The following analytic detects accounts with high number of Single Sign ON (SSO) logon errors. Excessive logon errors may indicate attempts to bruteforce of password or single sign on token hijack or reuse.
- Type: Anomaly
Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Last Updated: 2023-08-02
- Author: Rod Soto, Splunk
- ID: 8158ccc4-6038-11eb-ae93-0242ac130002
Kill Chain Phase
- CIS 10
1 2 3 4 5 6 `o365_management_activity` Workload=AzureActiveDirectory LogonError=*Sso* Operation=UserLoginFailed | stats count min(_time) as firstTime max(_time) as lastTime values(user) as user by src_ip signature user_agent authentication_service action | where count >= 5 | `security_content_ctime(firstTime)` | `security_content_ctime(lastTime)` | `o365_excessive_sso_logon_errors_filter`
The SPL above uses the following Macros:
o365_excessive_sso_logon_errors_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
List of fields required to use this analytic.
How To Implement
You must install splunk Microsoft Office 365 add-on. This search works with o365:management:activity
Known False Positives
Logon errors may not be malicious in nature however it may indicate attempts to reuse a token or password obtained via credential access attack.
Associated Analytic Story
|64.0||80||80||Excessive number of SSO logon errors from $src_ip$ using UserAgent $user_agent$.|
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
source | version: 3