LogoLogo
Knowledge BaseCommunityRelease NotesRequest Demo
  • Overview
  • Quick Start
    • Onboarding Guide
  • Data Sources & Transports
    • Supported Logs
      • 1Password Logs
      • Apache Logs
      • AppOmni Logs
      • Asana Logs
      • Atlassian Logs
      • Auditd Logs
      • Auth0 Logs
      • AWS Logs
        • AWS ALB
        • AWS Aurora
        • AWS CloudFront
        • AWS CloudTrail
        • AWS CloudWatch
        • AWS Config
        • AWS EKS
        • AWS GuardDuty
        • AWS Security Hub
        • Amazon Security Lake
        • AWS S3
        • AWS Transit Gateway
        • AWS VPC
        • AWS WAF
      • Azure Monitor Logs
      • Bitwarden Logs
      • Box Logs
      • Carbon Black Logs
      • Cisco Umbrella Logs
      • Cloudflare Logs
      • CrowdStrike Logs
        • CrowdStrike Falcon Data Replicator
        • CrowdStrike Event Streams
      • Docker Logs
      • Dropbox Logs
      • Duo Security Logs
      • Envoy Logs
      • Fastly Logs
      • Fluentd Logs
      • GCP Logs
      • GitHub Logs
      • GitLab Logs
      • Google Workspace Logs
      • Heroku Logs
      • Jamf Pro Logs
      • Juniper Logs
      • Lacework Logs
        • Lacework Alert Channel Webhook
        • Lacework Export
      • Material Security Logs
      • Microsoft 365 Logs
      • Microsoft Entra ID Audit Logs
      • Microsoft Graph Logs
      • MongoDB Atlas Logs
      • Netskope Logs
      • Nginx Logs
      • Notion Logs
      • Okta Logs
      • OneLogin Logs
      • Orca Security Logs (Beta)
      • Osquery Logs
      • OSSEC Logs
      • Proofpoint Logs
      • Push Security Logs
      • Rapid7 Logs
      • Salesforce Logs
      • SentinelOne Logs
      • Slack Logs
      • Snowflake Audit Logs (Beta)
      • Snyk Logs
      • Sophos Logs
      • Sublime Security Logs
      • Suricata Logs
      • Sysdig Logs
      • Syslog Logs
      • Tailscale Logs
      • Teleport Logs
      • Tenable Vulnerability Management Logs
      • Thinkst Canary Logs
      • Tines Logs
      • Tracebit Logs
      • Windows Event Logs
      • Wiz Logs
      • Zeek Logs
      • Zendesk Logs
      • Zoom Logs
      • Zscaler Logs
        • Zscaler ZIA
        • Zscaler ZPA
    • Custom Logs
      • Log Schema Reference
      • Transformations
      • Script Log Parser (Beta)
      • Fastmatch Log Parser
      • Regex Log Parser
      • CSV Log Parser
    • Data Transports
      • HTTP Source
      • AWS Sources
        • S3 Source
        • CloudWatch Logs Source
        • SQS Source
          • SNS Source
        • EventBridge
      • Google Cloud Sources
        • Cloud Storage (GCS) Source
        • Pub/Sub Source
      • Azure Blob Storage Source
    • Monitoring Log Sources
    • Ingestion Filters
      • Raw Event Filters
      • Normalized Event Filters (Beta)
    • Data Pipeline Tools
      • Chronosphere Onboarding Guide
      • Cribl Onboarding Guide
      • Fluent Bit Onboarding Guide
        • Fluent Bit Configuration Examples
      • Fluentd Onboarding Guide
        • General log forwarding via Fluentd
        • MacOS System Logs to S3 via Fluentd
        • Syslog to S3 via Fluentd
        • Windows Event Logs to S3 via Fluentd (Legacy)
        • GCP Audit to S3 via Fluentd
      • Observo Onboarding Guide
      • Tarsal Onboarding Guide
    • Tech Partner Log Source Integrations
  • Detections
    • Using Panther-managed Detections
      • Detection Packs
    • Rules and Scheduled Rules
      • Writing Python Detections
        • Python Rule Caching
        • Data Models
        • Global Helper Functions
      • Modifying Detections with Inline Filters (Beta)
      • Derived Detections (Beta)
        • Using Derived Detections to Avoid Merge Conflicts
      • Using the Simple Detection Builder
      • Writing Simple Detections
        • Simple Detection Match Expression Reference
        • Simple Detection Error Codes
    • Correlation Rules (Beta)
      • Correlation Rule Reference
    • PyPanther Detections (Beta)
      • Creating PyPanther Detections
      • Registering, Testing, and Uploading PyPanther Detections
      • Managing PyPanther Detections in the Panther Console
      • PyPanther Detections Style Guide
      • pypanther Library Reference
      • Using the pypanther Command Line Tool
    • Signals
    • Policies
    • Testing
      • Data Replay (Beta)
    • Framework Mapping and MITRE ATT&CK® Matrix
  • Cloud Security Scanning
    • Cloud Resource Attributes
      • AWS
        • ACM Certificate
        • CloudFormation Stack
        • CloudWatch Log Group
        • CloudTrail
        • CloudTrail Meta
        • Config Recorder
        • Config Recorder Meta
        • DynamoDB Table
        • EC2 AMI
        • EC2 Instance
        • EC2 Network ACL
        • EC2 SecurityGroup
        • EC2 Volume
        • EC2 VPC
        • ECS Cluster
        • EKS Cluster
        • ELBV2 Application Load Balancer
        • GuardDuty Detector
        • GuardDuty Detector Meta
        • IAM Group
        • IAM Policy
        • IAM Role
        • IAM Root User
        • IAM User
