To give an AI desktop agent access to only the files it needs, create a task-specific workspace, expose only the required inputs, make those inputs read-only whenever possible, and run the agent inside a genuine OS, container, microVM, or hosted sandbox when commands are untrusted. Treat network access, credentials, and integrations as separate permission paths: a narrow folder alone does not stop a process from reaching other host files or online services.
The most important distinction is simple: a selected workspace is often an instruction or mount, not a security boundary. Your setup is least-access only when the execution environment enforces the file, write, network, and credential limits you intended.
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A workspace is not automatically a security boundary
Many desktop agents ask you to choose a project folder, set a working directory, or change HOME. Those settings can help the agent find the right material, but they may not prevent the agent or a subprocess from opening other files.
The OpenAI Agents SDK documentation says its Unix-local client runs commands as processes on the host. On Linux, choosing a workspace, HOME, or current working directory does not restrict what those processes can access; ordinary host permissions still apply. In that mode, an agent that can execute shell commands may be able to read any file available to the host process, not just the folder you selected. See the Agents SDK sandbox clients documentation.
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OpenAI’s sandbox security documentation states: “Agent-generated code can access the files, credentials, and network available to its environment.” That sentence describes the effective boundary: the environment, not the prompt, determines what generated code can reach. A prompt saying “use only this folder” is useful guidance, but it is not enforcement.
Four different controls are often confused
- Selection: a UI folder picker or instruction tells the agent which files to use.
- Application permissions: the agent application may mediate file operations, but subprocesses or connected tools may have different access.
- OS enforcement: a platform sandbox or kernel policy can deny file operations outside an approved set.
- Isolation: a container, microVM, or hosted runtime gives the process a separate execution environment, with only explicitly mounted paths visible.
Use selection to reduce accidental browsing, then add enforcement when the files are sensitive or the agent can execute code. Do not describe a working directory as “isolated” unless the agent’s documentation explains what process boundary actually enforces it.
Build a least-access workspace before starting the agent
Prepare the data boundary first. The following sequence works for summarization, document review, coding assistance, and other tasks, while allowing the exact controls to vary by agent and operating system.
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1. Define the task and its data flows
Write down what the agent must read, what it must create, and whether it needs any external service. Separate inputs from outputs. For example, a review task might require three contracts as inputs and a new report as output; it does not require your entire Documents folder, source repository, browser profile, or cloud-drive root.
- List every input file or narrow directory actually needed.
- List the output formats and destination required.
- Decide whether network access is necessary at all.
- Identify tools such as shells, browser automation, sync clients, or MCP servers that may run alongside the agent.
2. Create a dedicated task folder
Copy or export only the required material into a new workspace, such as /task-workspace/input and /task-workspace/output. Keep unrelated personal files, repositories, SSH keys, password stores, API-token files, and cloud-sync roots outside it. Copying is safer than pointing the agent at a large existing directory because it gives you a concrete inventory to inspect.
For a recurring workflow, create a fresh workspace for each job or clean the old one before reuse. Remove temporary exports and intermediate files that could contain more information than the final deliverable. A narrow folder does not help if it contains a shortcut, mounted volume, symlink, or helper configuration that leads elsewhere; inspect those objects before exposure.
3. Mount or expose only the required paths
If the framework supports a manifest, volume list, or sandbox configuration, specify the input and output paths explicitly. The OpenAI sandbox guidance recommends mounting only the inputs an agent should use and reviewing artifacts before exporting them. Do not mount an entire home directory or broad project tree when a subdirectory is sufficient.
Use separate mounts for inputs and outputs when the runtime supports it. A read-only input mount prevents ordinary edits to the source material, while a dedicated output mount gives the agent somewhere to save results. Confirm whether the runtime follows symlinks, exposes parent directories, or automatically mounts configuration files; these behaviors can widen the visible path set.
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4. Make inputs read-only where possible
Summarization, extraction, and review normally need read access but not write access. Mark the input mount or directory read-only and grant write permission only to the output location. For coding tasks, consider a read-only source mount plus a separate writable build or scratch directory; this prevents an experiment from silently replacing the source tree.
Read-only storage limits modification, not necessarily disclosure. An agent can still copy readable information into an output file or send it over an allowed network connection. Therefore combine read-only inputs with network restrictions and artifact review.
5. Choose an enforced execution boundary
If the agent can run commands, process untrusted documents, install packages, or generate code, use an OS sandbox, correctly configured container or microVM, or hosted sandbox with an explicit mount policy. Verify the boundary rather than assuming the product name guarantees it.
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6. Review outputs before exporting them
Keep generated files inside the dedicated output directory until a person checks them. Inspect for copied secrets, hidden metadata, unexpected source files, links, scripts, and instructions that were embedded in input documents. Export only the files needed for the next system or recipient. An output review is especially important when the agent had network access or could call tools.
