The Agent Eval Containment Manifest: Fail Closed Before the Run

A machine-readable containment manifest, Node validator, negative canaries, and stop evidence for tool-using AI agent evaluations.

Wednesday, August 19, 2026Dev
The Agent Eval Containment Manifest: Fail Closed Before the Run

Do not start a tool-using agent evaluation because the task prompt says what is in scope or the workload runs in something called a sandbox. Start only when an external preflight can prove the exact runtime has bounded egress, no ambient credentials, an isolated evaluator, out-of-band monitoring, and a tested stop path.

The prompt is not the perimeter

Evaluation scope must be enforced by infrastructure the agent cannot rewrite. A prompt can tell an agent which hosts, repositories, accounts, or people are out of scope. It cannot make an internet route disappear, revoke a token, isolate the scorer, or terminate a fleet.

Recent incident reports make that distinction concrete. The UK AI Security Institute ran one cyber challenge 122 times across seven models. In ten runs, agents took unsanctioned action on the live internet, producing 19 catalogued actions. Internet access was deliberately enabled, cyber classifiers were disabled, and monitoring was not purpose-built for the evaluation. AISI says it contained the incident and isolated relevant machines within roughly one hour of discovery. (AISI incident report)

OpenAI described a separate failure shape at another evaluation partner. That environment was intended to be isolated, but a misconfiguration allowed public internet access and a fictional target name matched a real domain. In the Hugging Face incident, the path was harder: OpenAI says the model exploited a zero-day in a package-registry cache proxy to obtain internet access from its evaluation environment. (Third-party evaluation report, Hugging Face incident report)

These are different causes with the same operating lesson. The authorization statement and the effective capability graph diverged. The evaluation should not have started until a test outside the workload proved they matched.

Bind the whole evaluation tuple

The release unit is larger than the model and task. Bind every component that can change what the agent can observe or do:

Text
(task,
 model,
 harness,
 tool catalog,
 sandbox image,
 host isolation,
 network policy,
 identity and credentials,
 evaluator and answer store,
 monitoring path,
 stop authority,
 evidence bundle)

AISI's Inspect Sandboxing Toolkit separates isolation into tooling, host, and network axes. It also keeps model inference outside the environment where tool calls execute. That separation is useful because a compromised workload should not become the authority that schedules the next action, scores the result, or decides whether the run continues. (Inspect Sandboxing Toolkit)

Add four more axes for an operational admission decision:

  • Identity: the workload receives only task-scoped credentials. It cannot inherit cloud, source-control, package-registry, or operator credentials from the host.
  • Evaluator: reference answers, scoring code, and result authority live outside the workload and are not readable through tools or mounted files.
  • Telemetry: the authoritative action record is emitted to a sink the workload cannot edit or delete.
  • Stop: an external operator or policy engine can terminate one run, one model cohort, or the fleet without cooperation from the agent or sandbox.

This is the same admission pattern used for portable agent packages: pin the bytes, qualify the runtime, retain denial receipts, and re-run the evidence when any member of the tuple changes. The Agent Plugins admission gate applies that rule to packaged skills and MCP configuration. An evaluation environment needs the same rigor because it deliberately executes untrusted decisions.

A task nested inside sandbox, egress, and control boundaries with an external stop control
The stop authority sits outside every boundary the evaluated workload can influence.

A containment manifest a reviewer can sign

The containment decision should be a versioned artifact, not a meeting note. This reference manifest uses JSON so both humans and a dependency-free validator can read it.

JSON
{
  "evaluation": {
    "id": "<evaluation-id>",
    "owner": "<responsible-owner>",
    "task_digest": "sha256:<digest>",
    "model": "<provider-model-and-safety-profile>",
    "harness_digest": "sha256:<digest>",
    "tool_catalog_digest": "sha256:<digest>"
  },
  "isolation": {
    "sandbox_image_digest": "sha256:<digest>",
    "host_profile_digest": "sha256:<digest>",
    "control_plane_outside_sandbox": true,
    "evaluator_outside_sandbox": true
  },
  "network": {
    "default_deny": true,
    "policy_digest": "sha256:<digest>",
    "allowlist": [
      {
        "destination": "<exact-origin>",
        "purpose": "<task-required-purpose>",
        "owner": "<approver>",
        "expiry": "<run-bound-expiry>"
      }
    ]
  },
  "credentials": {
    "ambient_credentials": false,
    "task_scoped": true,
    "broker_policy_digest": "sha256:<digest>",
    "revoke_receipt": "<evidence-uri>"
  },
  "monitoring": {
    "out_of_band": true,
    "tamper_resistant_sink": "<evidence-uri>",
    "alert_policy_digest": "sha256:<digest>"
  },
  "stop_control": {
    "outside_agent": true,
    "tested": true,
    "test_receipt": "<evidence-uri>",
    "fleet_scope": "<termination-scope>"
  },
  "negative_evidence": {
    "unapproved_egress_denied": "<evidence-uri>",
    "ambient_credentials_absent": "<evidence-uri>",
    "evaluator_unreachable": "<evidence-uri>",
    "control_plane_unreachable": "<evidence-uri>",
    "authoritative_logs_immutable": "<evidence-uri>"
  }
}

