THIS IS A DEPRECATED DETECTION
This detection has been marked deprecated by the Splunk Threat Research team. This means that it will no longer be maintained or supported.
This search allows you to identify the endpoints that have connected to more than five DNS servers and made DNS Queries over the time frame of the search.
- Type: TTP
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Network_Resolution
- Last Updated: 2020-07-21
- Author: David Dorsey, Splunk
- ID: 74ec6f18-604b-4202-a567-86b2066be3ce
Kill Chain Phase
- Command & Control
- CIS 9
- CIS 12
- CIS 13
1 2 3 4 5 | tstats `security_content_summariesonly` count, values(DNS.dest) AS dest dc(DNS.dest) as dest_count from datamodel=Network_Resolution where DNS.message_type=QUERY by DNS.src | `drop_dm_object_name("Network_Resolution")` |where dest_count > 5 | `clients_connecting_to_multiple_dns_servers_filter`
The SPL above uses the following Macros:
clients_connecting_to_multiple_dns_servers_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
This search requires that DNS data is being ingested and populating the
Network_Resolution data model. This data can come from DNS logs or from solutions that parse network traffic for this data, such as Splunk Stream or Bro.
This search produces fields (
dest_count) that are not yet supported by ES Incident Review and therefore cannot be viewed when a notable event is raised. These fields contribute additional context to the notable. To see the additional metadata, add the following fields, if not already present, to Incident Review - Event Attributes (Configure > Incident Management > Incident Review Settings > Add New Entry):\n1. Label: Distinct DNS Connections, Field: dest_count
Detailed documentation on how to create a new field within Incident Review may be found here:
Known False Positives
It's possible that an enterprise has more than five DNS servers that are configured in a round-robin rotation. Please customize the search, as appropriate.
Associated Analytic Story
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: 3