Techniques
Sample rules
Detect Distributed Password Spray Attempts
- source: splunk
- technicques:
- T1110.003
- T1110
Description
This analytic employs the 3-sigma approach to identify distributed password spray attacks. A distributed password spray attack is a type of brute force attack where the attacker attempts a few common passwords against many different accounts, connecting from multiple IP addresses to avoid detection. By utilizing the Authentication Data Model, this detection is effective for all CIM-mapped authentication events, providing comprehensive coverage and enhancing security against these attacks.
Detection logic
| tstats `security_content_summariesonly` dc(Authentication.user) AS unique_accounts dc(Authentication.src) as unique_src values(Authentication.app) as app values(Authentication.src) as src count(Authentication.user) as total_failures from datamodel=Authentication.Authentication where Authentication.action="failure" NOT Authentication.src IN ("-","unknown") Authentication.user_agent="*" by Authentication.signature_id, Authentication.user_agent, sourcetype, _time span=10m
| `drop_dm_object_name("Authentication")` ```fill out time buckets for 0-count events during entire search length```
| appendpipe [
| timechart limit=0 span=10m count
| table _time]
| fillnull value=0 unique_accounts, unique_src ``` Create aggregation field & apply to all null events```
| eval counter=sourcetype+"__"+signature_id
| eventstats values(counter) as fnscounter
| eval counter=coalesce(counter,fnscounter)
| stats values(total_failures) as total_failures values(signature_id) as signature_id values(src) as src values(sourcetype) as sourcetype values(app) as app count by counter unique_accounts unique_src user_agent _time
``` remove 0 count rows where counter has data```
| sort - _time unique_accounts
| dedup _time counter ``` 3-sigma detection logic ```
| eventstats avg(unique_accounts) as comp_avg_user , stdev(unique_accounts) as comp_std_user avg(unique_src) as comp_avg_src , stdev(unique_src) as comp_std_src by counter user_agent
| eval upperBoundUser=(comp_avg_user+comp_std_user*3), upperBoundsrc=(comp_avg_src+comp_std_src*3)
| eval isOutlier=if((unique_accounts > 30 and unique_accounts >= upperBoundUser) and (unique_src > 30 and unique_src >= upperBoundsrc), 1, 0)
| replace "::ffff:*" with * in src
| where isOutlier=1
| foreach *
[ eval <<FIELD>> = if(<<FIELD>>="null",null(),<<FIELD>>)]
| mvexpand src
| iplocation src
| table _time, unique_src, unique_accounts, total_failures, sourcetype, signature_id, user_agent, src, Country
| eval date_wday=strftime(_time,"%a"), date_hour=strftime(_time,"%H")
| `detect_distributed_password_spray_attempts_filter`