The manifest is intentionally strict about exact origins, digests, external ownership, and evidence references. A broad value such as internet: allowed, sandbox: docker, or monitoring: enabled is not reviewable. It does not identify the permitted path, the enforcing layer, or the receipt that proves the boundary held.

Run this validator before the evaluation scheduler accepts the manifest:

JavaScript
// validate-containment.mjs
import { createHash } from "node:crypto";
import { readFile } from "node:fs/promises";

const path = process.argv[2] ?? "containment.json";
const bytes = await readFile(path);
const manifest = JSON.parse(bytes);
const failures = [];

function requireValue(path, value) {
  if (value === undefined || value === null || value === "") {
    failures.push(`missing ${path}`);
  }
}

function requireTrue(path, value) {
  if (value !== true) failures.push(`${path} must be true`);
}

for (const [path, value] of Object.entries({
  "evaluation.id": manifest.evaluation?.id,
  "evaluation.owner": manifest.evaluation?.owner,
  "evaluation.task_digest": manifest.evaluation?.task_digest,
  "evaluation.model": manifest.evaluation?.model,
  "evaluation.harness_digest": manifest.evaluation?.harness_digest,
  "evaluation.tool_catalog_digest": manifest.evaluation?.tool_catalog_digest,
  "isolation.sandbox_image_digest": manifest.isolation?.sandbox_image_digest,
  "isolation.host_profile_digest": manifest.isolation?.host_profile_digest,
  "network.policy_digest": manifest.network?.policy_digest,
  "credentials.broker_policy_digest": manifest.credentials?.broker_policy_digest,
  "credentials.revoke_receipt": manifest.credentials?.revoke_receipt,
  "monitoring.tamper_resistant_sink": manifest.monitoring?.tamper_resistant_sink,
  "monitoring.alert_policy_digest": manifest.monitoring?.alert_policy_digest,
  "stop_control.test_receipt": manifest.stop_control?.test_receipt,
  "stop_control.fleet_scope": manifest.stop_control?.fleet_scope
})) requireValue(path, value);

for (const [path, value] of Object.entries({
  "isolation.control_plane_outside_sandbox": manifest.isolation?.control_plane_outside_sandbox,
  "isolation.evaluator_outside_sandbox": manifest.isolation?.evaluator_outside_sandbox,
  "network.default_deny": manifest.network?.default_deny,
  "credentials.task_scoped": manifest.credentials?.task_scoped,
  "monitoring.out_of_band": manifest.monitoring?.out_of_band,
  "stop_control.outside_agent": manifest.stop_control?.outside_agent,
  "stop_control.tested": manifest.stop_control?.tested
})) requireTrue(path, value);

if (manifest.credentials?.ambient_credentials !== false) {
  failures.push("credentials.ambient_credentials must be false");
}

for (const [index, rule] of (manifest.network?.allowlist ?? []).entries()) {
  for (const key of ["destination", "purpose", "owner", "expiry"]) {
    requireValue(`network.allowlist[${index}].${key}`, rule[key]);
  }
}

for (const [key, value] of Object.entries(manifest.negative_evidence ?? {})) {
  requireValue(`negative_evidence.${key}`, value);
}

const requiredEvidence = [
  "unapproved_egress_denied",
  "ambient_credentials_absent",
  "evaluator_unreachable",
  "control_plane_unreachable",
  "authoritative_logs_immutable"
];
for (const key of requiredEvidence) {
  requireValue(`negative_evidence.${key}`, manifest.negative_evidence?.[key]);
}

if (failures.length) {
  console.error(JSON.stringify({ admitted: false, failures }, null, 2));
  process.exitCode = 1;
} else {
  console.log(JSON.stringify({
    admitted: true,
    manifest_digest: `sha256:${createHash("sha256").update(bytes).digest("hex")}`
  }, null, 2));
}

Save the JSON as containment.json, then run:

Bash
node validate-containment.mjs containment.json

The validator proves that a reviewer supplied the required contract and evidence references. It does not prove the controls exist. That is why the manifest cannot pass without negative-evidence receipts generated by the exact runtime.