        • KMS Key
        • Lambda Function
        • Password Policy
        • RDS Instance
        • Redshift Cluster
        • Route 53 Domains
        • Route 53 Hosted Zone
        • S3 Bucket
        • WAF Web ACL
  • Alerts & Destinations
    • Alert Destinations
      • Amazon SNS Destination
      • Amazon SQS Destination
      • Asana Destination
      • Blink Ops Destination
      • Custom Webhook Destination
      • Discord Destination
      • GitHub Destination
      • Google Pub/Sub Destination (Beta)
      • Incident.io Destination
      • Jira Cloud Destination
      • Jira Data Center Destination (Beta)
      • Microsoft Teams Destination
      • Mindflow Destination
      • OpsGenie Destination
      • PagerDuty Destination
      • Rapid7 Destination
      • ServiceNow Destination (Custom Webhook)
      • Slack Bot Destination
      • Slack Destination (Webhook)
      • Splunk Destination (Beta)
      • Tines Destination
      • Torq Destination
    • Assigning and Managing Alerts
      • Managing Alerts in Slack
    • Alert Runbooks
      • Panther-managed Policies Runbooks
        • AWS CloudTrail Is Enabled In All Regions
        • AWS CloudTrail Sending To CloudWatch Logs
        • AWS KMS CMK Key Rotation Is Enabled
        • AWS Application Load Balancer Has Web ACL
        • AWS Access Keys Are Used Every 90 Days
        • AWS Access Keys are Rotated Every 90 Days
        • AWS ACM Certificate Is Not Expired
        • AWS Access Keys not Created During Account Creation
        • AWS CloudTrail Has Log Validation Enabled
        • AWS CloudTrail S3 Bucket Has Access Logging Enabled
        • AWS CloudTrail Logs S3 Bucket Not Publicly Accessible
        • AWS Config Is Enabled for Global Resources
        • AWS DynamoDB Table Has Autoscaling Targets Configured
        • AWS DynamoDB Table Has Autoscaling Enabled
        • AWS DynamoDB Table Has Encryption Enabled
        • AWS EC2 AMI Launched on Approved Host
        • AWS EC2 AMI Launched on Approved Instance Type
        • AWS EC2 AMI Launched With Approved Tenancy
        • AWS EC2 Instance Has Detailed Monitoring Enabled
        • AWS EC2 Instance Is EBS Optimized
        • AWS EC2 Instance Running on Approved AMI
        • AWS EC2 Instance Running on Approved Instance Type
        • AWS EC2 Instance Running in Approved VPC
        • AWS EC2 Instance Running On Approved Host
        • AWS EC2 Instance Running With Approved Tenancy
        • AWS EC2 Instance Volumes Are Encrypted
        • AWS EC2 Volume Is Encrypted
        • AWS GuardDuty is Logging to a Master Account
        • AWS GuardDuty Is Enabled
        • AWS IAM Group Has Users
        • AWS IAM Policy Blocklist Is Respected
        • AWS IAM Policy Does Not Grant Full Administrative Privileges
        • AWS IAM Policy Is Not Assigned Directly To User
        • AWS IAM Policy Role Mapping Is Respected
        • AWS IAM User Has MFA Enabled
        • AWS IAM Password Used Every 90 Days
        • AWS Password Policy Enforces Complexity Guidelines
        • AWS Password Policy Enforces Password Age Limit Of 90 Days Or Less
        • AWS Password Policy Prevents Password Reuse
        • AWS RDS Instance Is Not Publicly Accessible
        • AWS RDS Instance Snapshots Are Not Publicly Accessible
        • AWS RDS Instance Has Storage Encrypted
        • AWS RDS Instance Has Backups Enabled
        • AWS RDS Instance Has High Availability Configured
        • AWS Redshift Cluster Allows Version Upgrades
        • AWS Redshift Cluster Has Encryption Enabled
        • AWS Redshift Cluster Has Logging Enabled
        • AWS Redshift Cluster Has Correct Preferred Maintenance Window
        • AWS Redshift Cluster Has Sufficient Snapshot Retention Period
        • AWS Resource Has Minimum Number of Tags
        • AWS Resource Has Required Tags
        • AWS Root Account Has MFA Enabled
        • AWS Root Account Does Not Have Access Keys
        • AWS S3 Bucket Name Has No Periods
        • AWS S3 Bucket Not Publicly Readable
        • AWS S3 Bucket Not Publicly Writeable
        • AWS S3 Bucket Policy Does Not Use Allow With Not Principal
        • AWS S3 Bucket Policy Enforces Secure Access
        • AWS S3 Bucket Policy Restricts Allowed Actions
        • AWS S3 Bucket Policy Restricts Principal
        • AWS S3 Bucket Has Versioning Enabled
        • AWS S3 Bucket Has Encryption Enabled
        • AWS S3 Bucket Lifecycle Configuration Expires Data
        • AWS S3 Bucket Has Logging Enabled
        • AWS S3 Bucket Has MFA Delete Enabled
        • AWS S3 Bucket Has Public Access Block Enabled
        • AWS Security Group Restricts Ingress On Administrative Ports
        • AWS VPC Default Security Group Restricts All Traffic
        • AWS VPC Flow Logging Enabled
        • AWS WAF Has Correct Rule Ordering
        • AWS CloudTrail Logs Encrypted Using KMS CMK
      • Panther-managed Rules Runbooks
        • AWS CloudTrail Modified
        • AWS Config Service Modified
        • AWS Console Login Failed
        • AWS Console Login Without MFA
        • AWS EC2 Gateway Modified
