Windows Process Injection In Non-Service SearchIndexer
Description
The following analytic identifies a non-service searchindexer.exe process. QakBot, a notorious banking trojan and information stealer, often deploys a process named "searchindexer.exe" as part of its malicious activities. This legitimate Windows process, "Search Indexer," is manipulated by QakBot to masquerade and evade detection within the system. The malware uses this deceptive tactic to camouflage its presence, remaining inconspicuous while performing unauthorized actions like data exfiltration, keystroke logging, and communication with command and control servers. By adopting the guise of a genuine system process, the malicious "searchindexer.exe" process helps QakBot evade scrutiny and continue its malevolent operations without arousing suspicion.
- Type: TTP
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2024-01-03
- Author: Teoderick Contreras, Splunk
- ID: d131673f-ede1-47f2-93a1-0108d3e7fafd
Annotations
Kill Chain Phase
- Exploitation
NIST
- DE.CM
CIS20
- CIS 10
CVE
Search
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| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where Processes.parent_process_name != services.exe Processes.process_name=searchindexer.exe by Processes.dest Processes.user Processes.parent_process_name Processes.parent_process Processes.process_name Processes.process Processes.process_id Processes.parent_process_id
| `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `windows_process_injection_in_non_service_searchindexer_filter`
Macros
The SPL above uses the following Macros:
windows_process_injection_in_non-service_searchindexer_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
Required fields
List of fields required to use this analytic.
- _time
- Processes.dest
- Processes.user
- Processes.parent_process_name
- Processes.parent_process
- Processes.original_file_name
- Processes.process_name
- Processes.process
- Processes.process_id
- Processes.parent_process_path
- Processes.process_path
- Processes.parent_process_id
- Processes.process_guid
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
Associated Analytic Story
RBA
Risk Score | Impact | Confidence | Message |
---|---|---|---|
49.0 | 70 | 70 | An uncommon non-service searchindexer.exe process 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.
Reference
- https://twitter.com/Max_Mal_/status/1736392741758611607
- https://twitter.com/1ZRR4H/status/1735944522075386332
Test Dataset
Replay any dataset to Splunk Enterprise by using our replay.py
tool or the UI.
Alternatively you can replay a dataset into a Splunk Attack Range
source | version: 1