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Choose an isolation platform by first defining what an evaluated agent may execute, which files and credentials it may see, and which network destinations it may reach. For trusted experiments, local execution is convenient but is not a security boundary. Containers add a configurable boundary; hosted sandboxes reduce infrastructure work; self-hosting offers the most control over images, private networks, and data placement while making your team responsible for provisioning and cleanup. Compare those options on isolation strength, run-to-run separation, network policy, credential handling, persistence, lifecycle controls, and operator responsibility—not on the word “sandbox” in a product name.
What must an isolation platform protect?
An AI agent can run code that reads every file, credential, and network endpoint available to its execution environment. OpenAI’s Sandbox security guidance states this directly: “Agent-generated code can access the files, credentials, and network available to its environment.” Your platform choice is therefore a decision about the blast radius of a mistaken or malicious action.
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- Host and kernel: Can agent code reach the operating system, device interfaces, or other workloads?
- Data: Which repository files, mounted directories, caches, and snapshots are visible?
- Identity: Which environment variables, API tokens, cloud roles, and SSH keys can code read?
- Network: Is outbound traffic open, allow-listed, proxied, or disabled? Can outside systems connect inward?
- Tenant separation: Can one user’s run, files, process, or network namespace be reached by another?
- Lifecycle: When are processes killed and disks deleted, and who verifies that cleanup happened?
Write these requirements down before selecting a product. A platform that is excellent for reproducible coding tasks may be unsuitable for evaluating an agent that handles production credentials or untrusted customer data.
How do local, container, hosted, and self-hosted options differ?
The following comparison describes the documented design patterns, not a universal ranking. Actual protection depends on the image, mounts, permissions, credentials, network settings, and provider configuration you deploy.
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| Option | Isolation mechanism | Network posture | Credential approach | Persistence and cleanup | Who operates it? |
|---|---|---|---|---|---|
| Local development | Usually host processes; no OS-level confinement on Linux in the OpenAI Agents SDK’s Unix-local mode | Uses the host network unless you add external controls | Host files and environment variables may be readable | Host workspace persists; cleanup is manual | Developer or test operator |
| Docker or another container runtime | Container boundary; strength depends on runtime, privileges, mounts, and kernel exposure | Can be disabled or restricted; the SDK documents a Docker mode with network_mode="none" |
Pass only scoped values; avoid mounting host credential stores | Images and volumes can persist; the orchestrator must remove runs and data | Your team or an orchestrator |
| Hosted sandbox | Provider-managed workspace and runtime isolation | Defaults vary. Daytona documents open egress, closed ingress, and no shared sandbox network | Use provider mechanisms or a trusted proxy; keep application secrets outside | Provider APIs typically create, pause, resume, and destroy workspaces | Provider for infrastructure; you for policy and data handling |
| Self-hosted environment | Your chosen VM, container, microVM, or cluster boundary | Can integrate with private networks and organization-wide egress controls | You design the broker, identity, rotation, and audit path | You own provisioning, snapshots, retention, deletion, and recovery | Your infrastructure and security teams |
Docker’s security documentation describes Docker Sandboxes specifically and says, “The primary trust boundary is the microVM.” That statement applies to that documented product and configuration; it should not be generalized to every container launched by a Docker-compatible runtime.
Is local execution safe enough for evaluation?
Use local execution for trusted development and fast iteration, not as the default boundary for untrusted agent-generated code. In the OpenAI Agents SDK, Unix-local execution on Linux runs commands as local host processes without OS-level confinement.
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A workspace directory, the current directory, or a changed HOME variable does not prevent a process from addressing other readable host paths. If the user account can read a file, the agent process generally can too. Host environment variables, credential helpers, SSH configuration, browser profiles, and cloud metadata endpoints are common accidental exposure paths.
What about macOS restrictions?
The SDK documents filesystem restrictions for macOS local execution, but those controls do not provide network isolation equivalent to a container. An agent could still contact services available through the host unless a separate firewall or network policy intervenes.
When local mode is reasonable
- Evaluating prompts or tools against code and data that are already trusted.
- Prototyping an agent before moving the same harness into a controlled runtime.
- Running offline tests on a disposable developer account with no valuable credentials.
For anything else, put the workload behind a container, VM, microVM, or hosted sandbox and explicitly limit its mounts, identity, and network.
When is a container the right boundary?
Containers are a practical middle ground when you need a repeatable image and control over runtime settings, but they are not automatically equivalent to a virtual machine. Treat the container configuration as part of your security design.
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Build a minimal, pinned image containing only the interpreters, libraries, and test fixtures required by the evaluation. Run as a non-root user, remove unnecessary Linux capabilities, use a read-only root filesystem where the workload allows it, and provide a writable temporary directory rather than a writable host path.
Control mounts and persistence
Mount only the project data the agent needs, preferably read-only for evaluation runs. Do not mount the host’s home directory, container runtime socket, SSH directory, cloud credential directory, or arbitrary device nodes. If a run needs a cache or checkpoint, give it a dedicated volume with an explicit retention period and a deletion job.
