ID | Technique | Tactic |
---|---|---|
T1110.003 | Password Spraying | Credential Access |
T1110 | Brute Force | Credential Access |
Detection: Detect Password Spray Attempts
Description
This analytic employs the 3-sigma approach to detect an unusual volume of failed authentication attempts from a single source. A password spray attack is a type of brute force attack where an attacker tries a few common passwords across many different accounts to avoid detection and account lockouts. 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.
Search
1
2| tstats `security_content_summariesonly` dc(Authentication.user) AS unique_accounts values(Authentication.app) as app count(Authentication.user) as total_failures from datamodel=Authentication.Authentication where Authentication.action="failure" by Authentication.src, Authentication.action, Authentication.signature_id, sourcetype, _time span=2m
3| `drop_dm_object_name("Authentication")` ```fill out time buckets for 0-count events during entire search length```
4| appendpipe [
5| timechart limit=0 span=5m count
6| table _time]
7| fillnull value=0 unique_accounts, unique_src ``` remove duplicate & empty time buckets```
8| sort - total_failures
9| dedup _time ``` Create aggregation field & apply to all null events```
10| eval counter=src+"__"+sourcetype+"__"+signature_id
11| eventstats values(counter) as fnscounter
12| eval counter=coalesce(counter,fnscounter)
13| eventstats avg(unique_accounts) as comp_avg , stdev(unique_accounts) as comp_std by counter
14| eval upperBound=(comp_avg+comp_std*3)
15| eval isOutlier=if(unique_accounts > 30 and unique_accounts >= upperBound, 1, 0)
16| replace "::ffff:*" with * in src
17| where isOutlier=1
18| foreach * [ eval <<FIELD>> = if(<<FIELD>>="null",null(),<<FIELD>>)]
19| table _time, src, action, app, unique_accounts, total_failures, sourcetype, signature_id
20| `detect_password_spray_attempts_filter`
Data Source
Name | Platform | Sourcetype | Source | Supported App |
---|---|---|---|---|
Windows Event Log Security 4625 | Windows | 'xmlwineventlog' |
'XmlWinEventLog:Security' |
N/A |
Macros Used
Name | Value |
---|---|
security_content_summariesonly | summariesonly= summariesonly_config allow_old_summaries= oldsummaries_config fillnull_value= fillnull_config`` |
detect_password_spray_attempts_filter | search * |
detect_password_spray_attempts_filter
is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
Annotations
Default Configuration
This detection is configured by default in Splunk Enterprise Security to run with the following settings:
Setting | Value |
---|---|
Disabled | true |
Cron Schedule | 0 * * * * |
Earliest Time | -70m@m |
Latest Time | -10m@m |
Schedule Window | auto |
Creates Notable | Yes |
Rule Title | %name% |
Rule Description | %description% |
Notable Event Fields | user, dest |
Creates Risk Event | True |
Implementation
Ensure in-scope authentication data is CIM mapped and the src field is populated with the source device. Also ensure fill_nullvalue is set within the macro security_content_summariesonly.
Known False Positives
Unknown
Associated Analytic Story
Risk Based Analytics (RBA)
Risk Message | Risk Score | Impact | Confidence |
---|---|---|---|
Potential Password Spraying attack from $src$ targeting $unique_accounts$ unique accounts. | 49 | 70 | 70 |
References
Detection Testing
Test Type | Status | Dataset | Source | Sourcetype |
---|---|---|---|---|
Validation | ✅ Passing | N/A | N/A | N/A |
Unit | ✅ Passing | Dataset | XmlWinEventLog:Security |
XmlWinEventLog |
Integration | ✅ Passing | Dataset | XmlWinEventLog:Security |
XmlWinEventLog |
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: GitHub | Version: 1