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This design limits damage if generated code is buggy, manipulated, or deliberately malicious. It also gives you a reviewable trail of what the agent asked to do, which policy evaluated the request, which credential was used, and what left the environment.
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What a sandbox actually protects
A sandbox is an execution boundary around model-directed code and tool calls. Its security is defined by everything the process can reach, not by what the system prompt tells the model to avoid. OpenAI’s Sandbox security guidance states: “Agent-generated code can access the files, credentials, and network available to its environment.” Treat that as the practical rule for design.
If a directory is mounted, a socket is reachable, a credential is injected, or an outbound route is open, assume the agent can eventually discover and use it. Prompt instructions are useful for behavior, but they are not an authorization boundary.
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The four assets that need separate protection
- Files: private documents, source code, browser profiles, SSH keys, configuration files, and local databases.
- Credentials: API keys, cookies, access tokens, signing keys, and cloud-role credentials.
- Network paths: internal services, metadata endpoints, arbitrary internet destinations, and mail or payment systems.
- Authority: the ability to send, delete, publish, deploy, change records, or spend money.
A useful boundary therefore contains the executor, while trusted infrastructure outside it retains authorization, secrets, audit records, and recovery state.
Reference architecture: executor, harness, and broker
Use a separate virtual machine, container, or hosted sandbox for each user or workload. Give it a dedicated working directory and only the mounts needed for the current task. Keep orchestration and policy in a trusted harness outside the execution environment.
What belongs inside the sandbox
- Task-specific input files, preferably copied into a disposable workspace.
- The agent runtime and approved libraries.
- Temporary output and artifacts awaiting review.
- Only the command, file, and port capabilities required by the task.
What stays outside
- Application API keys and third-party secrets.
- Authorization rules, approval state, billing, and rate limits.
- Immutable audit logs and alerts.
- Recovery data, production credentials, and the ability to destroy or restore the workspace.
The sandbox can ask the harness to perform an approved operation. A credential broker or vault then uses the real secret outside the model-visible environment and returns only the minimum result. This prevents a prompt, generated file, or process listing from becoming a secret-distribution channel.
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Trust boundaries to draw before implementation
- Model to tool: the model proposes a function call; it does not execute one directly.
- Tool to policy: the harness validates the function, arguments, destination, identity, and requested side effect.
- Policy to broker: only an approved request can obtain a narrowly scoped credential or network connection.
- Broker to external system: the broker enforces the approved host, operation, tenant, and limits.
- Result to model: output is size-limited and checked for secrets or unexpected content before it is returned.
Build a permission ladder instead of one broad “agent access” switch
Progressive authority lets you test useful work without immediately granting the ability to cause harm. Move upward only when the preceding level is observable and reliable.
| Level | Agent may | Typical control | Evidence required to advance |
|---|---|---|---|
| Observe | List metadata, read a small test file, or fetch a non-sensitive API response. | Read-only tools, synthetic data, no mutation functions. | Correct scope, destination, and output handling. |
| Draft | Prepare an email, patch, or API payload without sending or committing it. | Store output as an artifact for inspection. | Human can understand the exact proposed action. |
| Stage | Write to a quarantine directory or test tenant. | Isolated account, diff or preview, rollback path. | Expected side effects and failure behavior. |
| Approve | Request a specific consequential action. | Policy or human gate checks recipients, scope, and parameters. | Explicit approval tied to an immutable request. |
| Commit | Send email, mutate production data, or perform an external write. | Broker executes only the approved request, then records the result. | Audit event, response validation, and recovery confirmation. |
Do not let the model select its own level. The harness should decide whether a call is observational, draft-only, staged, or commit-capable based on the workflow and current approval state.
Step-by-step setup
1. Define the task and blast radius
Write down the exact outcome, data sources, destinations, and side effects. “Process invoices” is too broad; specify the input directory, fields the agent may read, test tenant, allowed recipients, maximum attachment size, and whether production writes are forbidden.
- Name the workspace and its lifetime.
- List every required file path, API host, port, and tool.
- Classify actions as read, draft, stage, or commit.
- Set limits for record count, request size, runtime, and spend.
- Define what happens on timeout, policy failure, or partial completion.
2. Start with disposable compute
Create a fresh VM, container, or hosted sandbox for the workload. Use a separate instance per user or job where practical, and destroy it when the task ends. Give the process an explicit working directory rather than the host’s home directory.
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3. Remove default network access
Configure outbound traffic as deny-by-default. Add only the domains and ports required for the current operation, and revisit the list when the workflow changes. Separate executor traffic from remote tool-server or MCP traffic because those connections may originate from different infrastructure.
Log the destination, request type, identity, policy decision, and response size for every permitted connection. An unrestricted egress path can exfiltrate mounted files even when the filesystem itself is isolated.
4. Keep credentials out of the model’s environment
Do not place long-lived secrets in prompts, instructions, source code, images, logs, or generated artifacts. Store them in a vault or trusted proxy. The sandbox receives an execution-service identity, not the application’s reusable API key.