        • AWS EC2 Network ACL Modified
        • AWS EC2 Route Table Modified
        • AWS EC2 SecurityGroup Modified
        • AWS EC2 VPC Modified
        • AWS IAM Policy Modified
        • AWS KMS CMK Loss
        • AWS Root Activity
        • AWS S3 Bucket Policy Modified
        • AWS Unauthorized API Call
    • Tech Partner Alert Destination Integrations
  • Investigations & Search
    • Search
      • Search Filter Operators
    • Data Explorer
      • Data Explorer SQL Search Examples
        • CloudTrail logs queries
        • GitHub Audit logs queries
        • GuardDuty logs queries
        • Nginx and ALB Access logs queries
        • Okta logs queries
        • S3 Access logs queries
        • VPC logs queries
    • Visualization and Dashboards
      • Custom Dashboards (Beta)
      • Panther-Managed Dashboards
    • Standard Fields
    • Saved and Scheduled Searches
      • Templated Searches
        • Behavioral Analytics and Anomaly Detection Template Macros (Beta)
      • Scheduled Search Examples
    • Search History
    • Data Lakes
      • Snowflake
        • Snowflake Configuration for Optimal Search Performance
      • Athena
  • PantherFlow (Beta)
    • PantherFlow Quick Reference
    • PantherFlow Statements
    • PantherFlow Operators
      • Datatable Operator
      • Extend Operator
      • Join Operator
      • Limit Operator
      • Project Operator
      • Range Operator
      • Sort Operator
      • Search Operator
      • Summarize Operator
      • Union Operator
      • Visualize Operator
      • Where Operator
    • PantherFlow Data Types
    • PantherFlow Expressions
    • PantherFlow Functions
      • Aggregation Functions
      • Date/time Functions
      • String Functions
      • Array Functions
      • Math Functions
      • Control Flow Functions
      • Regular Expression Functions
      • Snowflake Functions
      • Data Type Functions
      • Other Functions
    • PantherFlow Example Queries
      • PantherFlow Examples: Threat Hunting Scenarios
      • PantherFlow Examples: SOC Operations
      • PantherFlow Examples: Panther Audit Logs
  • Enrichment
    • Custom Lookup Tables
      • Creating a GreyNoise Lookup Table
      • Lookup Table Examples
        • Using Lookup Tables: 1Password UUIDs
      • Lookup Table Specification Reference
    • Identity Provider Profiles
      • Okta Profiles
      • Google Workspace Profiles
    • Anomali ThreatStream
    • IPinfo
    • Tor Exit Nodes
    • TrailDiscover (Beta)
  • Panther AI (Beta)
    • Managing Panther AI Response History
  • System Configuration
    • Role-Based Access Control
    • Identity & Access Integrations
      • Azure Active Directory SSO
      • Duo SSO
      • G Suite SSO
      • Okta SSO
        • Okta SCIM
      • OneLogin SSO
      • Generic SSO
    • Panther Audit Logs
      • Querying and Writing Detections for Panther Audit Logs
      • Panther Audit Log Actions
    • Notifications and Errors (Beta)
      • System Errors
    • Panther Deployment Types
      • SaaS
      • Cloud Connected
        • Setting Up a Cloud Connected Panther Instance
      • Legacy Configurations
        • Snowflake Connected (Legacy)
        • Customer-configured Snowflake Integration (Legacy)
        • Self-Hosted Deployments (Legacy)
          • Runtime Environment
  • Panther Developer Workflows
    • Panther Developer Workflows Overview
    • Using panther-analysis
      • Public Fork
      • Private Clone
      • Panther Analysis Tool
        • Install, Configure, and Authenticate with the Panther Analysis Tool
        • Panther Analysis Tool Commands
        • Managing Lookup Tables and Enrichment Providers with the Panther Analysis Tool
      • CI/CD for Panther Content
        • Deployment Workflows Using Panther Analysis Tool
          • Managing Panther Content via CircleCI
          • Managing Panther Content via GitHub Actions
        • Migrating to a CI/CD Workflow
    • Panther API
      • REST API (Beta)
        • Alerts
        • Alert Comments
        • API Tokens
        • Data Models
        • Globals
        • Log Sources
        • Queries
        • Roles
        • Rules
        • Scheduled Rules
        • Simple Rules
        • Policies
        • Users
      • GraphQL API
        • Alerts & Errors
        • Cloud Account Management
        • Data Lake Queries
        • Log Source Management
        • Metrics
        • Schemas
        • Token Rotation
        • User & Role Management
      • API Playground
    • Terraform
      • Managing AWS S3 Log Sources with Terraform
      • Managing HTTP Log Sources with Terraform
    • pantherlog Tool
    • Converting Sigma Rules
    • MCP Server (Beta)
  • Resources
    • Help
      • Operations
      • Security and Privacy
        • Security Without AWS External ID
      • Glossary
      • Legal
    • Panther System Architecture
Powered by GitBook
On this page
  • Overview
  • Where to use PantherFlow
  • How a PantherFlow query works
  • Example
  • Limitations of PantherFlow
  • Best practices when using PantherFlow

