of all code shipped to production today is AI-authored
GitClear
Your agents build software, connect to MCPs, use skills, and ship software at incredible speed. JFrog immunizes what your agents consume and controls how they build, so you can trust your agentic workforce.
of all code shipped to production today is AI-authored
GitClear
Growth of malicious packages and AI assets in the last three years
OpenSSF & JFrog Security Research
Enterprises have no governance framework for coding agents
Deloitte
A trusted agentic workforce is one where every artifact your agents consume, build, and ship is governed from a single source of truth. Models, MCP servers, skills, plugins, packages, and code are all part of the same supply chain, so trust can’t be bolted on from the outside. It has to be engineered into where software is built: immunize what agents consume before they write a line of code, heal what they build as they build it, and prove everything they ship.
Immunize your agents against untrusted AI assets. Every MCP server, skill, and plugin is vetted and governed at the pull, through the same controls your software already runs.
Every binary is scanned, prioritized by real exploitability, and remediated automatically, then released through the same controls as your human-written code, with logged evidence behind every action.
An agentic software supply chain is a software delivery pipeline where AI agents autonomously write, build, test, and deploy code with minimal human intervention. These agents pull packages, access models, and make deployment decisions at machine speed.
Governance is required to ensure every agent action produces artifacts that are verified, policy-compliant, and traceable from source to production. JFrog is the only platform that governs both sides of the agentic supply chain in a single source of truth, without gaps, without compromise, and without forcing your teams to stitch together a security story from disconnected point solutions.
JFrog AI Catalog automatically discovers every AI model, binary, and asset across your organization, including those adopted outside official procurement processes. Once discovered, each asset is inventoried, tagged, and brought under policy governance. Teams retain access to the tools they need while security and compliance teams gain full visibility and control.
The JFrog Platform generates cryptographic attestations, provenance records, and AI Bills of Materials (BOMs) that map to requirements in the EU AI Act, SOC 2, ISO 27001, and NIST SSDF. These compliance artifacts are embedded directly in every binary and model, creating an auditable chain of evidence from source to production.
Traditional scanning checks artifacts for known vulnerabilities after they are built. Engineered trust verifies integrity, provenance, and policy compliance at every pipeline step, producing cryptographic proof that each artifact is safe before it moves forward. The result is a continuous chain of evidence rather than a point-in-time scan.
JFrog connects to your existing agentic ecosystem instead of requiring you to adopt a new one. The JFrog MCP Server gives any MCP-compatible agent direct access to JFrog data and actions, like checking artifact status, running scans, or pulling governed packages. Native plugins extend this further into the coding agents your developers already use, such as Claude Code, Cursor, and VS Code, so governance is built into the environment. JFrog Skills package common workflows (security checks, release gates, compliance reviews) into reusable actions your agents can call directly.
Agent Immunization is JFrog’s multi-layered approach to controlling what coding agents consume, engineered into your supply chain instead of bolted around the agent. It works in four layers: intercept every request at the network so no pull escapes governance, vet each asset before the pull with the curation and scanning you already run, enforce approved-only assets inside the agent itself so it can reach nothing else, and give every agent a scoped, verifiable agent identity limited to what its task needs.