Windows Modify Registry Tamper Protection
The following analytic identifies a suspicious registry modification to tamper Windows Defender protection. This technique was being abused by several adversaries, malware authors and also red-teamers to evade detection on the targeted machine. RedLine Stealer is one of the malware we've seen that uses this technique to bypass Windows defender detection.
- Type: TTP
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2023-04-21
- Author: Teoderick Contreras, Splunk
- ID: 12094335-88fc-4c3a-b55f-e62dd8c93c23
Kill Chain Phase
- CIS 10
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="*\\SOFTWARE\\Microsoft\\Windows Defender\\Features\\TamperProtection" AND Registry.registry_value_data="0x00000000" by Registry.dest Registry.user Registry.registry_path Registry.registry_value_data Registry.registry_key_name | `drop_dm_object_name(Registry)` | `security_content_ctime(lastTime)` | `security_content_ctime(firstTime)` | `windows_modify_registry_tamper_protection_filter`
The SPL above uses the following Macros:
windows_modify_registry_tamper_protection_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
Processes node. In addition, confirm the latest CIM App 4.20 or higher is installed and the latest TA for the endpoint product.
Known False Positives
Administrators may enable or disable this feature that may cause some false positive.
Associated Analytic Story
|49.0||70||70||A registry modification to tamper Windows Defender protection on $dest$|
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
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source | version: 1