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When a request passes policy, the broker should issue a narrowly scoped, short-lived credential for one approved host and operation. Bind it to the job or request where possible, rotate secrets routinely, and revoke them immediately after suspected exposure. Ensure the secret is not echoed in tool output, exception text, process arguments, or artifact files.
5. Expose a minimal tool surface
Register separate read and write tools. A read-only agent should not even have a mutation function available to call. Filter the available MCP functions to those needed by the workflow, then validate every argument before execution.
read_filemay resolve paths only beneath an approved directory.list_recordsmay query a test tenant and cap page size.send_emailmay remain unavailable until recipient and attachment review.write_apimay target only a staging host until promotion is approved.
Apply input checks before a tool call and output checks before results return to the model. Reject unexpected destinations, oversized responses, path traversal, unsupported methods, and arguments that widen scope.
6. Add an approval gate for irreversible actions
For email, deletion, production updates, deployment, or other consequential operations, show the exact proposed action: recipients, subject, body, attachments, endpoint, method, record identifiers, and changed fields. Require a human or policy engine to approve those parameters, not a vague statement such as “send it.”
Bind approval to a request hash or immutable identifier. If the agent changes a recipient, attachment, endpoint, or payload after approval, require a new review. The broker must reject any execution whose parameters do not match the approved request.
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7. Capture artifacts and audit events
Store drafts, diffs, command output, tool requests, policy decisions, credential use, destinations, and response sizes in trusted logging infrastructure outside the sandbox. Review generated artifacts before exporting them. Logs should be append-only or otherwise protected from the agent.
Keep enough context to reconstruct who or what initiated a call, which identity was used, what policy allowed it, and whether the external service accepted it. Avoid logging raw secrets or unnecessary personal data.
8. End the job cleanly
Revoke temporary credentials, export only approved artifacts, and destroy the workspace when the task finishes. If persistence is required, snapshot only after scanning and review, and make the next run start from a known-clean image. Preserve audit records and recovery state outside the destroyed environment.
Protecting email workflows
Email combines data disclosure with an irreversible external action, so begin at Observe and Draft. Let the agent read a small, approved test mailbox or synthetic messages, extract information, and produce a draft without a send capability.
Safe progression for email
- Read only selected messages or attachments from a sandbox mailbox.
- Generate a draft in a quarantine store; do not expose a send function.
- Display recipients, reply-to address, subject, body, attachment names, and sizes for review.
- Check recipient domains, prohibited data classes, and attachment policy.
- After approval, let the broker send exactly that draft using a short-lived credential.
- Record the message identifier, policy decision, sender identity, recipients, and provider response.
Separate “compose” and “send” functions so a prompt injection in an email cannot directly trigger delivery. Cap attachment size, scan generated files, and reject hidden or unexpected attachments. Treat links and instructions inside incoming messages as untrusted content, not as authorization.
Protecting local and shared files
File access should be path-scoped, read-only by default, and explicit about symlinks and archives. A rule that allows /workspace is safer than one that allows an entire home directory, but the harness must still prevent traversal outside the approved root.
Recommended file controls
- Copy only task inputs into a disposable workspace.
- Use separate input and output directories; make inputs read-only.
- Reject absolute paths, parent-directory traversal, and symlinks that resolve outside the workspace.
- Limit file count, size, decompression depth, and total extracted bytes.
- Keep secrets, browser profiles, SSH material, and host sockets unmounted.
- Review diffs before copying outputs back to a trusted system.
For a document-editing task, the agent can read /workspace/in and write /workspace/out. The harness can then present a diff and export only named files. This is safer than granting write access to the source repository or shared drive.
Protecting API access
Expose an API-specific broker rather than a generic HTTP client. The broker should map a small set of approved operations to fixed hosts, methods, schemas, and identities.
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Read-only API phase
Start with a non-sensitive response from a test tenant or fixture. Restrict methods to the minimum, cap pagination and response size, and strip fields the model does not need. Log the destination and identity even for reads.
Staging phase
Allow writes only to a test tenant or quarantine endpoint. Show a structured diff, validate identifiers and field values, and provide a rollback or cleanup operation. Do not reuse production credentials in staging.
Production commit
Require approval tied to the exact endpoint, method, payload, and record scope. The broker obtains a short-lived credential only after approval, enforces rate and quantity limits, executes once, and records the external response. If the API is not idempotent, add a deduplication key or keep commit unavailable until a human can handle retries safely.
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Default-deny egress is necessary but not sufficient. An agent can encode data into an allowed request or hide it in a permitted response unless the broker understands the operation.
- Allowlist domains and ports per task, not globally.
- Prefer fixed API routes over arbitrary URL fetch tools.
- Block link-local and metadata endpoints, private ranges, and unexpected DNS destinations.
- Cap request and response sizes and reject unusual methods or content types.
- Inspect redirects so an approved host cannot silently send traffic elsewhere.
- Separate network identities for read and write operations.
- Alert on repeated denials, destination changes, and unusual volume.
Remote MCP traffic deserves its own policy because the connection may originate outside the executor. Apply the same destination, identity, input, output, and logging controls to that path.
