Windows Apache Benchmark Binary
The following analytic identifies a default behavior of a MetaSploit payload. MetaSploit uses Apache Benchmark to generate payloads. The payloads contain standard artifacts including "Apache Benchmark" and the original file name is always ab.exe. During triage, review the process and it's path. It is possible network connections spawned from it. Review parallel processes for further behaviors.
- Type: Anomaly
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2022-11-21
- Author: Michael Haag, Splunk
- ID: 894f48ea-8d85-4dcd-9132-c66cdb407c9b
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.Processes where Processes.original_file_name=ab.exe by Processes.dest Processes.user Processes.parent_process_name Processes.process_name Processes.original_file_name Processes.process Processes.process_id Processes.parent_process_id | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `windows_apache_benchmark_binary_filter`
The SPL above uses the following Macros:
windows_apache_benchmark_binary_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
False positives should be limited as there is a small subset of binaries that contain the original file name of ab.exe. Filter as needed.
Associated Analytic Story
|100.0||100||100||A known MetaSploit default payload has been identified on $dest$ ran by $user$, $parent_process_name$ spawning $process_name$.|
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