:warning: THIS IS A EXPERIMENTAL DETECTION

This detection has been marked experimental by the Splunk Threat Research team. This means we have not been able to test, simulate, or build datasets for this detection. Use at your own risk. This analytic is NOT supported.

Try in Splunk Security Cloud

Description

This search identifies DNS query failures by counting the number of DNS responses that do not indicate success, and trigger on more than 50 occurrences.

  • Type: Anomaly
  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
  • Datamodel: Network_Resolution
  • Last Updated: 2020-07-21
  • Author: Bhavin Patel, Splunk
  • ID: 104658f4-afdc-499e-9719-17243f9826f1

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1071.004 DNS Command And Control
T1071 Application Layer Protocol Command And Control
Kill Chain Phase
  • Command & Control
NIST
  • PR.PT
  • DE.AE
  • DE.CM
CIS20
  • CIS 8
  • CIS 9
  • CIS 12
CVE
1
2
3
4
5
6
7
8
9
10
11
| tstats `security_content_summariesonly` count values("DNS.query") as queries from datamodel=Network_Resolution where nodename=DNS "DNS.reply_code"!="No Error" "DNS.reply_code"!="NoError" DNS.reply_code!="unknown" NOT "DNS.query"="*.arpa" "DNS.query"="*.*" by "DNS.src","DNS.query"
| `drop_dm_object_name("DNS")`
| lookup cim_corporate_web_domain_lookup domain as query OUTPUT domain
| where isnull(domain)
| lookup update=true alexa_lookup_by_str domain as query OUTPUT rank
| where isnull(rank)
| stats sum(count) as count mode(queries) as queries by src
| `get_asset(src)`
| where count>50 
| `excessive_dns_failures_filter`

Macros

The SPL above uses the following Macros:

:information_source: excessive_dns_failures_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
  • DNS.query
  • DNS.reply_code
  • DNS.src

How To Implement

To successfully implement this search you must ensure that DNS data is populating the Network_Resolution data model.

Known False Positives

It is possible legitimate traffic can trigger this rule. Please investigate as appropriate. The threshold for generating an event can also be customized to better suit your environment.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
25.0 50 50 tbd

: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: 2