This search is to detect potential DNS exfiltration using nslookup application. This technique are seen in couple of malware and APT group to exfiltrated collected data in a infected machine or infected network. This detection is looking for unique use of nslookup where it tries to use specific record type, TXT, A, AAAA, that are commonly used by attacker and also the retry parameter which is designed to query C2 DNS multiple tries.
- Type: TTP
- Product: Splunk Behavioral Analytics
- Datamodel: Endpoint_Processes
- Last Updated: 2021-12-07
- Author: Michael Haag, Splunk
- ID: 2452e632-9e0d-11eb-34ba-acde48001122
Kill Chain Phase
1 2 3 4 5 6 7 8 | from read_ssa_enriched_events() | where "Endpoint_Processes" IN(_datamodels) | eval timestamp=parse_long(ucast(map_get(input_event, "_time"), "string", null)), cmd_line=ucast(map_get(input_event, "process"), "string", null), process_name=ucast(map_get(input_event, "process_name"), "string", null), process_path=ucast(map_get(input_event, "process_path"), "string", null), parent_process_name=ucast(map_get(input_event, "parent_process_name"), "string", null), event_id=ucast(map_get(input_event, "event_id"), "string", null) | where cmd_line IS NOT NULL AND process_name IS NOT NULL AND process_name="nslookup.exe" AND (like (cmd_line, "%-querytype=%") OR like (cmd_line, "%-qt=%") OR like (cmd_line, "%-q=%") OR like (cmd_line, "%-type=%") OR like (cmd_line, "%-retry=%")) | eval start_time=timestamp, end_time=timestamp, entities=mvappend(ucast(map_get(input_event, "dest_user_id"), "string", null), ucast(map_get(input_event, "dest_device_id"), "string", null)) | eval body=create_map(["event_id", event_id, "cmd_line", cmd_line, "process_name", process_name, "parent_process_name", parent_process_name, "process_path", process_path]) | into write_ssa_detected_events();
The SPL above uses the following Macros:
dns_exfiltration_using_nslookup_app_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
Known False Positives
It is possible for some legitimate administrative utilities to use similar cmd_line parameters. Filter as needed.
Associated Analytic Story
|72.0||90||80||An instance of $parent_process_name$ spawning $process_name$ was identified on endpoint $dest_device_id$ by user $dest_user_id$ performing activity related to DNS exfiltration.|
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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