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Choose a network mode deliberately
The OpenAI Agents SDK documents a Docker client option using network_mode="none" to disable networking. That is useful for tests that need no package downloads or external APIs. If the agent must reach services, use a controlled bridge or proxy and allow only the required destinations; a default bridge is not an allow-list.
Know when a container is not enough
A container shares the host kernel. If your threat model includes a determined escape attempt, hostile native code, or mutually untrusted tenants, evaluate a VM or microVM boundary and the runtime’s hardening guidance instead of assuming a standard container is sufficient.
What should I verify in a hosted sandbox?
Hosted sandboxes can remove much of the provisioning work, but “managed” does not mean policy-free. Confirm the provider’s actual isolation and retention behavior for the plan and region you will use.
Runtime and tenant isolation
Ask whether each run receives a separate process space, filesystem, runtime, and network namespace, and whether sandboxes from different customers share a network. Daytona’s documentation describes runtime, network, and project isolation; it also states that egress is open by default, ingress is closed by default, and sandboxes do not share a network. Those are documented design claims, not an independent comparative audit, so validate them against your configuration and current contract.
Ingress and egress
Closed ingress prevents unsolicited connections into a workspace, but it does not stop the agent from calling the internet. Open egress can expose prompts, source code, or generated data to any destination the agent chooses. Determine whether you can set an allow-list by hostname, IP, port, or proxy route, and whether DNS is governed by the same policy.
Images, snapshots, and resume
Check whether you can supply a custom image, install system packages, snapshot a workspace, or resume it later. Resume features improve debugging but extend the lifetime of agent-created files and tokens. Set an expiration for idle and completed workspaces, and verify that snapshots, logs, and object-storage copies follow the same deletion policy as the live runtime.
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A hosted service may expose an API that creates and destroys sandboxes. Keep your application’s authentication, billing, approval decisions, and sensitive audit functions in your own control plane; do not place those systems inside the agent workspace merely because the provider offers a private endpoint.
When does self-hosting justify the operational cost?
Self-hosting is justified when you need a private network, a specific image or accelerator, a residency requirement, or infrastructure controls that a hosted service cannot provide. It transfers responsibility for the entire lifecycle to your organization.
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Separate the three planes
OpenAI’s architecture guidance separates the agent harness, execution environment, and application server. Keep the application server responsible for user identity, billing, approvals, policy, and durable records. Let the harness coordinate tools, while the execution environment runs untrusted code with the smallest possible identity.
Isolate users and workloads
Self-hosted environments should be isolated by user or workload wherever data must not be shared. Depending on the threat model, that may mean separate containers, VMs, microVMs, nodes, accounts, or cloud projects. Document which boundary protects against which failure; a namespace that prevents accidental file overlap may not protect against a kernel-level escape.
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Own provisioning and destruction
Automate creation from a known image, apply network and identity policy before starting the agent, and destroy the environment after the evaluation window. Add a reconciler that finds abandoned runtimes, volumes, snapshots, and credentials. Test the cleanup path during an incident rather than assuming that a successful API response means all artifacts are gone.
How should network access be designed?
Start with no network access, then add the smallest set of destinations required by the evaluation. OpenAI recommends restricting outbound access to approved endpoints; this is safer than treating unrestricted internet access as a convenience setting.
Use a tiered policy
- Offline: Disable networking for tests that use only local fixtures and preinstalled dependencies.
- Allow-listed services: Permit specific package registries, model endpoints, or test APIs through a proxy.
- Brokered access: Route sensitive third-party calls through a service that authenticates, filters, rate-limits, and logs requests.
- Broad internet: Enable only when open-web behavior is the subject of the evaluation, and use disposable identities and data.
Cover the less-obvious paths
Check DNS resolution, IPv6, metadata-service addresses, proxy environment variables, local Unix sockets, and egress from helper processes. A policy that filters HTTP traffic but leaves raw TCP, DNS tunneling, or cloud metadata reachable is incomplete.
Design ingress separately
Inbound access is a different decision from outbound access. Prefer no inbound routes. If a test needs a callback, expose a short-lived endpoint with authentication and a narrow path rather than placing the workspace on a shared internal network.
How do I keep credentials out of agent workspaces?
Keep application API credentials outside the execution environment wherever possible. OpenAI’s self-hosting guidance notes that an executor-environment key is narrower than an application key but is still readable by agent-generated code.
Use a broker instead of mounting secrets
Have the application server or a dedicated broker perform privileged operations. The sandbox submits a narrowly scoped request; the broker checks the user, run, destination, and action before making the call. Return only the minimum response, redact secrets from logs, and never place a long-lived master token in an environment variable visible to the agent.
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Scope and rotate every token
- Give each run a distinct identity and expiration time.
- Limit permissions to the exact repository, bucket, API method, or test account required.
- Prevent tokens from being reused across users or resumed workspaces.
- Rotate or revoke credentials when a run ends, fails, or is suspected of compromise.
