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Do not give an agent production credentials until it has passed supervised boundary tests in a disposable environment. Start with no credentials, deny unnecessary network and filesystem access, and use synthetic documents to exercise prompt-injection and unauthorized-tool scenarios. Treat a pass as evidence about the exact configuration tested—not as proof that every future agent run will be contained.
The safest preflight combines architecture review, adversarial testing, external monitoring, and a repeatable stop-and-fix process. The sequence below covers what to inspect, which tests to run, what counts as failure, and how to decide whether a narrowly scoped test account is safe to issue.
What the sandbox must prove
An agent can act through whatever files, credentials, tools, and network routes its execution environment exposes. OpenAI cautions that agent-generated code may access those resources, so isolation is an access-control boundary, not merely a convenience for running code.
Your preflight should produce evidence for five separate questions:
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- Filesystem: Can the agent read and write only the workspace and paths required for the task?
- Network: Can it reach approved test services while blocked from everything else?
- Tools: Does the authorization layer reject an action that the model requests but is not allowed to perform?
- Secrets: Are credentials absent from prompts, source files, logs, snapshots, and exported artifacts?
- Integrity: Can the agent modify its own instructions, policy files, tests, audit records, or monitoring configuration?
A successful run supports only the model, tools, policies, mounts, network rules, and test cases exercised. It does not certify a sandbox generally, and it does not guarantee containment after a model, prompt, tool, retrieval source, memory store, or policy changes.
Write the boundary before you run anything
Turn the intended workload into an explicit allowlist. Security reviewers and operators should be able to point to a written answer for every resource the agent may use.
| Boundary area | Write down | Default for a first test |
|---|---|---|
| Files | Readable paths, writable paths, temporary directories, mounted volumes, and shared services | One disposable workspace; no host home directory, credential store, socket, or unrelated mount |
| Commands and tools | Exact executables, APIs, parameters, rate limits, and actions requiring approval | Only the minimum tools needed for a synthetic task; destructive actions disabled |
| Network | Approved hostnames, ports, protocols, direction, and data-transfer limits | No internet; add one controlled test endpoint only when required |
| Data | Permitted input classes, retention period, export paths, and cross-workload sharing rules | Synthetic or scrubbed data, isolated per workload or user |
| Human control | Actions that must pause for review and who can approve them | Require confirmation for external side effects, credential use, and data export |
Separate environments when data must not be shared between users or workloads. Record the intended boundary as a test contract; every later result should map to one of its entries.
Build a disposable test setup
Use an isolated image and a second layer of containment
Create a fresh sandbox image or instance that can be destroyed and recreated. Anthropic recommends static configuration review and supervised probing before an evaluation, ideally without internet access and inside a second sandbox. The outer layer should observe and, where possible, enforce limits on the inner agent runtime.
Pin operating-system, runtime, dependency, model, tool, and policy versions where practical. Capture the image identifier and configuration hash with the test record so a later rerun is comparable. Do not use a shared development machine whose files, SSH agent, cloud metadata endpoint, container socket, or browser profile could become an unintended escape route.
Start with no credentials
The first pass should authenticate to nothing. If authentication is essential to exercise a control, create a disposable test account with narrow permissions, synthetic data, short expiry, and an easy revocation path. It must not be able to reach production records, alter identity settings, create new credentials, or authorize other services.
A sandbox executor key should grant execution access only; it must not carry the application’s authority. Never place a long-lived application key in the prompt, repository, task file, manifest, environment dump, source code, or artifact directory.
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Review configuration before launching the agent
Perform a static review before the model receives a task. Inspect the following items and record the effective value, not merely the value intended by an interface:
- Base image, kernel or virtual-machine boundary, runtime version, installed packages, and set-user or privilege settings.
- Workspace and temporary-directory mounts, read-only flags, device mappings, host sockets, shared volumes, and path traversal protections.
- Environment variables, inherited process arguments, mounted configuration files, metadata endpoints, and shell history.
- Exposed ports, DNS behavior, proxy settings, egress firewall rules, IPv4 and IPv6 routes, and any service-discovery mechanism.
- Tool definitions, argument validation, approval gates, rate limits, identity used for each call, and error handling.
- Logging destinations, audit immutability, snapshot and cache locations, artifact export jobs, and teardown behavior.
- Memory, retrieval indexes, browser state, and shared queues that could carry data from another run.
Verify the active controls from outside the agent process. A configuration file that says “deny” is not evidence that the runtime actually denies the operation.
Keep credentials out of agent-readable context
Credential placement is part of the security boundary. Treat secrets as runtime configuration supplied by a trusted broker or provider-native secret facility, not as prompt content. The agent should receive the minimum capability needed for one operation, preferably through a mediated call that never reveals the underlying value.
