Unusual LOLBAS in short period of time
Description
Attacker activity may compromise executing several LOLBAS applications in conjunction to accomplish their objectives. We are looking for more than usual LOLBAS applications over a window of time, by building profiles per machine.
- Type: Anomaly
- Product: Splunk Behavioral Analytics
- Datamodel: Endpoint_Processes
- Last Updated: 2020-08-25
- Author: Ignacio Bermudez Corrales, Splunk
- ID: 59c0dd70-169c-4900-9a1f-bfcf13302f93
ATT&CK
ID | Technique | Tactic |
---|---|---|
T1059 | Command and Scripting Interpreter | Execution |
T1053 | Scheduled Task/Job | Execution, Persistence, Privilege Escalation |
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| from read_ssa_enriched_events()
| eval device=ucast(map_get(input_event, "dest_device_id"), "string", null), process_name=lower(ucast(map_get(input_event, "process_name"), "string", null)), timestamp=parse_long(ucast(map_get(input_event, "_time"), "string", null))
| where process_name=="regsvcs.exe" OR process_name=="ftp.exe" OR process_name=="dfsvc.exe" OR process_name=="rasautou.exe" OR process_name=="schtasks.exe" OR process_name=="xwizard.exe" OR process_name=="findstr.exe" OR process_name=="esentutl.exe" OR process_name=="cscript.exe" OR process_name=="reg.exe" OR process_name=="csc.exe" OR process_name=="atbroker.exe" OR process_name=="print.exe" OR process_name=="pcwrun.exe" OR process_name=="vbc.exe" OR process_name=="rpcping.exe" OR process_name=="wsreset.exe" OR process_name=="ilasm.exe" OR process_name=="certutil.exe" OR process_name=="replace.exe" OR process_name=="mshta.exe" OR process_name=="bitsadmin.exe" OR process_name=="wscript.exe" OR process_name=="ieexec.exe" OR process_name=="cmd.exe" OR process_name=="microsoft.workflow.compiler.exe" OR process_name=="runscripthelper.exe" OR process_name=="makecab.exe" OR process_name=="forfiles.exe" OR process_name=="desktopimgdownldr.exe" OR process_name=="control.exe" OR process_name=="msbuild.exe" OR process_name=="register-cimprovider.exe" OR process_name=="tttracer.exe" OR process_name=="ie4uinit.exe" OR process_name=="sc.exe" OR process_name=="bash.exe" OR process_name=="hh.exe" OR process_name=="cmstp.exe" OR process_name=="mmc.exe" OR process_name=="jsc.exe" OR process_name=="scriptrunner.exe" OR process_name=="odbcconf.exe" OR process_name=="extexport.exe" OR process_name=="msdt.exe" OR process_name=="diskshadow.exe" OR process_name=="extrac32.exe" OR process_name=="eventvwr.exe" OR process_name=="mavinject.exe" OR process_name=="regasm.exe" OR process_name=="gpscript.exe" OR process_name=="rundll32.exe" OR process_name=="regsvr32.exe" OR process_name=="regedit.exe" OR process_name=="msiexec.exe" OR process_name=="gfxdownloadwrapper.exe" OR process_name=="presentationhost.exe" OR process_name=="regini.exe" OR process_name=="wmic.exe" OR process_name=="runonce.exe" OR process_name=="syncappvpublishingserver.exe" OR process_name=="verclsid.exe" OR process_name=="psr.exe" OR process_name=="infdefaultinstall.exe" OR process_name=="explorer.exe" OR process_name=="expand.exe" OR process_name=="installutil.exe" OR process_name=="netsh.exe" OR process_name=="wab.exe" OR process_name=="dnscmd.exe" OR process_name=="at.exe" OR process_name=="pcalua.exe" OR process_name=="cmdkey.exe" OR process_name=="msconfig.exe"
| stats count(process_name) as lolbas_counter by device,span(timestamp, 300s)
| eval lolbas_counter=lolbas_counter*1.0
| rename window_end as timestamp
| adaptive_threshold algorithm="quantile" value="lolbas_counter" entity="device" window=2419200000L
| where label AND quantile>0.99
| eval start_time = window_start, end_time = timestamp, entities = mvappend(device), body=create_map(["lolbas_counter", lolbas_counter, "quantile", quantile, "device", device])
| into write_ssa_detected_events();
Macros
The SPL above uses the following Macros:
Note that unusual_lolbas_in_short_period_of_time_filter
is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
Required field
- dest_device_id
- _time
- process_name
How To Implement
Collect endpoint data such as sysmon or 4688 events.
Known False Positives
Some administrative tasks may involve multiple use of LOLBAS applications in a short period of time. This might trigger false positives at the beginning when it hasn't collected yet enough data to construct the baseline.
Associated Analytic story
Kill Chain Phase
- Exploitation
RBA
Risk Score | Impact | Confidence | Message |
---|---|---|---|
25.0 | 50 | 50 | A system process $process_name$ with commandline $cmd_line$ spawn iin short period of time in host $dest_device_id$ |
Note that risk score is calculated base on the following formula: (Impact * Confidence)/100
Reference
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: 2