GitLab provides a web-based Git-repository platform with wiki, issue-tracking, and continuous integration and continuous deployment (CI/CD) functionality. Panther can collect, normalize, and monitor GitLab logs to help you identify suspicious activity within your GitLab environment in real time. Your normalized data is then retained to power future security investigations in a data lake powered by the cloud-native data platform, Snowflake.
Use Cases for GitLab Audit & API Logs
Panther is able to ingest both GitLab API and Audit logs, which track important events, including who performed a related action and when. Some common SIEM use cases for these log types include:
- Monitoring changes to group or project settings
- Identifying any failed requests from GitLab to Git repositories
- Monitoring API requests and information about integration activities
Onboarding GitLab Logs in Panther
Panther’s integration for GitLab is fast and easy to configure, allowing you to onboard GitLab logs in just a few minutes. Simply select GitLab from the list of pre-defined log sources, select your preferred data transport method (AWS S3 or SQS), and configure GitLab to push logs to your data transport source.
For more details on onboarding GitLab logs or for supported log schema, you can view our GitLab documentation here.
Parsing, Normalizing, & Analyzing Logs
As Panther ingests GitLab logs, they are parsed, normalized, and stored in a Snowflake security data lake. This allows you to build detections, identify anomalies, and conduct investigations in the context of days, weeks, or months of data.
Panther applies normalization fields to all log records, which standardizes names for attributes and empowers users to correlate data across all of your log sources. Panther’s various search tools - such as Query Builder, Data Explorer, and Indicator Search - allow you to investigate your normalized logs for suspicious activity or vulnerabilities. For more information on searching logs, check out our documentation on Investigations & Search.
Built-in and Easily Customizable Detections
With Panther, you aren’t confined to restrictive detections or proprietary languages as seen in many SIEM solutions. Panther is architected around detection-as-code principles, giving you the ability to write Python to build 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 detections for your security team.
Panther generates alerts when your detection rules or policies for GitLab are triggered, and integrates with a variety of alert destinations to allow for intuitive management of any alerts. Alerts can also be sent to alert context or SOAR platforms for more remediation options.
Alerts are categorized by five different severity levels: Info, Low, Medium, High, and Critical. Your security team has the ability to dynamically assign severity based on specific log event attributes.
If you have any questions about configuring or monitoring GitLab logs in Panther, our customer support team is here to help. All customers have access to support via a dedicated Slack channel, email, or in-app messenger.
You can view our documentation on configuring and monitoring GitLab logs here , or customers can sign up for the Panther Community to share best practices or custom detections for GitLab logs.
Replacing Traditional SIEM for GitLab
With Panther, your team doesn’t have to waste time and resources on operational overhead, pay excessive costs to keep up with the growth of cloud app data, or struggle with restrictive detection logic. Panther was founded by a team of security engineers who struggled with other SIEM solutions 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 flexible detection-as-code, intuitive security workflows, and actionable real-time alerts. If you’re searching for a seamless SIEM platform for GitLab, request a demo today.