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.
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 …
Imagine your lead Software Engineer walks into your office and says, “Good news! I just deployed that critical update to production. I wrote the code on my personal laptop, didn’t run it through CI/CD, skipped the security scan, and just copied the files directly to the server with a USB drive.” You would fire them. …
Listen to a NotebookLM podcast version of the blog: When Anthropic announced Claude Code’s new security scanning capabilities, following the announcement of OpenAI’s Aardvark, it marked an important moment for the industry. For the first time, expert-level security review is becoming embedded directly into the act of writing code. Subtle, context-dependent vulnerabilities can now …
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, …
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 …
The rapid pace of AI innovation is driving new possibilities for every organization. Yet, for many, the journey from inception to reliable, production-ready AI applications is riddled with hidden challenges: proliferation of models, security blind spots, and a desperate need for consistent governance. You want to harness the power of AI, but not at the …
As software supply chains get more complex, your GRC initiatives become more critical. You need a deeper level of assurance that your software has gone through required processes as it moves toward release. The stakes are only getting higher; new software and AI regulations are gaining ground, and businesses that aren’t able to prove compliance …
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