Your agents are only as trustworthy as what they consume, build, and ship. JFrog governs every AI model, agent skill, MCP server, AI-generated code, and assembled artifact in a single source of truth.
Secure your entire agentic software supply chain so you can ship trusted software at your new speed.
Note: This blog was originally published in July 2024 and updated on an annual basis. It was most recently updated in April 2026. Regulatory compliance is a common and critical part of today’s rapidly evolving financial services landscape. One new regulation that EU financial institutions must adhere to is the Digital Operational Resilience Act (DORA), …
Proving compliance is a necessity, but in a world of tightening regulations, the path to compliance is currently paved with spreadsheets, screenshots, and manual attestations. We call this the “Audit Tax”, the millions of dollars and thousands of people hours spent not just integrating security, but on proving you are handling security. With the advent …
For years, the conversation around digital transformation in Southeast Asia focused on “getting to the cloud.” Today, that conversation has shifted. Our region is no longer just adopting the cloud; we are leapfrogging traditional development cycles by integrating AI and cloud-native architectures at a staggering pace. However, this acceleration has created a byproduct that many …
The software supply chain is no longer just about shipping code, it is about managing intelligence and risk. As DevOps, DevSecOps, DevGovOps and AI/ML practices converge into a single AI-driven and increasingly agentic delivery pipeline, the demands on development and security teams have reached a new level. The platform that once managed packages and artifacts …
In an AI-native world where Model Context Protocol (MCP) is the universal standard for AI connectivity, the security and governance stakes have never been higher. AI’s ability to take autonomous action through MCPs means that a single breach of an MCP server can grant attackers control over mission-critical enterprise systems, putting enterprises in an immediate …
In 2026, software development speed is an AI-solved problem. Yet, as AI-generated code volumes surge, organizations face a new kind of risk visibility gap. Developers are increasingly copying third-party snippets into their codebases—from both AI prompts and open-source software components—creating large security and compliance blind spots that lead to significant risks. While proven software composition …
In today’s AI rush, I’ve seen even the most disciplined organizations find it almost impossible to apply the hard-won lessons of DevOps and DevSecOps onto AI adoption. These organizations often feel forced to choose between moving fast and staying in control. As a result, they develop a “wait and see” approach to AI usage and …
When we first introduced the JFrog AI Catalog, it was our mission to provide the industry with a single system of record for governing the complex landscape of internal, open-source, and external commercial AI models. This foundational step was critical for enterprises to move from uncontrolled innovation to delivering AI with trust and confidence. However, …
Are you confident that you’re scanning for security vulnerabilities on all your software running in production? If this question makes you uncomfortable don’t worry. First, you’re not alone. Second – keep reading. Almost all security teams today face a massive challenge: they’re drowning in data but lack direction. They have an overwhelming amount of code …
Today’s software organizations can’t make tradeoffs between speed and trust – you need both to succeed. But juggling them is tough. Moving too fast can lead to security vulnerabilities and compliance issues, while moving too slow means your competitors beat you to market. This tension creates friction that slows down every release, a problem that …
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