Page 104 - Cyber Defense eMagazine September 2025

The Solution: An Integrated Approach to Machine Learning Operations (MLOps)

Imagine a world where the system would not let you promote a software release into production unless
it had passed all the tests (yes, I mean all the tests!). Exceptions could be recorded, tracked, and the
approvals documented in a single system.

Continuous Compliance Automation offers the solution. By applying controls and enforcing regulations
from beginning to end—from initial design to production release—we can eliminate the need for point-in-
time checks (i.e., audits). We integrate evidence from all your tools and procedures into a single data
source of truth, enabling everyone (developers, AppSec teams, security personnel, auditors, and
business owners) to see how the software complies with their specific regulatory requirements. This is
also a great benefit to ML engineers and data scientists, who can have peace of mind knowing that
they’re working with trusted models that have been vetted and conform with policy.

Implementing an approach that combines consistent tools and processes with a reliable path to
production creates a trusted environment that automatically generates information demonstrating
adherence to regulations and compliance obligations. As some of my fellow CISOs are beginning to
recognize, the most effective way to integrate security is to automate it through a methodical process.

Leveraging JFrog for Trusted AI/ML Development

AI, ML, LLM, and GenAI are here to stay. With the upcoming challenge of agentic AI, we need to build
the foundations of a secure approach to managing risk. This includes addressing traditional concerns like
vulnerabilities, personally identifiable information (PII), and business risks, while also developing the
flexibility to adjust to new demands as the world confronts emerging threats generated by this new
intelligence landscape. Start today, since tomorrow won’t wait.

In the JFrog Platform, we have a full solution for AI/ML model lifecycle management, which provides a
trusted environment for AI/ML developers to build and fine-tune models. With JFrog ML, you gain
governance over your ML development, with end-to-end visibility and control into AI model deployment,

Cyber Defense eMagazine – September 2025 Edition 104
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