This search is to detect a suspicious bcdedit.exe execution to ignore all failures. This technique was used by ransomware to prevent the compromise machine automatically boot in repair mode.
- Type: TTP
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2021-06-10
- Author: Teoderick Contreras, Splunk
- ID: 7742aa92-c9d9-11eb-bbfc-acde48001122
Kill Chain Phase
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.process_name = "bcdedit.exe" Processes.process = "*bootstatuspolicy*" Processes.process = "*ignoreallfailures*" by Processes.parent_process_name Processes.parent_process Processes.process_name Processes.process Processes.dest Processes.user Processes.process_id Processes.process_guid | `drop_dm_object_name(Processes)` | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `prevent_automatic_repair_mode_using_bcdedit_filter`
The SPL above uses the following Macros:
prevent_automatic_repair_mode_using_bcdedit_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
Supported Add-on (TA)
List of Splunk Add-on’s tested to work with the analytic.
List of fields required to use this analytic.
How To Implement
To successfully implement this search, you need to be ingesting logs with the process name, parent process, and command-line executions from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. Tune and filter known instances where renamed bcdedit.exe may be used.
Known False Positives
Administrators may modify the boot configuration ignore failure during testing and debugging.
Associated Analytic Story
|56.0||70||80||A suspicious process $process_name$ with process id $process_id$ contains commandline $process$ to ignore all bcdedit execution failure in host $dest$|
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
source | version: 1