Was this helpful?

PantherFlow (Beta)

PantherFlow is Panther's pipelined query language

PreviousAthenaNextPantherFlow Quick Reference

Last updated 28 days ago

Was this helpful?

Overview

PantherFlow is in open beta starting with Panther version 1.110, and is available to all customers. Please share any bug reports and feature requests with your Panther support team.

PantherFlow is Panther's pipelined query language. It's designed to be simple to understand, yet powerful and expressive.

Use PantherFlow to explore and analyze your data in Panther. With its and , you can perform a variety of data operations, such as filtering, transformations, and aggregations—in addition to as a bar or line chart. PantherFlow is schema-flexible, meaning you can seamlessly search across multiple data sources (including those with different schemas) in a single query.

PantherFlow queries use pipes (|) to delineate data operations, which are processed sequentially. This means the output of a query's first operator is passed as the input to the second operator, and so on. See an example query below:

panther_logs.public.okta_systemlog
| where p_event_time > time.ago(1d)
| search 'doug'
| summarize agg.count() by eventType 

Where to use PantherFlow

Use PantherFlow to query data in Search. .

To assist your query writing, the PantherFlow code editor in Search has autocomplete, error underlining, hover tooltips, inlay hints, and function signature assistance.

If your PantherFlow query specifies a database/table, the in the upper-right corner of the Search page are ignored.

If your PantherFlow query does not specify a database/table, the database, table, and date range filters are all applied. In this scenario, if your PantherFlow query includes a date/time range (with a | where p_event_time ... statement), both date/time ranges are applied—i.e., returned data must fall within the date/time range set in both the date range filter and the range defined by the | where p_event_time ... statement.

How a PantherFlow query works

Example

Let's explore the following PantherFlow query:

panther_logs.public.aws_alb
| where p_event_time > time.ago(1d)
| sort p_event_time
| limit 10

In short, this query reads data from the aws_alb table, filters out events that occurred before the last day, sorts remaining events by time, and returns the first 10 events.

Let's take a deeper look at each line:

  1. panther_logs.public.aws_alb

    • This statement identifies the data source.

