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Give an AI agent only the access needed for its current task. Check each route separately—connected apps, files, commands, internet destinations and control of your screen—then turn off unnecessary routes, narrow the remaining permissions and review consequential actions before they happen. One permission setting may not cover every way an agent can reach the same information.

What can an AI agent access?

“Agent access” is not one permission. Depending on the product, an agent may use connected services, read or change files, run commands, contact websites, or view and control applications on screen. Review the tools the agent can use as well as the data and accounts connected to it.

Access route What to check
Connected apps and accounts Which apps and accounts are enabled, and whether another agent feature can reach the same data.
Local files Which folders, projects or external directories are in scope, and whether sensitive files need separate authorization.
Commands and tools Whether the agent can run shell or terminal commands, use MCP servers, or invoke other tools.
Internet and websites Whether network access is available and, where supported, restricted to particular domains.
Visual computer use Whether the agent can see screen content, click, type or navigate apps that are open or logged in.

These routes can overlap. OpenAI cautions that disabling synced-app access in ChatGPT does not necessarily block access to the same information through separately enabled app features such as chat or deep research. Review all active routes, not just the integration you first notice. OpenAI’s ChatGPT agent documentation describes its app controls and this distinction.

How to restrict an agent safely

  1. Identify the task. Decide what the agent must do, which data it needs, and which actions it must be able to take. Avoid granting broad access “just in case.”
  2. Inventory enabled routes. Check connected apps and accounts, file or project access, terminal and other tools, browser or network access, and any visual computer-use capability. Switch off routes the task does not require.
  3. Narrow the scope. Prefer the one app, folder, project, domain or operation needed for the task over an entire home directory, mailbox, account or workspace. For example, a coding task may need a project folder and specific tools, not personal documents or email.
  4. Separate asking from enforcement. Approval prompts can require the agent to ask before an action; a sandbox can impose file or network boundaries on supported execution paths. Check which protections actually apply to the tool being used.
  5. Review high-impact actions. Before an agent sends, shares, deletes, purchases or changes settings, inspect the proposed action and the account or app it will affect. Stop if the target or consequence is unclear.
  6. Remove temporary access afterward. Disable integrations or permissions granted for a one-off task, and review connected apps periodically. If the agent used a sensitive logged-in site, follow that product’s guidance for ending or clearing the session.

What controls do specific products provide?

ChatGPT agent and workspace controls

ChatGPT workspace administrators can enable or disable agent mode, assign availability by role, manage available apps and request website blocking. The exact controls depend on workspace plan, administrator settings and rollout. OpenAI’s Agent Security and local work sync documentation distinguishes requirements, which members cannot override, from defaults, which set starting values within those limits. It also describes global and execution-environment settings, including filesystem permissions and sandboxing for supported local work.

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Cloud and local execution have distinct settings, so do not assume a policy for one governs the other. For local execution, mobile device management and legacy managed-device requirements take priority over Agent Security. Review the workspace’s enabled apps and other agent features together; blocking one synced-data route may not block another route to the same data.

Gemini in Android Studio

These controls apply to Gemini in the Android Studio developer environment, not to AI apps generally or to a single Android phone-wide agent setting. Android Studio’s permission categories include project files, external directories and sensitive data, Google Search and other domains, shell commands, and MCP servers. Its Agent Shell Sandbox limits unauthorized network access and filesystem writes unless consent is supplied. Sensitive files such as SSH keys and password files require separate authorization. Consult the Android Studio agent-permissions guide for the settings in your installed version; interface labels can change.

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Visual Studio Code

VS Code documents a terminal sandbox that can restrict filesystem paths and network access for terminal commands and their child processes. Where supported, network access can be limited to configured domains. Approval level and sandbox enforcement are separate: choosing a more permissive approval setting does not remove restrictions imposed by an enabled terminal sandbox. The VS Code trust and safety documentation labels the local terminal sandbox Preview on macOS, Linux and WSL2, and Experimental on Windows in the reviewed documentation. Check the current documentation and your platform before relying on it.

GitHub Copilot computer use

Computer use is an optional capability for visually interacting with desktop applications. When enabled, it can inspect accessible app content and screen context, click, type and navigate workflows. GitHub’s documentation identifies Accessibility and Screen Recording permissions on macOS. Changing interfaces, ambiguous instructions or unexpected on-screen content can lead to unintended actions, so review the target app and the result, especially when data or other people may be affected. Avoid persistent “Always allow” access for sensitive apps or apps with high-impact workflows. See GitHub’s computer-use documentation.

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Windows Copilot Actions preview

Microsoft describes an experimental Copilot Actions approach for Windows that is disabled by default in the preview described in its documentation. It uses a separate standard account and a contained agent workspace to limit visibility and access. This is a product-specific experimental approach, not a control every Windows user can rely on. Check the current Windows agentic security documentation for availability and requirements.

iPhone and iPad

iOS and iPadOS use app sandboxing and declared entitlements as part of Apple’s platform security model. Those protections are a layer of containment, not a complete permission checklist for a particular AI agent. Review the integrations and permissions exposed by the agent app and service you use; do not assume platform protections make that review unnecessary. Apple describes the platform model in its Apple Platform Security guide.

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How should organizations limit workplace agents?

For a workplace deployment, use a dedicated agent identity rather than a person’s broad account, assign scoped roles, and define clear boundaries around the tools the agent can call. Establish ownership and action logging, and check that downstream systems still enforce the intended permissions. Microsoft’s least-privilege guidance for Microsoft Entra Agent ID recommends scoped roles and tool boundaries. Apply the same review discipline to revoking access when an agent or task is no longer needed.

How can you compare agent permission controls?

Instead of labeling a product simply “secure” or “insecure,” compare the specific protections it offers:

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  • Access surface: Does it reach apps, local files, terminal commands, websites or the visible desktop?
  • Scope: Can you limit access by app, folder, project, domain, role or operation?
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For any configuration, verify which execution environment and tools the setting covers. A permission or sandbox in one product, environment or platform should not be assumed to protect another.

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