Zscaler extends Zero Trust platform to secure AI agents with new AI Broker and endpoint controls

Zscaler Claims Industry's First Complete Zero Trust Platform for Agentic AI

Zscaler unveiled a suite of products at Zenith Live 2026 in Las Vegas designed to secure autonomous AI agents, positioning itself as the first vendor to deliver a complete Zero Trust platform for agentic AI1

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. The announcement extends the company's Zero Trust Exchange platform to cover how AI agents connect to networks, reach enterprise data, and run on employee devices. CEO Jay Chaudhry framed agentic AI as the next major wave after cloud and mobile, warning that enterprises will soon face "dozens of AI agents for every employee," each running continuously and autonomously accessing enterprise systems1

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. Traditional security tools were designed around known human identities and predictable access patterns, but autonomous AI agents operate at machine speed, create ephemeral identities, spawn sub-agents, and exercise permissions in ways that legacy systems cannot fully see or control2

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AI Broker and Endpoint AI Security Target New Risk Plane

At the center of the launch are two products addressing what Chaudhry described as a new risk plane. Zscaler AI Broker secures agent-to-agent and Model Context Protocol communications, shipping with an integrated Agent Registry that lets organizations define what each agent is permitted to access2

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. The Broker tracks each agent's identity, purpose, and permitted data and actions, enabling granular policies such as restricting financial agents to specific systems or limiting customer-support agents' access to personally identifiable information1

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. Zscaler Endpoint AI Security targets AI threats on employee devices, reaching into browsers, extensions, plugins, and local AI tools that the company said legacy endpoint products were not built to inspect2

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. These capabilities detect and block behaviors such as malicious browser extensions acting as agents, unmanaged AI tools accessing sensitive files, and data exfiltration through AI assistants1

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Leveraging Existing Infrastructure for Securing AI Agents

Chaudhry told CRN that Zscaler estimates it already had 70 percent of the functionality necessary to expand its Zero Trust Exchange into the sphere of AI agent communications4

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. "We already solved most problems needed to secure agentic communication," he said. "We really had to do probably about 30 percent new work, and 70 percent we could leverage from what we have in place"4

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. The company processes 750 billion transactions per day across its global systems, a scale that Chaudhry argued few if any other vendors could replicate without far more investment of resources3

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. For enterprises that have already standardized on Zscaler for Zero Trust and Security Service Edge, this means they can onboard AI agents into the same fabric used today to connect users and applications rather than standing up a new, parallel AI security stack1

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AI Access Graph Maps Identity and Data Lineage

Zscaler also introduced AI Access Graph, a tool that maps how identities, applications, and data sources connect across an organization so security teams can spot and cut unnecessary access2

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. The technology comes from Zscaler's acquisition of Symmetry Systems in May for $175 million2

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. Powered by this acquisition, AI Access Graph enables organizations to understand and then enforce policies, reduce unnecessary access and risk, and track data lineage in real-time across every channel5

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. John Israel, Global CISO at KPMG, who joined as a guest speaker, noted that "having a unified, zero-trust framework to trace data lineage and govern agent-to-agent interactions is paramount to maintaining trust, compliance, and competitive advantage"5

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Building on AI Protect with Enhanced Governance

The announcements build on Zscaler AI Protect, which launched in January 20262

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. The company is adding the ability to discover embedded AI in software-as-a-service and internet traffic, identify agents and MCP servers running in public cloud, and scan agentic codebases for risk2

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. It's also expanding controls for sanctioned AI tools, with prompt extraction across more than 250 generative AI apps and support for the compliance application programming interfaces offered by Anthropic and OpenAI2

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. For teams building AI applications, Zscaler is adding red teaming for MCP servers, a standalone prompt hardening service, and compliance heat maps meant to strengthen governance across the development and runtime lifecycle2

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Partners See Competitive Advantage in Market Position

Zscaler partners told CRN that the company's combination of a broad customer base, massive data telemetry, and global system for securing communications between AI agents gives the vendor a substantial edge when it comes to securing agentic AI adoption3

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. "I think they're incredibly well-positioned, and we're seeing it in the market," said Tristan Tarpinian, vice president for national alliances at GuidePoint Security3

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. Meg Smith, vice president for strategic security partnerships at AHEAD, noted that "Zscaler and their trusted relationships—and the rate at which they've been innovating over the past two years—is an incredible advantage that they have in the ecosystem"3

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. The push reflects a wider scramble among security vendors to wrap controls around agentic AI before enterprises deploy it at scale, with rivals including Palo Alto Networks and Google rolling out their own agent security offerings over the past year2

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. Zscaler did not disclose pricing or general availability dates for the new products2

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