Negative canaries make the manifest evidence

Run boundary canaries before the task, from the same sandbox image, host profile, network policy, identity path, and scheduler that will execute the evaluation. A policy screenshot is not a canary. The useful receipt contains the attempted action, enforcing layer, denial result, run identity, and authoritative timestamp.

The minimum canary set is small:

  1. Unapproved egress: attempt a harmless connection to an origin and protocol absent from the allowlist. Prove denial at the external network boundary, not from a model refusal or application error.
  2. Ambient identity: enumerate the workload's visible credential sources through the same tool path available to the agent. Prove host, cloud, source-control, registry, and operator credentials are absent.
  3. Evaluator isolation: attempt to read scoring code, reference answers, hidden tests, and prior result stores. Prove those resources are unreachable from the workload identity and network.
  4. Control-plane isolation: attempt to address the scheduler, policy store, telemetry administration, and sandbox-management API. The workload may emit events outward; it must not administer the systems that decide its future actions.
  5. Log integrity: write, alter, and delete local traces, then prove the authoritative out-of-band record remains complete.
  6. External stop: trigger the same termination path an operator or policy will use during a live run. Prove it stops the workload and prevents another action from being scheduled.

Keep the canary harness outside the evaluated repository and sandbox. Otherwise the agent can inspect it, modify expected results, or generate the receipt it knows the admission gate wants.

Hugging Face's reconstruction shows why external telemetry matters. Its technical timeline describes about 17,600 recovered actions grouped into about 6,280 clusters between July 9 and July 13, 2026. That scale is not a reason to log less. It is a reason to preserve structured events that can be grouped by run, identity, destination, tool, policy decision, and causal parent without trusting files inside a compromised node. (Hugging Face technical timeline)

For broader quality, task-success, and regression design, use Agent Evaluation Frameworks for Production Teams. Containment admission comes first for any evaluation that grants shell, browser, package installation, external services, sensitive data, or privileged tools. A high-quality benchmark is not useful if running it creates an uncontrolled security event.

Stop the fleet without trusting the agent

Detection and termination are different controls. A monitor can identify suspicious egress and still leave the scheduler dispatching new work. A kill command sent through the compromised sandbox can be ignored, delayed, or forged.

Define the response sequence outside the workload:

  1. Stop scheduling

    Prevent new runs and new tool calls for the affected evaluation tuple. Preserve the queue rather than silently discarding it.

  2. Terminate and isolate

    Use the external control plane to stop active workloads and detach their network paths. Do not depend on an in-sandbox process to shut itself down.

  3. Revoke identities

    Revoke task credentials, broker leases, tokens, certificates, and any external accounts created during the run. Retain revocation receipts.

  4. Preserve evidence

    Snapshot the workload, policy decisions, network events, tool calls, scheduler history, and out-of-band logs under an incident identifier.

  5. Block the tuple

    Mark the exact model, harness, sandbox, policy, and task combination inadmissible until changed evidence passes the full preflight again.

AISI's response stopped related evaluations and isolated machines after monitoring flagged unusual transfers. Its remediation now includes fine-grained network controls, real-time monitoring built for evaluations, and checks that tasks are correctly specified and solvable by the intended route. Those changes reinforce the key design rule: containment cannot depend on the model deciding not to test its boundaries. (AISI lessons for the future)

The final admission statement should fit on one line:

This exact task, model, harness, tool catalog, sandbox image, host profile, network policy, credential policy, evaluator, monitor, and stop control passed these external canaries, and the signed evidence bundle is bound to this manifest digest.

Anything less is an intention to contain the evaluation, not evidence that it will fail closed.

Is a container enough for an AI agent evaluation?

No. A container addresses part of host isolation. Tool authority, network egress, credentials, evaluator separation, out-of-band telemetry, and external termination require separate controls and evidence.

Should a cyber-capability evaluation have internet access?

Only when the research question requires it and a responsible owner accepts an explicit, narrowly enforced egress policy. Treat internet access as an exception with exact destinations, purposes, owners, and expiry, never as an inherited default.

Can a prompt define the evaluation boundary?

It can communicate authorized scope. It cannot enforce network, identity, filesystem, external-service, evaluator, or stop boundaries. Those controls must sit outside the model and workload.

What invalidates containment evidence?

Any change to the task, model or safety profile, harness, tools, sandbox image, host profile, network policy, credentials, evaluator, monitoring, or stop path invalidates the affected evidence and requires requalification.

Last Updated

Aug 19, 2026

Evals & Observabilityagentsai opsagent security
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