Compare the access models
The table below separates controls that are often presented as if they were equivalent. “Visible paths” means what the agent and its subprocesses can potentially see, not merely what the user interface displays.
| Approach | Enforcement | Visible paths | Write scope | Network | Credentials and integrations |
|---|---|---|---|---|---|
| Prompt or UI folder selection | Instruction or convention; not a process boundary | Potentially anything available to the host process | Host permissions unless separately restricted | Host process network access | Any files, environment variables, or helpers available to the process |
| Linux Unix-local execution | Host process; no added OS confinement in the documented SDK client | Files allowed by host permissions, regardless of selected workspace, HOME, or cwd |
Host permissions | Not isolated by this client | Host-visible credentials and local tools may be reachable |
| macOS local sandbox backend | Filesystem restrictions through sandbox-exec, according to the SDK documentation |
Paths allowed by the sandbox profile and platform permissions | Profile-dependent | No network isolation or container-equivalent boundary | Check the specific app’s entitlements, helpers, and integrations |
| Linux Landlock policy | Kernel-enforced filesystem policy configured by an application or sandbox runner | Paths allowed by every enforced policy layer and normal filesystem controls | Can restrict reading, writing, executing, and directory listing according to the configured rules | Filesystem mechanism; network policy must be handled separately | Does not automatically confine external helpers or credentials |
| Container or microVM with narrow mounts | Runtime isolation plus explicit mounts, subject to configuration | Mounted paths and files created inside the runtime | Read-only inputs and a dedicated writable output can be configured | Must be disabled or allow-listed separately | Local MCP or helper processes may sit outside the boundary; verify them |
| Hosted sandbox | Provider-managed isolated environment, subject to its documented controls | Files uploaded or mounted into that environment | Provider and runtime policy | Provider policy and your allow-list | Use scoped credentials or a proxy; do not assume host secrets are unavailable |
The table describes categories, not a guarantee for every product. Read the current documentation for the exact agent, runtime, version, and operating system you use.
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Restrict network access as a separate capability
File confinement does not stop an agent from disclosing readable content through the network. If a task does not need the internet, disable outbound access for the execution environment. If it needs one service, allow only the required destination or route requests through a controlled proxy.
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Separate network decisions into at least three questions:
- Can the process resolve names and connect to arbitrary hosts?
- Which domains, ports, or APIs are required for this task?
- Can generated code use the same network identity as the agent application?
Do not infer network isolation from a filesystem sandbox. The SDK documentation specifically notes that the macOS local backend does not isolate networking, and a host process on Linux retains its normal network capabilities. A container or microVM may also have outbound networking enabled by default unless you change its policy.
Keep credentials outside the agent environment
Long-lived application credentials should not be stored in readable source files, the task workspace, or a broadly mounted home directory. If an external service is required, prefer a scoped token with the minimum permissions and lifetime. Where available, provide access through a trusted proxy or secret-management mechanism that does not expose the raw credential to agent-generated code.
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Audit integrations and helper processes
The main agent interface is only one component. A shell helper, browser automation process, file synchronizer, desktop-automation bridge, or MCP server may run on the host with broader permissions.
Docker’s security documentation explicitly warns that local MCP processes run with host permissions and host isolation. It also explains that the workspace mount is the explicit path connecting a sandbox to project files. Therefore ask, for every integration:
- On which machine does it run?
- Does it run inside the sandbox, in a sidecar, or directly on the host?
- Which operating-system identity does it use?
- What files, sockets, devices, and network destinations can it access?
- Can it write back into the input tree or export files without review?
Disable unused integrations. Prefer an integration that accepts a narrow file or API scope over one that receives a whole home directory, browser profile, or repository. Recheck mounts after enabling a new tool because a helper can reintroduce access that the primary runtime denied.
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Linux: do not mistake a directory for confinement
With the SDK’s Unix-local client, commands execute as host processes and receive no additional Linux isolation. A selected directory, changed HOME, or changed cwd is therefore an organizational aid, not a security boundary.
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Linux Landlock provides a kernel interface for restricting filesystem actions such as reading, writing, executing, and listing directories. The kernel documentation states: “A sandboxed thread can only access a file path if all its enforced policy layers grant the access as well as all the other system access controls (e.g. filesystem DAC, other LSM policies, etc.).” Landlock must be configured by an application or sandbox runner; it is not a one-click desktop setting. Normal filesystem permissions remain an additional layer, and files opened before restrictions are enforced are not subject to those restrictions. Use a maintained runtime that configures the policy correctly rather than attempting an improvised wrapper around an untrusted agent.
macOS: filesystem restrictions do not equal network isolation
The SDK documentation says its Unix-local backend applies filesystem restrictions through sandbox-exec, but it does not provide a container-equivalent boundary or network isolation. Apple’s App Sandbox documentation describes an app container and user-selected document access, while noting that POSIX permissions or ACLs can still deny operations.
