Name:Detect Password Spray Attack Behavior From Source id:b6391b15-e913-4c2c-8949-9eecc06efacc version:2 date:2024-09-30 author:Steven Dick status:production type:TTP Description:The following analytic identifies one source failing to authenticate with 10 or more unique users. This behavior could represent an adversary performing a Password Spraying attack to obtain initial access or elevate privileges. This logic can be used for real time security monitoring as well as threat hunting exercises and works well against any number of data sources ingested into the CIM datamodel. Environments can be very different depending on the organization. Test and customize this detections thresholds if needed. Data_source:
-Authentication Events (various)
search:| tstats `security_content_summariesonly` max(_time) as lastTime, min(_time) as firstTime, values(Authentication.user_category) as user_category values(Authentication.src_category) as src_category values(Authentication.app) as app count from datamodel=Authentication.Authentication where * by Authentication.action,Authentication.src,Authentication.user | `drop_dm_object_name("Authentication")` | eval user=case((match(upper(user),"[a-zA-Z0-9]{3}")),upper(user),true(),null), src=upper(src), success=if(action="success",count,0),success_user=if(action="success",user,null),failure=if(action="failure",count,0), failed_user=if(action="failure",user,null) | `detect_password_spray_attack_behavior_from_source_filter` | stats count min(firstTime) as firstTime max(lastTime) as lastTime values(app) as app values(src_category) as src_category values(success_user) as user values(failed_user) as failed_user dc(success_user) as success_dc dc(failed_user) as failed_dc dc(user) as user_dc ,sum(failure) as failure,sum(success) as success by src | fields - _time | where user_dc >= 10 AND .25 > (success/failure) AND failed_dc > success_dc | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)`
how_to_implement:This detection requires ingesting authentication data to the appropriate accelerated datamodel. Recommend adjusting the search time window for this correlation to match the number of unique users (user_dc) in hours. i.e. 10 users over 10hrs known_false_positives:Domain controllers, authentication chokepoints, and vulnerability scanners. References: -https://attack.mitre.org/techniques/T1110/003/ -https://www.microsoft.com/en-us/security/blog/2020/04/23/protecting-organization-password-spray-attacks/ -https://github.com/MarkoH17/Spray365 drilldown_searches: name:'View the detection results for - "$src$" and "$user$"' search:'%original_detection_search% | search src = "$src$" user = "$user$"' earliest_offset:'$info_min_time$' latest_offset:'$info_max_time$' name:'View risk events for the last 7 days for - "$src$" and "$user$"' search:'| from datamodel Risk.All_Risk | search normalized_risk_object IN ("$src$", "$user$") 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' asset_type:Account confidence:75 impact:80 message:The source [$src$] attempted to access $user_dc$ distinct users a total of $count$ times between [$firstTime$] and [$lastTime$]. $success$ successful logins detected. mitre_attack_id: - 'T1110.003' - 'T1110' observable: name:'src' type:'Hostname' - role: - 'Victim' name:'user' type:'User' - role: - 'Victim' name:'failed_user' type:'User' - role: - 'Attacker' product: - 'Splunk Enterprise' - 'Splunk Enterprise Security' - 'Splunk Cloud' required_fields: - '_time' - 'Authentication.user_category' - 'Authentication.src_category' - 'Authentication.app' - 'Authentication.action' - 'Authentication.src' - 'Authentication.user' risk_score:60 security_domain:access
