Name:Windows Modify Registry Qakbot Binary Data Registry id:2e768497-04e0-4188-b800-70dd2be0e30d version:7 date:2025-04-22 author:Teoderick Contreras, Bhavin Patel, Splunk status:production type:Anomaly Description:The following analytic detects the creation of a suspicious registry entry by Qakbot malware, characterized by 8 random registry value names with encrypted binary data. This detection leverages data from Endpoint Detection and Response (EDR) agents, focusing on registry modifications under the "SOFTWARE\\Microsoft\\" path by processes like explorer.exe. This activity is significant as it indicates potential Qakbot infection, which uses the registry to store malicious code or configuration data. If confirmed malicious, this could allow attackers to maintain persistence and execute arbitrary code on the compromised system. Data_source:
-Sysmon EventID 1 AND Sysmon EventID 12
-Sysmon EventID 1 AND Sysmon EventID 13
search:| tstats `security_content_summariesonly` count dc(registry_value_name) as registry_value_name_count FROM datamodel=Endpoint.Registry where Registry.registry_path="*\\SOFTWARE\\Microsoft\\*" AND Registry.registry_value_data = "Binary Data" by _time span=1m Registry.action Registry.dest Registry.process_guid Registry.process_id Registry.registry_hive Registry.registry_path Registry.registry_key_name Registry.registry_value_data Registry.registry_value_name Registry.registry_value_type Registry.status Registry.user Registry.vendor_product | `drop_dm_object_name(Registry)` | eval registry_key_name_len = len(registry_key_name) | eval registry_value_name_len = len(registry_value_name) | regex registry_value_name="^[0-9a-fA-F]{8}" | where registry_key_name_len < 80 AND registry_value_name_len == 8 | join process_guid, _time [| tstats `security_content_summariesonly` count FROM datamodel=Endpoint.Processes where Processes.process_name IN ("explorer.exe", "wermgr.exe","dxdiag.exe", "OneDriveSetup.exe", "mobsync.exe", "msra.exe", "xwizard.exe") by _time span=1m Processes.action Processes.dest Processes.original_file_name Processes.parent_process Processes.parent_process_exec Processes.parent_process_guid Processes.parent_process_id Processes.parent_process_name Processes.parent_process_path Processes.process Processes.process_exec Processes.process_guid Processes.process_hash Processes.process_id Processes.process_integrity_level Processes.process_name Processes.process_path Processes.user Processes.user_id Processes.vendor_product | `drop_dm_object_name(Processes)` ] | stats min(_time) as firstTime max(_time) as lastTime values(registry_value_name) as registry_value_name dc(registry_value_name) as registry_value_name_count values(registry_key_name) by dest process_guid process_name parent_process_name | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | where registry_value_name_count >= 5 | `windows_modify_registry_qakbot_binary_data_registry_filter`
how_to_implement: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:unknown References: -https://www.trustwave.com/en-us/resources/blogs/spiderlabs-blog/decrypting-qakbots-encrypted-registry-keys/ drilldown_searches: name:'View the detection results for - "$dest$"' search:'%original_detection_search% | search dest = "$dest$"' earliest_offset:'$info_min_time$' latest_offset:'$info_max_time$' name:'View risk events for the last 7 days for - "$dest$"' search:'| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$dest$") starthoursago=168 | stats count min(_time) as firstTime max(_time) as lastTime values(search_name) as "Search Name" values(risk_message) as "Risk Message" values(analyticstories) as "Analytic Stories" values(annotations._all) as "Annotations" values(annotations.mitre_attack.mitre_tactic) as "ATT&CK Tactics" by normalized_risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' earliest_offset:'$info_min_time$' latest_offset:'$info_max_time$' tags: analytic_story: - 'Qakbot' asset_type:Endpoint mitre_attack_id: - 'T1112' product: - 'Splunk Enterprise' - 'Splunk Enterprise Security' - 'Splunk Cloud' security_domain:endpoint