Hosted, self-hosted, or Docker-backed isolation?
Choose the execution layer according to data locality, operational capacity, and required controls rather than convenience alone.
| Option | Strengths | Trade-offs | Best fit |
|---|---|---|---|
| Hosted sandbox | Provider provisions Linux compute and exposes settings for packages, files, setup commands, environment variables, container size, and network. | Less control over underlying infrastructure and data location; provider capabilities and regional availability must be verified. | Teams that want isolation without operating the runtime layer. |
| Self-hosted VM or container platform | Control over image, private network, data locality, credentials, snapshots, and runtime policy. | You operate patching, isolation hardening, capacity, monitoring, and incident response. | Regulated workloads or internal services that cannot be exposed to a provider network. |
| Docker-backed executor | Repeatable images, disposable filesystems, and straightforward local development. | A container is not automatically a complete security boundary; kernel, daemon, mounts, sockets, and host permissions require careful hardening. | Controlled workloads where the host and container policy are managed by a capable team. |
Compare candidates on isolation strength, mount controls, egress policy, credential brokering, MCP and tool filtering, approval hooks, artifact review, persistence and snapshots, auditability, and operational burden. Verify the provider’s current supported regions and controls before placing sensitive data in a hosted environment.
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Harness design: keep authorization outside the model
The harness is the trusted control plane. It should own identity, policy, approvals, rate limits, audit records, and recovery. The sandbox should handle commands, files, ports, and artifacts within the granted scope.
Minimum request pipeline
- Receive the model’s proposed tool call.
- Normalize paths, URLs, identities, methods, and payloads.
- Classify the action as observe, draft, stage, or commit.
- Evaluate allowlists, schemas, quotas, data policy, and current approval.
- Reject or transform unsafe requests before execution.
- Ask the broker for a scoped credential only when policy permits.
- Execute in the sandbox or through the broker.
- Validate and size-limit the result before returning it to the model.
- Write an audit event independent of the sandbox.
Input guardrails can prevent a call; output guardrails can inspect the converted result before it reaches the model. Use both. A successful tool response is not proof that the requested operation was safe.
Failure modes and recovery
The agent reads files outside the approved directory
Stop the job, revoke any temporary credential, preserve logs, and destroy the workspace. Check mounts, symlinks, archive extraction, and path normalization. Tighten the resolver so authorization occurs on the canonical path, not the user-supplied string.
A tool call targets an unexpected host
Reject it before network connection. Review redirects, DNS resolution, proxy rules, and any generic URL-fetch capability. Replace broad HTTP access with fixed broker operations.
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Revoke and rotate it immediately, identify every system that received the value, and remove exposed copies from artifacts and logs where feasible. Add redaction and prohibit secret-bearing environment variables, command arguments, and prompt content.
The agent sends a message without approval
Disable the send capability, preserve the immutable request and provider response, and inspect whether the approval token was missing, replayed, or bound to different parameters. Separate draft and commit tools and require a fresh approval whenever recipients, attachments, or content change.
The sandbox is compromised
Assume all mounted data and temporary credentials were exposed. Revoke credentials, quarantine affected artifacts, destroy the instance, and rebuild from a known-clean image. Use the audit trail to determine external calls and notify affected system owners.
Pre-production test plan
Exercise the controls with harmless accounts and synthetic files before granting production access.
- Attempt path traversal, symlink escape, oversized archives, and hidden files.
- Ask the agent to print environment variables, process arguments, mounted devices, and network routes.
- Try an unapproved domain, redirect, private address, metadata endpoint, and oversized response.
- Inject instructions into a document or email that request secret disclosure or tool use.
- Change a recipient, endpoint, attachment, or payload after approval and confirm the broker rejects it.
- Interrupt a write midway and verify idempotency, rollback, or safe operator recovery.
- Confirm logs capture request, policy decision, credential use, destination, response size, and outcome without storing secrets.
- Destroy the workspace and verify that no credential or artifact remains usable.
Operational checklist
- Use a disposable workspace and non-production account first.
- Mount the smallest possible directory; keep sensitive mounts read-only.
- Deny network access until a destination allowlist exists.
- Keep secrets outside prompts and files; use a vault or trusted broker.
- Separate read, draft, stage, and commit tools.
- Require approval for sending email, changing records, deleting data, or deploying infrastructure.
- Record every tool request, policy decision, credential use, destination, and output size.
- Review generated artifacts before exporting them.
- Revoke credentials and destroy the workspace when the task ends.
- Test failure modes with synthetic data before production access.
How to decide whether an agent is ready for production
Production access is justified only when the workflow has a narrow purpose, a tested boundary, and a recovery path. You should be able to answer, without asking the model, which files it can read, which hosts it can reach, which identity it can use, which actions require approval, and how to revoke access within minutes.
If any answer depends on the model voluntarily following instructions, the system is not sandboxed enough. Reduce mounts and tools, move authorization into the harness, add a broker, or keep the workflow at Observe, Draft, or Stage until those controls are enforceable.
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