- Audit issuance, use, denial, and revocation in the control plane.
Separate executor and application identities
The executor needs enough authority to start and manage its assigned runtime, not to read billing records, change policy, or mint new credentials. Keep those capabilities in a service outside the sandbox and require explicit approval for actions that affect durable systems.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What persistence and lifecycle controls should I require?
Decide whether each evaluation should be disposable, resumable, or reproducible from a clean snapshot. Persistence changes both debugging value and data exposure.
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| Snapshot-based repeat | Reproducible comparisons across agents | Snapshot contains hidden state or credentials | Build snapshots from clean images and scan before publication |
Define retention for live disks, attached volumes, snapshots, logs, terminal transcripts, proxy records, and provider backups. A “delete workspace” button is not enough unless the service documents what it removes and when residual copies expire.
How can I choose a platform step by step?
Use this sequence to turn a broad platform decision into testable requirements.
- Describe the agent: List interpreters, compilers, browser tools, native binaries, file operations, and package-install behavior it can invoke.
- Classify the data: Mark source code, personal data, credentials, regulated records, and proprietary prompts by sensitivity.
- Define the adversary: Decide whether you are defending against accidental misuse, prompt injection, malicious dependencies, a compromised agent, or a deliberate escape attempt.
- Set network rules: Record required destinations and ports. Default everything else to denied, and decide whether DNS and metadata endpoints need separate controls.
- Choose the minimum boundary: Use local mode only for trusted work; a container for basic repeatability; a hosted sandbox for managed isolation; or a VM/microVM-based self-hosted design for stronger control and private-network needs.
- Design identities: Specify which service creates the runtime, which identity the agent receives, and which operations remain in the application control plane.
- Set persistence: Choose ephemeral or resumable behavior, then define retention and deletion checks for every artifact.
- Run adversarial acceptance tests: Attempt to read a forbidden host path, access another run’s files, reach a denied endpoint, query cloud metadata, reuse an expired token, and retain data after teardown.
- Recheck defaults after changes: Re-test whenever the runtime image, SDK, provider plan, network policy, or identity configuration changes.
What common selection mistakes should I avoid?
Assuming “sandbox” means a fixed security level
The label can describe anything from a restricted process to a microVM. Read the provider’s architecture and configuration reference, then verify the controls in your own account.
Confusing a private workspace with a private network
A workspace can have an isolated filesystem while still having unrestricted outbound internet access. Evaluate storage, process, and network separation as separate properties.
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Mounting convenience credentials
Mounting a developer’s home directory or cloud credentials may make a demo work quickly, but it grants the agent the same authority as the developer. Replace it with a scoped brokered identity.
Leaving cleanup to humans
Abandoned runtimes often retain logs, volumes, and tokens. Use automatic expiration plus a reconciliation job and alert when deletion fails.
Comparing providers on unsupported numbers
There is no established universal winner for cost, performance, reliability, or security effectiveness in the available official documentation. Compare the controls you can verify, and measure your own workload under the threat model that matters.
What does a defensible reference architecture look like?
Place a policy-enforcing application service between the user and the execution runtime. The service authenticates the user, creates a run-specific identity, selects an approved image, applies network rules, and records an audit event. The agent harness receives only the tools and data needed for that run. The sandbox has no direct path to application databases, billing systems, approval queues, or master credentials.
For a hosted design, the provider supplies the workspace lifecycle while your service supplies policy, data minimization, secret brokering, and retention decisions. For a self-hosted design, add image signing, patching, capacity management, host monitoring, and a tested destroy-and-recover process. In both cases, treat provider defaults as changeable: SDK integrations, network policies, and isolation details can change over time.
Which option should I select?
Select the simplest option that satisfies the threat model, not the one with the shortest setup guide. Local execution fits trusted development. A carefully configured container fits repeatable tests with modest risk. A hosted sandbox fits teams that need managed workspaces and can accept provider-specific controls. Self-hosting fits private-network, custom-image, residency, or infrastructure-control requirements when the organization is prepared to operate the full lifecycle. If you cannot state the allowed files, identities, destinations, and retention period, you are not ready to choose a platform.
Frequently Asked Questions
Can a workspace directory protect the rest of my computer?
No. A directory changes where an application starts, but it does not by itself limit the paths, processes, credentials, or network interfaces available to that process. Enforce those limits with an operating-system boundary, container or VM policy, and a restricted identity.
Should every evaluation disable the internet?
No. Disable it for offline tests, but allow only the destinations needed when network behavior is part of the evaluation. Use disposable data and identities for open-web tests, and keep the application’s privileged services behind a broker.
What should an executor credential be allowed to do?
It should be limited to creating or managing the specific runtime and artifacts assigned to one run. It should not read application databases, change authorization policy, access billing, or mint broader credentials.
How often should isolation settings be revalidated?
Revalidate after any SDK, image, provider-plan, network, identity, or orchestration change, and on a scheduled basis even when nothing appears to have changed. Include negative tests for forbidden files, networks, identities, and post-run retention.
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