As web browsers increasingly experiment with agentic AI features—tools that can take actions on a user’s behalf such as booking tickets or shopping—security concerns are becoming more prominent. These capabilities introduce new risks, including unintended actions, data exposure, or financial loss.

Google has outlined how it plans to manage those risks in Chrome, detailing a layered security approach designed to keep agentic actions aligned with user intent while limiting exposure to sensitive data. The company previewed Chrome’s agentic features in September and said they are expected to roll out in the coming months.

To ensure agentic tasks remain aligned with user intent, Google said it relies on a system of observer models. At the center of this approach is a User Alignment Critic, built using Gemini, which evaluates the action plan created by Chrome’s planner model.

If the critic determines that a proposed action does not serve the user’s original goal, it instructs the planner model to rethink its strategy. Importantly, Google emphasized that the critic model only reviews metadata about proposed actions—not the actual web content—reducing the risk of unnecessary data exposure.

To limit where agents can read or write data, Google introduced Agent Origin Sets, which define boundaries around trusted and untrusted web content, helping prevent agents from accessing untrustworthy sites.

Read-only origins allow the agent to consume relevant content, such as product listings on a shopping site, while excluding irrelevant elements like banner ads.

Read-write origins restrict where the agent can interact, such as clicking buttons or typing into specific fields.

This separation prevents agents from interacting with irrelevant or potentially malicious content, such as banner ads or unauthorized page elements. According to Google, the browser itself enforces these boundaries by preventing data outside approved origins from ever being sent to the model.

Google said it also monitors page navigation through an additional observer model that evaluates URLs before agents follow them. This safeguard is designed to prevent agents from navigating to harmful or model-generated URLs that could lead to phishing or malicious sites.

For high-risk actions, Google is keeping humans firmly in the loop. When an agent attempts to access sensitive websites—such as those involving banking or medical information—it must first request user approval.

Similarly, if a site requires a sign-in, Chrome asks for permission before using the built-in password manager. Google stated that agent models never have direct access to password data. Users are also prompted before actions like completing a purchase or sending messages.

Beyond consent controls, Google said it uses a prompt-injection classifier to detect attempts to manipulate agent behavior. The company is also testing Chrome’s agentic features against adversarial attacks developed by security researchers.

Other AI browser developers are taking similar steps. Earlier this month, Perplexity released an open-source content detection model aimed at preventing prompt-injection attacks targeting AI agents.

Q: What are agentic features in Chrome?
A: Agentic features allow Chrome to take actions on a user’s behalf—such as navigating websites, filling forms, booking tickets, or making purchases—based on a stated goal.

Q: Why do agentic browsers introduce new security risks?
A: Because agents can interact with websites and initiate actions, mistakes or malicious manipulation could result in data leaks, unauthorized access, or unintended financial transactions.

Q: How does Google ensure agent actions align with user intent?
A: Google uses a User Alignment Critic, powered by Gemini, to review planned actions and determine whether they serve the user’s stated goal before execution.

Q: Does Google’s AI have access to private web content or passwords?
A: No. Google stated that agent models do not have access to password data, and sensitive actions—such as logging into accounts or making purchases—require explicit user approval.

Q: What are Agent Origin Sets?
A: Agent Origin Sets restrict which parts of a website an agent can read from or write to, preventing interaction with untrusted or irrelevant content and reducing the risk of cross-origin data leaks.

Q: How does Chrome defend against prompt injection attacks?
A: Google uses a prompt-injection classifier and actively tests its agentic systems against adversarial attacks developed by security researchers.

Agentic browsers represent a fundamental change in how people interact with the internet—from issuing commands to delegating decisions. When a browser can act on your behalf, security failures are no longer abstract—they can translate directly into financial loss, privacy violations, or misuse of sensitive personal data.

Google’s approach highlights a broader industry reality: agentic AI cannot be deployed safely without strong guardrails, transparency, and human oversight. By layering observer models, restricting data access, and requiring user consent for high-risk actions, Chrome is signaling that autonomy must be earned—not assumed.

For users, this matters because trust will determine adoption. For developers and competitors, it raises the bar for what “safe by design” means in AI-powered browsers. And for the broader web ecosystem, it underscores that the future of browsing will depend as much on security architecture as on AI capability.

This focus on security is not unique to Google. Other companies building AI-powered browsers and agents are also reinforcing safeguards as these tools become more capable. Perplexity has introduced multiple security layers in its Comet browser and released BrowseSafe, an open-source model designed to detect prompt-injection attacks on real-world web pages. OpenAI has similarly described multi-layered protections across its browser-based and agentic products, including automated monitoring for prompt-injections, built-in guardrails, and required user approval for higher-risk actions. Together, these efforts point to a growing industry consensus: as AI agents move closer to everyday use, security and human oversight are becoming core requirements—not optional add-ons.

As AI agents take on more responsibility in everyday tasks, the real measure of progress will not be how much they can do—but how safely, transparently, and responsibly they act on our behalf.

Editor’s Note: This article was created by Alicia Shapiro, CMO of AiNews.com, with writing, image, and idea-generation support from ChatGPT, an AI assistant. However, the final perspective and editorial choices are solely Alicia Shapiro’s. Special thanks to ChatGPT for assistance with research and editorial support in crafting this article.