NVIDIA Morpheus is an open AI application framework that provides cybersecurity developers with a highly optimized AI framework and pre-trained AI capabilities that allow them to instantaneously inspect all IP traffic across their data center fabric. The Morpheus developer framework allows teams to build their own optimized pipelines that address cybersecurity and information security use cases. Bringing a new level of security to data centers, Morpheus provides development capabilities around dynamic protection, real-time telemetry, adaptive policies, and cyber defenses for detecting and remediating cybersecurity threats.
- Built on RAPIDS
Built on the RAPIDS™ libraries, deep learning frameworks, and NVIDIA Triton™ Inference Server, Morpheus simplifies the analysis of logs and telemetry to help detect and mitigate security threats.
- AI Cybersecurity Capabilities
Deploy your own models using common deep learning frameworks. Or get a jump-start in building applications to identify leaked sensitive information, detect malware, and identify errors via logs by using one of NVIDIA’s pre-trained and tested models.
- Real-Time Telemetry
Morpheus can receive rich, real-time network telemetry from every NVIDIA® BlueField® DPU-accelerated server in the data center without impacting performance. Integrating the framework into a third-party cybersecurity offering brings the world’s best AI computing to communication networks.
The NVIDIA BlueField Data Processing Unit (DPU) can be used as a telemetry agent for receiving critical data center communications into Morpheus. As an optional addition to Morpheus, BlueField DPU also extends static security logging to a sophisticated dynamic real-time telemetry model that evolves with new policies and threat intelligence.
Getting Started with Morpheus - Using pre-built Docker containers, building Docker containers from source, and fetching models and datasets
Morpheus CLI Overview - Brief overview of the command line interface
Building a Pipeline - Introduction to building a pipeline using the command line interface
Morpheus Examples - Example pipelines using both the Python API and command line interface
Pretrained Models - Pretrained models with corresponding training, validation scripts, and datasets
Developer Guides - Covers extending Morpheus with custom stages
Contributing to Morpheus - Covers building from source, making changes and contributing to Morpheus
Morpheus Cloud Deployment Guide - Kubernetes and cloud based deployments