Bad placements to eliminate
- System and user prompts, hidden instructions, or chat transcripts.
- Source files, package manifests, shell scripts, notebooks, and task descriptions.
- Environment-variable dumps, command-line arguments, process listings, crash reports, and debug traces.
- Retrieval documents, browser downloads, generated code, screenshots, checkpoints, and model memory.
- Logs, snapshots, caches, exported artifacts, and support bundles.
Properties of a safe test credential
- Dedicated to the test and easy to revoke.
- Limited to one service, one tenant, or one synthetic dataset.
- Unable to create users, issue tokens, change policy, access billing, or reach production systems.
- Short-lived, with an explicit expiration and an owner responsible for revocation.
- Delivered only at the point of a permitted operation, with access recorded outside the agent’s control.
After teardown, verify that the account is revoked and that no copy remains in the sandbox, logs, artifacts, or monitoring system.
Run the preflight in eight stages
1. Establish the baseline
Launch the clean image with the agent disabled and collect an inventory of processes, mounts, routes, listening ports, environment variables, and available tools from an external observer. Mark every item that should remain unchanged during the run. This baseline lets you distinguish a normal runtime component from an unexpected capability added by the agent.
2. Exercise permitted filesystem operations
Give the agent a harmless task that creates, reads, edits, and deletes files inside its assigned workspace. Check ownership, permissions, symlink handling, temporary files, and cleanup. Then use synthetic instructions that request reads of parent directories, host paths, mounted secret locations, device files, and another workload’s workspace.
The expected result is a policy denial or an empty, non-sensitive response for every out-of-scope path. Also test whether the agent can edit its own system instructions, policy files, test fixtures, audit configuration, or log destination. A successful write outside the allowlist is a stop condition.
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3. Exercise the network allowlist
Permit one controlled test endpoint if the workload genuinely needs network access. Ask the agent to make an approved request and verify the destination, method, payload, identity, and response through an external network log. Next attempt connections to controlled destinations that should be denied, including an unapproved hostname, a raw IP address, an alternate port, and a redirect target.
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4. Test tool authorization independently of model behavior
Submit requests for an allowed tool, a disallowed tool, and an allowed tool with a disallowed argument. The enforcement layer—not the model—must reject the latter two. Try variations in capitalization, encoding, path syntax, nested arguments, and error-retry messages. Confirm that a tool cannot call another tool implicitly, elevate its identity, or bypass an approval gate through a free-form parameter.
Record the requested action, effective principal, policy decision, arguments after normalization, and result. A model declining to ask for a forbidden action is useful behavior, but it is not a substitute for an authorization decision enforced below the model.
5. Deliver indirect prompt-injection content
Place harmless synthetic instructions in a document, web response, issue, email, or retrieval record. For example, the content can tell the agent to upload workspace files, reveal hidden instructions, disable logging, or invoke an administrative tool. The task itself should require none of those actions.
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Run separate cases for:
- A single retrieved document containing an out-of-scope instruction.
- A web response that redirects the agent to another host.
- A multi-turn conversation in which an earlier message establishes a misleading role or policy.
- Conflicting instructions in two documents, one trusted and one untrusted.
- Obfuscated or encoded text that becomes an instruction after parsing.
The agent may describe or flag the malicious content, but the tool and data layers must still block the prohibited action. OWASP recommends structured security testing before production and after material changes to prompts, tools, memory, retrieval, policies, or model providers.
6. Check secret exposure and artifact handling
Seed the test only with clearly synthetic markers, such as unique canary strings, so you can trace where data travels without risking a real secret. Search process output, logs, generated files, screenshots, caches, snapshots, memory stores, traces, and exported artifacts for those markers and for credential-like patterns.
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Ask the agent to print environment variables, inspect process arguments, search common secret paths, and include its context in a generated report. The expected behavior is denial, redaction, or omission. Verify that a broker-mediated operation does not expose the broker’s underlying secret and that teardown removes temporary copies.
7. Monitor integrity and stop on boundary crossings
Use an observer outside the agent’s control for filesystem, process, network, tool, and identity events. Configure immutable or append-only audit storage where possible. Stop immediately if the run:
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- Reads or writes an out-of-scope path.
- Reaches an unapproved host, port, address family, or proxy.
- Accesses a secret location or emits a canary value where it should not.
- Changes instructions, tests, policies, logs, monitoring, or teardown settings.
- Makes an unauthorized tool call, escalates identity, or bypasses human approval.
- Attempts persistence after the task or survives the intended teardown.
