Open AI Framework for Cybersecurity Providers

NVIDIA Morpheus is an open application framework that enables cybersecurity developers to create optimized AI pipelines for filtering, processing and classifying large volumes of real-time data. Developer kits in AWS, from Red Hat, or running on NVIDIA-certified servers support pre-trained AI models, allowing customers to continuously inspect network and server telemetry at scale. Bringing a new level of information security to data centers, Morpheus enables dynamic protection, real-time telemetry, and adaptive defenses for detecting and remediating cybersecurity threats.

NVIDIA Morpheus is available for download on NVIDIA NGC, or develop with Morpheus now on GitHub.

Download on NGC Develop on Github

Leverage AI to achieve up to 200x improved cybersecurity threat detection performance. Discover NVIDIA Morpheus AI framework.

AI-Based, Real-Time Threat Detection at Scale

With Morpheus, enterprises can observe all their data across their entire network and apply Al inferencing and real-time monitoring to all necessary packets and data streams - at a scale previously impossible to achieve.

Analyze Behavior of Every User

Enhancements to NVIDIA Morpheus allow developers to implement workflows that uniquely fingerprint every user, service, account, and machine across the enterprise data center – employing unsupervised learning to flag when user and machine activity patterns shift.

Detect Cybersecurity Threats Instantly

Morpheus gives security teams complete visibility into security threats by bringing together unmatched AI processing with real-time monitoring of every server and packet throughout the data center.


Quick Development and Deployment

Morpheus integrates tools to make it easier for you to build cybersecurity solutions. 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

You can deploy your own models using common deep learning frameworks. Or use one of NVIDIA’s pretrained and tested models to get a jump-start in building applications to identify leaked sensitive information, detect malware or fraud, do network mapping, flag user behavior changes, or identify errors via logs.

Real-Time Telemetry

Morpheus can receive rich, real-time network telemetry from every NVIDIA® BlueField® DPU-accelerated server and NVIDIA DOCA™-based application, including Telemetry Flow Inspector and App Shield 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.

DPU Ready

NVIDIA BlueField data processing unit (DPU) offloads, accelerates, and isolates critical data center infrastructure functions. BlueField DPU also extends static security logging to a sophisticated dynamic real-time telemetry model that evolves with new policies and threat intelligence.

Framework Architecture

Built on a number of new and existing technologies, Morpheus provides a framework to perform real-time inference across massive amounts of cybersecurity data.

Framework Architecture
Morpheus can send and receive telemetry from multiple sources, including the BlueField DPU, allowing continuous, real-time, and variable feedback that can affect policies, rewrite rules, adjust sensing, and other actions.

Key AI Cybersecurity Capabilities

Pre-trained Models

Customize for Your Applications

Digital Fingerprinting

Uniquely fingerprint every user, service, account, and machine across the enterprise data center and then employ unsupervised learning to flag when user and machine activity patterns shift.

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Integrate Existing Deployments and Code

Easily integrate your own already trained models with Morpheus for inferencing. Swap in newer models without interruption to your pipeline. Morpheus also effortlessly integrates with existing SIEM, SOAR, visualization, or graph tools.

Classify Leaked Sensitive Data

Find and classify leaked credentials, keys, passwords, credit card numbers, bank account numbers, and more.

Common Formats Supported

Use common deep learning frameworks like ONNX, PyTorch, TensorFlow, and NVIDIA TensorRT™ with support from the Triton Inference Engine. Forest inference is also supported via the RAPIDS Forest Inference Library (FIL).

Profile Behavior Anomalies

Catch anomalies by profiling behaviors to spot malicious code or misconfigurations. Make use of various types of logs to target specific use cases.

Monitor Model Performance

Get real-time metrics on model performance with integrated MLOps.

Detect Phishing Attempts

Use this natural language processing (NLP) AI model to analyze entire raw emails to classify them into ham, spam, or phishing categories automatically.

Fine-Tuning Scripts

Increase accuracy and reduce false positives by using base scripts that can be customized for your environment. Give your data scientists and experts a head-start on customized AI for your unique applications.

Identify Errors in Server Logs

Scan server logs with this NLP-based predictive maintenance model to identify errors and potential failures that wouldn’t be flagged with existing log filtering rules.

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Get hands-on experience using Morpheus by registering for the free, 1-hour DLI course: Sensitive Information Detection with Morpheus.

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