JFrog for MLSecOps

Manage, Secure, and Deliver Trusted AI/ML Components
Unify MLOps and DevSecOps to bring AI/ML into
your software supply chain confidently.
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Organizations today have benefited from mature DevSecOps practices to achieve trusted software supply chains. However, when it comes to MLSecOps, technology leaders face issues identifying AI components in software in addition to ensuring ML model security, version control, rollback, and governance.

Overcome these challenges and accelerate your AI/ML initiatives by bringing mature DevOps and Security practices to your AI pipelines. The JFrog Platform - integrated with leading ML model hubs and development platforms - offers a comprehensive solution for securing and managing the versioned AI/ML models, software packages, data, and dependencies as a single entity, alongside all the other artifacts that make up your applications.

All Your AI/ML Components,
Secured in One Place

Create a common hub between Data Scientists, Developers, and DevSecOps teams with a single source of truth for
versioned, approved, and production-ready AI/ML assets.

Identify
Hidden AI Discover where AI/ML may be hiding in components and applications to map and control the usage of AI across your software supply chain.

Block Unapproved AI Components

Block Harmful
AI Components Detect and prevent malicious, vulnerable, and non-compliant ML packages from being used in your organization with automated policies.

ML Model Artifact Management

Manage Model Artifacts Comprehensively Manage all the artifacts and data that make up a model as a single entity alongside the components needed for it to run in production

Operationalize ML Components

Operationalize AI/ML
Components with Ease Ensure the right model versions are used at the right place and the right time with greater traceability and governance across the SDLC

Your Smart, Secure, Governed
Model Registry
More than a box to hold model files, JFrog provides advanced functionality needed to take proprietary and third-party components from AI/ML model development through to release.
  • Advanced model versioning that works for all stakeholders
  • Access controls and distribution gets models where needed
  • Remote model hosting for assured access to essential models
  • Model release bundling for trusted releases
  • Ecosystem integrations that control model development inputs and outputs
  • Trace AI/ML components across the SDLC
  • Malicious model detection and blocking
  • Model vulnerability and license scanning
  • Automated security and compliance policy enforcement
  • Advanced model versioning that works for all stakeholders
  • Access controls and distribution gets models where needed
  • Remote model hosting for assured access to essential models
  • Model release bundling for trusted releases
  • Ecosystem integrations that control model development inputs and outputs
  • Trace AI/ML components across the SDLC
  • Malicious model detection and blocking
  • Model vulnerability and license scanning
  • Automated security and compliance policy enforcement

Bring Trusted Models to Production, Fast

JFrog provides all the tools needed to deliver Al applications. Your Al developers
benefit from an opinionated, simplified solution that makes it easy to build a model
and bring it into production in a trusted way.

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Model Registry

Model Training

Model serving

Model Monitoring

Feature Store

Vector Store

Feature Vector Pipeline

Where Data Science and DevSecOps meet
Bring the right DevSecOps tools and processes to model development while allowing Data Scientists and ML Engineers to work in their preferred spaces. JFrog integrates natively across the AI/ML ecosystem and provides the client side SDKs and CLI to seamlessly integrate into ML model development workflows.
Explore JFrog Integrations
Explore JFrog Integrations

Guarantee the Right Components are Used Across Teams

Provide Data Science and ML teams with secure Python, C/C++, Images and other software components to use in
model development and a single place to manage training outputs, while making it simple for DevOps and
Developers to identify which versions of models to incorporate in production ready assets.

Benefit from
an Enterprise
Ready Platform
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True Universality
Bring the management of AI/ML models alongside your images, PyPI, CRAN, Conda, Conan, and 30+ additional software component types for a unified view of the software you’re building and releasing. Operate in self-hosted data centers, in the cloud, or across multiple public clouds for ultimate flexibility in where and how you build software.
Integrated Security
Protect your applications from hidden scripts and clever malicious behaviors with built-in detection of malicious models and license compliance within your chosen ML Model binaries. Continuous, built-in scanning fortifies your supply chain, blocks risk, and simplifies remediation.
Auditing and Traceability
Control how AI/ML components enter and advance across your organization with greater efficiency. Capture signed evidence of every action taken against immutable releases to get full traceability of every component and see where they’re used across your environments.
Proven Scale
The JFrog Platform is proven to meet the needs of the largest organizations in the world, handling petabytes of data across multiple sites without breaking a sweat. Your mission critical tools, components, and data are available and accessible wherever, whenever needed with trusted enterprise resilience.
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See how the JFrog Platform can help you take control
of AI/ML in your software supply chain

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Additional Resources

Integration
JFrog Integrates with AWS SageMaker
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Integration
JFrog Integrates with Qwak
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Integration
JFrog Integrates with Hugging Face
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Webinar
Building for the Future: DevSecOps in the Era of AI/ML Model Development with AWS
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Solution Sheet
ML Model Management with JFrog
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JFrog Platform
Explore the JFrog Software Supply Chain Platform
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