Windows Registry Payload Injection
Description
The following analytic detects suspiciously long data written to the Windows registry, a behavior often linked to fileless malware or persistence techniques. It leverages Endpoint Detection and Response (EDR) telemetry, focusing on registry events with data lengths exceeding 512 characters. This activity is significant as it can indicate an attempt to evade traditional file-based defenses, making it crucial for SOC monitoring. If confirmed malicious, this technique could allow attackers to maintain persistence, execute code, or manipulate system configurations without leaving a conventional file footprint.
Query · spl
| tstats `security_content_summariesonly` count FROM datamodel=Endpoint.Registry
WHERE Registry.registry_value_data=*
BY _time span=1h Registry.dest
Registry.registry_path Registry.registry_value_name Registry.process_guid
Registry.registry_value_data Registry.registry_key_name Registry.registry_hive
Registry.status Registry.action Registry.process_id
Registry.user Registry.vendor_product
| `drop_dm_object_name(Registry)`
| eval reg_data_len = len(registry_value_data)
| where reg_data_len > 512
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `windows_registry_payload_injection_filter`
Implementation guide
The detection is based on data that originates from Endpoint Detection and Response (EDR) agents. These agents are designed to provide security-related telemetry from the endpoints where the agent is installed. To implement this search, you must ingest logs that contain the process GUID, process name, and parent process. Additionally, you must ingest complete command-line executions. These logs must be processed using the appropriate Splunk Technology Add-ons that are specific to the EDR product. The logs must also be mapped to the Processes node of the Endpoint data model. Use the Splunk Common Information Model (CIM) to normalize the field names and speed up the data modeling process.
Known false positives
- No false positives have been identified at this time.
Analyst notes
Known false positives: No false positives have been identified at this time.