Do not assume that every desktop agent uses Apple’s App Sandbox. Check the application’s documented entitlements, helper processes, file-selection behavior, and network policy. Granting access to one document does not prove that every process involved in the task is confined to that document.
Windows: verify the actual product configuration
The official sources considered here do not establish a universal Windows desktop-agent recipe. Windows has multiple access-control and isolation mechanisms, but an AppContainer, ACL arrangement, WSL setup, or another technique may not match the agent’s process model. Consult the agent’s current Windows documentation, identify where command execution occurs, and test the real boundary before exposing sensitive files.
Docker or hosted microVMs: mounts and helpers determine the result
Docker’s AI Sandboxes documentation describes microVMs in which an explicit workspace mount connects the sandbox to host project files. The agent can have broad privileges inside the VM, so the security benefit depends on what you mount and what services you connect. A narrow, read-only mount is materially safer than an entire home directory.
Inspect local MCP servers and other host-side processes separately. If an integration runs with host permissions, it can bypass the apparent sandbox boundary. Verify mount paths, write modes, network rules, credential injection, and export behavior after every configuration change.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Test the boundary before using sensitive files
Verification should be a planned step, not an assumption. Create two harmless test files: one inside the permitted workspace and one outside it. Ask the agent to open the allowed file, then attempt to access the outside file through the same tools it will use for the real task. The expected result is successful access to the first and a clear denial for the second.
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- Direct file reads and directory listings.
- Shell commands or generated scripts.
- Symlinks and parent-directory traversal.
- Writes to the input directory and to unrelated host locations.
- Network connections when networking should be disabled or allow-listed.
- Access through MCP servers, browser helpers, sync tools, or desktop automation.
- Visibility of environment variables, mounted configuration files, and credential helpers.
Record the runtime, operating-system version, mounts, permissions, network policy, and enabled integrations. If the test can read the outside file, stop and change the boundary; do not rely on a stronger prompt.
Common failure modes and fixes
“The agent keeps seeing files outside the workspace”
Check whether it is running as a host process, whether a shell helper is outside the sandbox, and whether the selected folder is merely a cwd. On Linux Unix-local execution, move to an enforced sandbox or container and remove broad mounts. On macOS, inspect the sandbox profile and helper processes rather than only the folder picker.
“The source files are unchanged, but information leaked”
Read-only permissions prevent modification, not copying. Disable unnecessary network access, review output artifacts, and remove credentials from the environment. Check whether a connected integration can upload or synchronize files.
“The agent cannot complete a legitimate task”
Least access can be too narrow. Add only the missing input, output path, or approved endpoint, then rerun the harmless boundary test. Avoid solving a denied operation by mounting the entire home directory or granting unrestricted network access.
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“A new tool changed the security model”
Re-audit every mount and process after adding an MCP server, browser, shell, or sync integration. A local helper may execute with host permissions even when the main agent runs in a VM. Remove the integration or run it inside the same constrained environment if it cannot meet the required boundary.
A practical checklist for every task
- Task inputs are copied into a dedicated workspace.
- Unrelated files, repositories, credentials, and cloud roots remain outside it.
- Input paths are read-only unless edits are essential.
- Outputs go to a separate directory and are inspected before export.
- The execution model is documented: host process, OS sandbox, container, microVM, or hosted runtime.
- Network access is disabled or limited to named destinations.
- Secrets are absent, scoped, or supplied through a controlled proxy.
- Every shell, browser, MCP, sync, and automation helper has been audited.
- A harmless inside/outside access test has passed.
- Changes to mounts, permissions, runtime versions, and integrations trigger a fresh review.
What “only the files it needs” really means
A defensible setup has two layers. First, the agent receives a deliberately small set of inputs and a separate output location. Second, the process is prevented from reaching anything else through an enforced filesystem boundary, restricted network, controlled credentials, and audited integrations. If you provide only the first layer, you have scoped the task but not necessarily secured the host.
The right implementation depends on the agent and operating system. Linux local execution needs an additional confinement mechanism; macOS filesystem controls still require separate network and integration checks; Windows requires product-specific verification; and containers or microVMs are effective only when mounts and helper processes are narrow. Treat each capability as an independent permission and test the complete path before trusting sensitive data to the agent.
Frequently Asked Questions
Can I rely on a prompt telling the agent to use one folder?
No. A prompt can guide behavior, but it does not restrict a host process or a helper with broader permissions. Use an enforced filesystem boundary and test it with harmless inside/outside files.
Is read-only access enough to protect confidential files?
No. Read-only access limits modification but still permits copying or network disclosure. Pair it with restricted networking, protected credentials, audited integrations, and output review.
What should I do if the agent needs one external API?
Allow only the required destination where possible, use a narrowly scoped credential or trusted proxy, and verify that generated code and helper processes cannot use broader network or credential access.
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