Okta provides a trusted access management platform to secure every identity within an organization’s workforce or customer base. Panther can collect, normalize, and monitor Okta System Logs to help you identify suspicious activity in real time. Your normalized data is then retained to power future security investigations in a serverless data lake powered by Snowflake.
The Okta System Log records system events within your Okta instance and provides an audit trail to help users understand platform activity. Common security use cases for monitoring Okta logs include:
Panther’s integration for Okta is easy and fast to configure, allowing you to onboard system logs in just a few minutes. Simply select Okta from the list of pre-defined log sources, provide domain information for your Okta instance, and submit an Okta API token to the Panther console.
Once the log source setup process is complete, Panther will fetch Okta events by querying the Okta System Log API. Panther will query the System Log API every 1 minute. For more details on onboarding Okta logs or for supported log schema, you can view our Okta documentation here.
As Panther ingests Okta audit logs, they are parsed, normalized, and stored in a Snowflake security data lake. This allows security teams to write detections, identify anomalies, and conduct investigations on logs in the context of days, weeks, or months of data.
Panther applies normalization fields to all log records, which standardizes names for attributes and allows you to correlate data across all log sources - not just Okta. You can use Panther’s various search tools - such as Data Explorer, Indicator Search, and Query Builder - to investigate your normalized logs for suspicious activity or vulnerabilities. For more on querying and searching normalized log data in Panther, check out our documentation on Investigations & Search.
With Panther, your team won’t be confined to rigid detection rules as seen in most legacy SIEMs. Panther is architected around detection-as-code principles, giving you the ability to write Python to define detection logic and to integrate external systems like version control and CI/CD pipelines into your detection engineering processes. This results in powerful, flexible, and reusable scripting of detection logic for your security team.
A number of pre-built detections are available by default in Panther, offering users immediate value for monitoring common IoCs and threats. You can explore our built-in detection coverage for Okta logs here.
Panther generates alerts when your detection rules or policies are triggered, and integrates with a variety of alert destinations to allow for easy access and management of alerts for your security team. Alerts can also be sent to alert context or SOAR platforms for more remediation options.
Alerts are categorized by different severity levels: Info, Low, Medium, High, and Critical. Security teams have the options to dynamically assign severity based on specific log event attributes.
If you have any questions about configuring or monitoring Okta logs in Panther, we’re here to help. All customers have access to our technical support team via a dedicated Slack channel, email, or in-app messenger.
You can view our detailed documentation on configuring and monitoring Okta logs here, or customers can join the Panther Community to share best practices or custom detections for monitoring Okta.
With Panther, you don’t have to accept limitations with SIEM detections, waste time and effort on operational overhead, or pay skyrocketing costs to keep up with the growth of cloud app data. Panther was founded by a team of veteran security practitioners who struggled with legacy SIEM challenges first-hand, and built an intuitive, cloud-native platform to solve them.
Panther is a cloud-native SIEM built for security operations at scale, offering powerful detection-as-code, intuitive security workflows, and actionable real-time alerts to keep up with the needs of today’s security teams. For a powerful, practical, and scalable SIEM solution for Okta, request a demo today.
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