Overview
Documentation overview highlighting key features and benefits of Panther's cloud-native threat detection platform
Panther is a cloud-native threat detection platform that transforms terabytes of raw logs per day into a structured security data lake to power real-time detection, swift incident response, and thorough investigations.
With detection-as-code in Python and out-of-the-box integrations for dozens of critical log sources, Panther solves the challenges of security operations at scale.
A diagram showing how Panther works: It ingests and normalizes security logs then alerts your team of suspicious activity.
It works by normalizing security logs from various places and alerting your team when suspicious activity happens.

Benefits

  • Focus on security, not ops with a cloud-native architecture that eliminates the need to manage servers, storage and updates.
  • Detect threats immediately by analyzing logs as soon as they are ingested, giving you the fastest possible time to detection.
  • Answer security questions quickly with the ability to immediately query months of data in minutes and efficiently search for IoCs across all logs.
  • Reduce false positives with Python Detection-as-Code, and CI/CD workflows for creating, testing, and deploying detections.
  • Expedite incident response by adding dynamic context to alerts to power more efficient routing, triage, and automation.
  • Reduce SIEM costs dramatically while gaining lightning-fast query speeds, with an efficient, highly scalable data lake architecture.
Learn more about the advantages of running Panther instead of a traditional SIEM.

Key Features

  • Effortless Data Ingestion: Built-in support for common data transports such as S3, SQS, SNS, and out-of-the-box integrations for critical log sources like Okta, Duo, Slack, Google WorkSpaces, and more.
  • Log normalization: Logs are parsed and IoC fields like domains and IPs are normalized to support analysis, searches and correlations across all log types.
  • Detection-as-Code: Highly customizable Python-based detections, a built-in testing framework, and the ability to create detections directly in the Panther Console or with Panther Developer Workflows including the Panther Analysis Tool and CI/CD.
  • Security data lake: Normalized security data is aggregated in a high-performance, scalable, and cost-effective data lake capable of running queries over massive data sets in minutes using Data Explorer or Scheduled Queries.
  • Indicator Search: Query petabytes of data and find related activity based on attributes like usernames, emails, IPs, and more to tell the full story during an incident.
  • Detection packs: Built-in detections give customers a starting point to customize as needed. Provided by Panther to analyze key log sources and support common security and compliance needs.
  • Alert routing: Feed alerts into notification systems for triage, and include valuable context to enable hands-off response via automation platforms.

Getting Started

Follow the quick start guide to get your new Panther account up and running.
Last modified 1mo ago