score=(query_length-avg)/stdev | `dns_query_length_with_high_standard_deviation_filter`
The SPL above uses the following Macros:
dns_query_length_with_high_standard_deviation_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
List of fields required to use this analytic.
How To Implement
To successfully implement this search, you will need to ensure that DNS data is populating the Network_Resolution data model.
Known False Positives
It's possible there can be long domain names that are legitimate.
Associated Analytic Story
|56.0||70||80||A dns query $query$ with 2 time standard deviation of name len of the dns query in host $host$|
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
source | version: 4