Okta Suspicious Activity Reported
THIS IS A EXPERIMENTAL DETECTION
This detection has been marked experimental by the Splunk Threat Research team. This means we have not been able to test, simulate, or build datasets for this detection. Use at your own risk. This analytic is NOT supported.
Description
The following event is generated when an associate receives an email from Okta asking if a login attempt was suspicious or not. If the associate identifies it as suspicious an event is generated and should be reviewed.
- Type: TTP
-
Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Last Updated: 2022-09-21
- Author: Michael Haag, Splunk
- ID: bfc840f5-c9c6-454c-aa13-b46fd0bf1e79
Annotations
ATT&CK
Kill Chain Phase
- Exploitation
NIST
- DE.CM
CIS20
- CIS 16
CVE
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`okta` eventType=user.account.report_suspicious_activity_by_enduser
| stats count min(_time) as firstTime max(_time) as lastTime values(displayMessage) by user eventType client.userAgent.rawUserAgent client.userAgent.browser client.geographicalContext.city client.geographicalContext.country
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `okta_suspicious_activity_reported_filter`
Macros
The SPL above uses the following Macros:
okta_suspicious_activity_reported_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
Required fields
List of fields required to use this analytic.
- _time
- displayMessage
- user
- eventType
- client.userAgent.rawUserAgent
- client.userAgent.browser
- client.geographicalContext.city
- client.geographicalContext.country
How To Implement
This analytic is specific to Okta and requires Okta logs to be ingested. It also requires that suspicious activity reporting is enabled and associates are trained to submit.
Known False Positives
False positives should be limited as this is a high fidelity marker.
Associated Analytic Story
RBA
Risk Score | Impact | Confidence | Message |
---|---|---|---|
25.0 | 50 | 50 | The following $user$ has reported a suspicious login activity. |
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
Reference
Test Dataset
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 | version: 1