Gen Launches VPN for Agents and Norton AI Protection
Gen has launched two new security products targeting the emerging market of autonomous AI agents. The company announced VPN for Agents and expanded Norton AI Agent Protection within Norton 360, both components of its Agent Trust Hub platform. The products address security gaps that arise when AI agents read emails, manage financial workflows, execute code, and operate across sensitive accounts on behalf of users.
Traditional virtual private networks protect devices and networks, but they do not separate a user's traffic from an agent's traffic or control where agents connect and what they access. VPN for Agents uses what Gen describes as multi-tunnel technology, allowing agents to operate across different countries simultaneously. The product shields identity and location details to reduce tracking and profiling while working without software downloads or client setup.
According to the company's official press release, this represents the first consumer AI-native VPN built specifically for autonomous AI agents. The announcement came from Gen's newsroom on April 30, 2026. VPN for Agents is available now through the Gen Agent Trust Hub, with access tokens and setup instructions at ai.gendigital.com/agentvpn.
Norton AI Agent Protection has been built into Norton 360, Gen's consumer security platform. The tool monitors what supported AI agents do and where they connect, with blocking tools and prompts designed to intervene between an agent's decision and execution. The expanded protection adds checks before AI plugins, skills and tools are used, along with defences against prompt injection attacks. It also scans code and files that AI agents access or generate to detect malware and unsafe scripts before execution.
Support for Norton AI Agent Protection is currently limited to Windows customers using Claude Code, Cursor and OpenClaw. Mac support will follow, according to Gen. The New Zealand release forms part of a wider consumer strategy around AI safety, with Norton 360 used by tens of millions of customers worldwide.
Howie Xu, Chief AI Innovation Officer at Gen, outlined the company's position on the shift towards agent-based computing. "As people embrace AI agents and use them to manage more of their digital lives, they deserve security and privacy that keeps pace," Xu said. "Our VPN for Agents protects that activity in real time, and with Agent Protection embedded into Norton 360, we are giving millions of people the confidence to let AI work on their behalf, knowing every connection and action is secured."
The launch reflects a broader shift in the security market as software groups respond to the rise of autonomous AI systems. These systems are moving beyond chatbot functions into software development, online account management and the handling of sensitive personal and financial information. For security providers, this creates a new challenge. AI agents can be manipulated through malicious prompts, directed to unsafe websites, or given access to tools and data beyond what a user intended.
Existing consumer cyber products have largely been designed around device, network and identity protection for human users rather than software agents acting independently. Gen's Agent Trust Hub is intended to serve as a control point for that activity. According to the company, the platform combines verification, detection and communication security, and is being developed through work between Gen Threat Labs and Gen AI Foundry.
Gen AI Foundry is the group's internal unit for developing and scaling AI products, while Gen Threat Labs focuses on threat research and security technology. The new products extend Gen's trust framework across more of the AI agent workflow. In practical terms, that means monitoring agent behaviour, controlling network connections and screening the content and tools agents use before actions are carried out.
Unlike many AI security products focused on corporate systems, Gen is targeting consumer use cases in which individuals may rely on AI agents for routine personal tasks. That includes handling files, interacting with online services and processing sensitive information, all of which create opportunities for misuse if an agent is deceived or compromised. The company serves nearly 500 million users across more than 150 countries through brands including Norton, Avast, LifeLock and MoneyLion.
When you actually use Norton 360, the interface presents prompts that interrupt agent actions before they execute. You'll see a notification window appear on your screen when an agent attempts to access a new tool or plugin. The blocking mechanism doesn't just silently prevent access—it shows you what the agent is trying to do and gives you the option to approve or deny. This creates friction in the workflow (which some users will find annoying, but it's better than having your bank account drained by a compromised agent).
As consumer technology groups race to add more autonomous AI functions to everyday software, the security model around those tools is still taking shape. Gen's latest launch signals that established cyber companies now see AI agents as a distinct category requiring separate controls, rather than simply an extension of existing endpoint or network protection. The products extend Gen's trust framework across more of the AI agent workflow.
Independent reporting from Future Five corroborates the timeline and scope of the changes, noting the May 11, 2026 availability in New Zealand markets. The coverage confirms that VPN for Agents is available now, while Norton AI Agent Protection is available to Norton 360 customers on Windows using Claude Code, Cursor and OpenClaw.
The physical reality of this protection becomes apparent when you consider what happens during a typical agent session. An AI agent might need to access your email, check your calendar, and then book a flight. Each of those actions requires network connections, data access, and potentially third-party integrations. Without agent-specific controls, all of that traffic flows through the same VPN tunnel as your regular browsing, making it impossible to distinguish between your activity and the agent's activity.
VPN for Agents creates separate encrypted corridors for agent traffic, allowing different agents to operate from different geographic locations simultaneously. This matters when an agent needs to access region-specific services or when you want to prevent location-based tracking. The multi-tunnel technology means you're not stuck with a single exit point for all your agent operations.
Whether users actually pay for this protection remains the real question. Gen is betting that consumers will value the additional layer of security as AI agents take on more sensitive tasks. The company has positioned these products as essential infrastructure for the AI agent era, but adoption will depend on whether users perceive the risk as significant enough to warrant the investment.
Gen framed the products as part of a broader effort to create what it calls a trust layer for AI use. The question is whether that trust layer will be enough to prevent the inevitable security incidents that will occur as AI agents become more autonomous and powerful. Time will tell if this works, but at least now there's something between your data and a rogue agent trying to sell your information.
Artūras Malašauskas is an AI Systems Integrator with 20+ years of production-grade web engineering experience. He has designed, shipped, and scaled enterprise Python/PHP systems for logistics, SaaS, and public-sector clients. For the past year, he has focused exclusively on AI integrations: deploying open-source LLMs, building generative media pipelines (image, audio, video), and engineering multi-agent workflows for real production environments. His standard: reproducibility, security, cost-efficient inference—no vaporware. He documents and evaluates emerging AI tooling, separating verified capabilities from marketing noise. Technical editor at: muza-ai.eu, ai-verslas.lt, ai-naujinos.lt Connect on LinkedIn
Artūras Malašauskas is an AI Systems Integrator with 20+ years of production-grade web engineering experience. He has designed, shipped, and scaled enterprise Python/PHP systems for logistics, SaaS, and public-sector clients. For the past year, he has focused exclusively on AI integrations: deploying open-source LLMs, building generative media pipelines (image, audio, video), and engineering multi-agent workflows for real production environments. His standard: reproducibility, security, cost-efficient inference—no vaporware. He documents and evaluates emerging AI tooling, separating verified capabilities from marketing noise. Technical editor at: muza-ai.eu, ai-verslas.lt, ai-naujinos.lt
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