Name:Detect Password Spray Attempts id:086ab581-8877-42b3-9aee-4a7ecb0923af version:4 date:2024-10-17 author:Dean Luxton status:production type:TTP 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. Data_source:
-Windows Event Log Security 4625
search:| tstats `security_content_summariesonly` values(Authentication.user) AS unique_user_names 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" NOT Authentication.src IN ("-","unknown") by Authentication.src, Authentication.action, Authentication.signature_id, sourcetype, _time span=5m | `drop_dm_object_name("Authentication")` ```fill out time buckets for 0-count events during entire search length``` | appendpipe [| timechart limit=0 span=5m count | table _time] | fillnull value=0 unique_accounts ``` Create aggregation field & apply to all null events``` | eval counter=src+"__"+sourcetype+"__"+signature_id | eventstats values(counter) as fnscounter | eval counter=coalesce(counter,fnscounter) ``` stats version of mvexpand ``` | stats values(app) as app values(unique_user_names) as unique_user_names values(total_failures) as total_failures values(src) as src values(signature_id) as signature_id values(sourcetype) as sourcetype count by counter unique_accounts _time ``` remove duplicate time buckets for each unique source``` | sort - _time unique_accounts | dedup _time counter ```Find the outliers``` | eventstats avg(unique_accounts) as comp_avg , stdev(unique_accounts) as comp_std by counter | eval upperBound=(comp_avg+comp_std*3) | eval isOutlier=if(unique_accounts > 30 and unique_accounts >= upperBound, 1, 0) | replace "::ffff:*" with * in src | where isOutlier=1 | foreach * [ eval <<FIELD>> = if(<<FIELD>>="null",null(),<<FIELD>>)] | table _time, src, action, app, unique_accounts, unique_user_names, total_failures, sourcetype, signature_id, counter | `detect_password_spray_attempts_filter`
how_to_implement: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.
This search operates best on a 5 minute schedule, looking back over the past 70 minutes. Configure 70 minute throttling on the two fields _time and counter. known_false_positives:Unknown References: -https://attack.mitre.org/techniques/T1110/003/ drilldown_searches: name:'View the detection results for - "$sourcetype$"' search:'%original_detection_search% | search sourcetype = "$sourcetype$"' earliest_offset:'$info_min_time$' latest_offset:'$info_max_time$' name:'View risk events for the last 7 days for - "$sourcetype$"' search:'| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$sourcetype$") starthoursago=168 | stats count min(_time) as firstTime max(_time) as lastTime values(search_name) as "Search Name" values(risk_message) as "Risk Message" values(analyticstories) as "Analytic Stories" values(annotations._all) as "Annotations" values(annotations.mitre_attack.mitre_tactic) as "ATT&CK Tactics" by normalized_risk_object | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`' earliest_offset:'$info_min_time$' latest_offset:'$info_max_time$' tags: analytic_story: - 'Compromised User Account' - 'Active Directory Password Spraying' asset_type:Endpoint atomic_guid: - '90bc2e54-6c84-47a5-9439-0a2a92b4b175' confidence:70 impact:70 message:Potential Password Spraying attack from $src$ targeting $unique_accounts$ unique accounts. mitre_attack_id: - 'T1110.003' - 'T1110' observable: name:'unique_user_names' type:'User' - role: - 'Victim' name:'src' type:'Endpoint' - role: - 'Attacker' product: - 'Splunk Enterprise' - 'Splunk Enterprise Security' - 'Splunk Cloud' risk_score:70 required_fields: - 'Authentication.action' - 'Authentication.user' - 'Authentication.src' security_domain:access
