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 or from Red Hat 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.

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The Morpheus “humans-as-machines, machines-as-humans” model enables creation of behavioral patterns and profiles for every account and interaction on a network, at a massive scale, helping to protect networks in a way never before possible. Apply for early access to try it now.

Find out how organizations are using AI-based cybersecurity solutions at NVIDIA GTC.

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.

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.


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.


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 data directly from the BlueField DPU, or other data sources, 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

Bring Your Own Model

Classify Leaked Sensitive Data

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

Integrate Existing Code

Easily integrate your existing models with Morpheus for inferencing. Swap in newer models without interruption to your pipeline.

Profile Behavior Anomalies

Catch anomalies by profiling behaviors to spot malicious code or misconfigurations. Specify which logs are used to target specific use cases.

Common Formats Supported

The Triton Inference Engine supports common deep learning (DL) frameworks like ONNX, PyTorch, TensorFlow, and TensorRT. Forest inference is also supported via RAPIDS FIL.

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.

Monitor Model Performance

Morpheus integrates Morpheus integrates Machine Learning Operations (MLOps) to provide real-time metrics on model performance.

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.

Fine-Tuning Scripts

Increase accuracy and reduce false positives by using base scripts that can be customized for your environment.


Aria cybersecurity solutions
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Booz | Allen | Hamilton
Red Hat

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