Web Access Firewall (WAF) is a service provided by Amazon Web Services that allows you to control how your protected resources respond to HTTP(S) web requests. This is done by creating Access Control Lists (ACLs), which can define rules to allow or deny traffic to and from your AWS resources, such as EC2 instances, subnets, or VPCs. Panther can collect, normalize, and monitor WAF Web ACL 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.
WAF Web ACL logs capture web access control list (ACL) traffic information, including when AWS WAF received a web request, detailed information about the request, and any details about the ACL rules that were matched. Some common security use cases for these logs include:
Panther supports ingesting WAF logs via an AWS S3 bucket. To pull WAF logs into Panther, simply select AWS WAF Web ACL from the list of predefined log sources in Panther, and configure an S3 bucket for data transport.
For more detailed steps on onboarding AWS WAF logs or for supported log schema, you can view our AWS WAF documentation here.
As Panther ingests WAF logs, they are parsed, normalized, and stored in a Snowflake security data lake. This allows security teams to write detections, detect 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 empowers users to correlate data across all log types. Panther’s search tools empower you to investigate your normalized logs for suspicious activity or vulnerabilities. For more on searching log data in Panther, check out our documentation on Investigations & Search.
With Panther, your team won’t be confined to restrictive detection rules as seen in most SIEM platforms. Panther is built with detection-as-code principles, allowing you to use Python to define detection logic and to integrate external systems like version control and CI/CD pipelines into your detection engineering workflows. This results in powerful, flexible, and reusable scripting of detections for your security team.
Panther fires 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 any alerts. Alerts can also be sent to alert context or SOAR platforms for more remediation options.
Alerts are grouped within five different severity levels: Info, Low, Medium, High, and Critical. Security teams have the option to dynamically assign severity level based on specific log event attributes.
If you have any questions about configuring or monitoring WAF 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 documentation on configuring and monitoring AWS WAF logs here, or customers can sign up for the Panther Community to share best practices or custom detections.
With Panther, security teams don’t have to pay skyrocketing costs to keep up with cloud data volume, struggle with restrictive detection logic, or waste resources on operational overhead. 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 flexible 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, flexible, and scalable SIEM solution for AWS environments, request a demo today.
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