    • This query is reading from the panther_logs.public.aws_alb table. If the query contained only this line, all data in the table would be returned.

  2. | where p_event_time > time.ago(1d)

    • This query is requesting data where the p_event_time field value is greater than the time one day ago. In other words, it's asking for events that occurred within the last day. The time.ago() function subtracts from the current time, and its argument (1d) is a timestamp constant representing one day.

  3. | sort p_event_time

  4. | limit 10

    • This query is requesting no more than 10 events.

See additional query examples:

Limitations of PantherFlow

  • In some cases, a PantherFlow query may run slower than an equivalent SQL query.

Best practices when using PantherFlow

To ensure your PantherFlow query results return as quickly as possible (and to minimize Snowflake costs arising from the search), it's recommended to follow these best practices:

  • Use the limit operator

    • Example: panther_logs.public.aws_alb | limit 100

  • Use a time range filter

    • Example: panther_logs.public.aws_alb | where p_event_time > time.ago(1d)

  • Use p_any fields

    • During log ingestion, Panther extracts common security indicators into p_any fields, which standardize attribute names across all data sources. The p_any fields are stored in optimized columns. It's recommended to query p_any fields instead of various differently named fields for multiple log types.

    • Example: panther_logs.public.aws_alb | '10.0.0.0' in p_any_ip_addresses

  • Use the project operator

    • Example: panther_logs.public.aws_alb | project targetIp, targetPort

  • Summarize results

    • Summaries execute faster than queries fetching full log records. Using a summary is especially helpful when you're investigating logs over a long period of time, or when you don't know how much data volume exists for the time range you're investigating.

    • Example: panther_logs.public.aws_alb | summarize count=agg.count() by targetIp

  • Filter data early

    • Filter data before performing expensive operations, such as summarize or join, rather than after.

    • Example:

      • Instead of: panther_logs.public.aws_alb | summarize agg.count() by actor | where actor != nil

      • Use: panther_logs.public.aws_alb | where actor != nil | summarize agg.count() by actor

  • Avoid the search operator, if possible

    • Example:

      • Instead of: | search 'alice'

      • Use: | where strings.contains(name, 'alice')

If your query is still running slowly after implementing the best practices above:

  • Check the number of returned rows to see how much data you're querying.

    • If it's a large amount of data, it is likely expected for it to take a while.

  • Reduce the time range you're querying.

  • Reach out to your Panther Support team for additional help.

The term "PantherFlow query" typically refers to a , which retrieves a dataset and returns it in some form (in contrast to a .) A tabular expression statement usually contains separated by pipes (|). Each operator performs some action on the data—i.e., filters or transforms it—before passing it on to the next operator. Operator order is important, as PantherFlow statements are read sequentially.

See an overview of PantherFlow syntax on , or explore syntax topics in more detail:

The takes an to filter the data.

The lets you order events by one or more field values.

This query orders data by p_event_time. Because the is descending, the most recent event will be returned first.

The defines how many events you'd like returned, at most.

While you can using PantherFlow in the Panther Console, it's not possible to:

Schedule a Saved Search (i.e., create a )

Create a Saved Search using PantherFlow in the developer workflow (i.e., by uploading a saved_query via the or by using the or APIs)

Aggregations (i.e., the ) do not show information on the .

In Search, the does not reflect fields that are added or removed when using operators like , , and .

The .

Use the to specify the maximum number of records your query will return.

Use the to filter by a time range (perhaps against p_event_time). A query with a time range filter will access fewer , which returns results faster.

Learn more about .

Learn more on .

A query without a retrieves all columns, which can slow down queries. When possible, use project to query only the fields you need to investigate.

Instead of querying the full data set, use the , which will execute faster and help you determine a narrower timeframe to query next.

Learn more about .

The can introduce slowness, and should be avoided unless necessary. If you know which column (or columns) might contain the text you'd like to search for, instead of searching across all columns in the specified database/table with search, use with .

PantherFlow Quick Reference
PantherFlow Statements
PantherFlow Operators
PantherFlow Data Types
PantherFlow Expressions
PantherFlow Functions
where operator
expression
sort operator
default sort order
limit operator
PantherFlow Example Queries
Scheduled Search Examples
Scheduled Search
Panther Analysis Tool
REST
GraphQL
limit operator
where operator
micro-partitions
Standard Fields
project operator
summarize operator
operators
functions
visualizing your results
operators
summarize operator
project
extend
summarize
search operator
where
available time functions here
available aggregation functions here
strings.contains()
tabular expression statement
let statement
visualize operator has its own limitations
Learn how to use PantherFlow in Search here
database, table, and date range filters
create a Saved Search
Search results histogram
Available Fields list