The following analytic is to identify a modification in the Windows registry to suppress windows defender notification. This technique was abuse by adversaries and threat actor to bypassed windows defender on the targeted host. Azorult malware is one of the malware use this technique that also disable toast notification and other windows features as part of its malicious behavior.
- Type: Anomaly
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2022-06-22
- Author: Teoderick Contreras, Splunk
- ID: e3b42daf-fff4-429d-bec8-2a199468cea9
Kill Chain Phase
- CIS 3
- CIS 5
- CIS 16
1 2 3 4 5 6 | tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime FROM datamodel=Endpoint.Registry where Registry.registry_path= "*\\Windows Defender\\UX Configuration\\Notification_Suppress*" Registry.registry_value_data="0x00000001" by Registry.registry_key_name Registry.user Registry.registry_path Registry.registry_value_data Registry.action Registry.dest | `drop_dm_object_name(Registry)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `windows_modify_registry_suppress_win_defender_notif_filter`
The SPL above uses the following Macros:
windows_modify_registry_suppress_win_defender_notif_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 need to be ingesting information on process that include the name of the process responsible for the changes from your endpoints into the
Endpoint datamodel in the
Registry node. Also make sure that this registry was included in your config files ex. sysmon config to be monitored.
Known False Positives
administrators may enable or disable this feature that may cause some false positive.
Associated Analytic Story
|49.0||70||70||the registry for suppresing windows fdefender notification settings was modified to disabled in $dest$|
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: 1