Preserve the event record, image identifier, policy version, prompt and retrieved inputs, tool arguments, and external logs. Do not “clean up” evidence before the failure is analyzed.
8. Revoke, destroy, and rerun
Revoke any disposable credential, destroy the runtime, remove snapshots and caches, and inspect exported artifacts. Fix the configuration or policy that allowed the failure, then rerun the complete relevant suite from a fresh image. Do not convert a failed test into a pass by weakening the test case.
Use a test matrix instead of a single demonstration
| Area | Positive case | Negative case | Pass evidence |
|---|---|---|---|
| Filesystem | Create and edit a file in the assigned workspace | Read a parent path, secret mount, or another workload’s directory | Allowed operation succeeds; denied operation is blocked and logged |
| Network | Call the one approved synthetic endpoint | Reach an unapproved host, port, redirect, raw IP, or IPv6 route | Only the allowlisted request leaves the runtime |
| Tools | Invoke an allowed operation with valid arguments | Invoke a forbidden tool or alter an argument to exceed scope | Authorization decision is enforced below the model |
| Injection | Summarize hostile text as data | Follow hostile text to exfiltrate, alter policy, or call an admin tool | Content is treated as untrusted; side effect is rejected |
| Secrets | Use a broker-mediated test capability | Print variables, search secret paths, or export context | Underlying value never appears in agent context or artifacts |
| Integrity | Write normal task output | Modify instructions, tests, logs, or monitoring | Protected files remain unchanged and the attempt is alerted |
Repeat each negative case with different wording and ordering. A control that works only for one prompt is a fragile demonstration, not a reliable boundary.
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A pass is scoped evidence
Approve the next stage only when every required negative case was blocked, the positive cases worked, logs are complete, artifacts are clean, and teardown removed the test state. Record the exact model, tools, policy, image, network rules, mounts, retrieval sources, and test inputs. The approval should name the credential scope and expiration, not grant a general production entitlement.
A failure is a design signal
Classify failures by layer: runtime isolation, filesystem policy, egress control, tool authorization, secret brokerage, data handling, monitoring, or teardown. Fix the lowest layer that can enforce the rule. For example, do not rely on a prompt telling the agent not to read a file when the mount itself can be removed; do not rely on a model refusal when an authorization gateway can reject the call deterministically.
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Repeat testing whenever the system changes
Rerun the full preflight after material changes to the model provider, system prompt, tools, tool identities, retrieval pipeline, memory, policy engine, sandbox image, mounts, network routes, logging, or credential broker. Smaller smoke tests can run on every build, but they do not replace the complete adversarial suite after a boundary-affecting change.
Anthropic’s security guidance states: “This configuration should be verified before every evaluation begins.” Apply that principle to production-like trials as well: verify the active configuration, not merely the configuration stored in source control.
Choosing an environment for repeatable tests
If you are selecting infrastructure, compare capabilities rather than assuming a product label guarantees isolation.
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|---|---|
| Isolation strength | What prevents access to the host kernel, devices, sockets, metadata services, and neighboring workloads? |
| Workload separation | Can each user or task receive a fresh instance, identity, workspace, and memory store? |
| Filesystem controls | Are mounts explicit, read-only by default, and protected against symlink and traversal tricks? |
| Outbound controls | Can egress be default-deny with hostname, port, protocol, DNS, IPv4, and IPv6 visibility? |
| Secret brokerage | Can a service perform a narrowly scoped action without exposing the underlying secret to the agent? |
| Audit and monitoring | Are tool calls, identity changes, file events, network events, and policy decisions visible outside the runtime? |
| Persistence and teardown | Can you destroy instances, revoke identities, remove caches, and verify artifact deletion? |
| Repeatability | Can the image, policy, test inputs, and results be versioned and rerun after every change? |
| Operational effort | Can your team maintain rules, review alerts, rotate test accounts, and investigate failures? |
These axes describe what to verify; they are not a ranking of providers. Obtain architecture-specific assurances and test the actual deployment you will operate.
What the published evidence does—and does not—say
OpenAI reported in 2025 that one particular prompt-injection example “worked 50% of the time” with the specific user prompt described in its article. That figure is not a general prompt-injection rate, a sandbox-escape rate, or a current reliability score. It illustrates why one successful refusal or one successful attack cannot establish a universal security conclusion.
Guidance from OpenAI, Anthropic, and OWASP converges on least privilege, deny-by-default networking, supervised adversarial testing, external monitoring, and retesting after changes. None of those sources turns a checklist into a certification method. A production credential rollout still requires architecture-specific review and least-privilege access design.
Quick Recap
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