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The strongest protection is layered: expose only the action-group functions the agent needs, constrain the service role and Lambda permissions, require confirmation for consequential calls, and let the agent ask for missing parameters instead of guessing. Guardrails add content safeguards but do not replace authorization or approval controls.
Important product status: AWS documentation now refers to the original service as Amazon Bedrock Agents Classic. It is no longer open to new customers, although existing customers can continue using it. AWS points new deployments toward Amazon Bedrock AgentCore. Verify the service and console version available in your account before following the instructions below.
Which settings actually limit an agent’s tool access?
In Bedrock Agents Classic, the controls that directly reduce what an agent can do are its action groups, the operations and parameters defined in those groups, the state of each group, and the AWS permissions granted to the agent and its executors. Confirmation adds a human approval gate, while user input prevents the model from inventing values for required arguments. Guardrails address unwanted content and behavior in messages and responses; they are an additional safeguard, not an authorization boundary.
Use the following order when designing an agent:
- Expose the smallest useful set of functions or API operations.
- Choose whether Bedrock or your application will execute each proposed action.
- Restrict the service role and every action-group Lambda to the resources and operations actually required.
- Require explicit confirmation before actions with financial, data-changing, communication, or account-impacting consequences.
- Keep user input enabled when a required value might be missing.
- Associate an appropriate Guardrail for content policy and response safety.
Check the product and version before configuring anything
AWS’s current action-group documentation says the existing product is Amazon Bedrock Agents Classic and is closed to new customers. Existing customers can continue to use it, while AWS directs readers seeking comparable capabilities to AgentCore. Console labels, API behavior, and availability can change, so first confirm which service your account supports. The classic setup described here is documented in AWS’s action-group guide and related pages.
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If you are maintaining an existing Classic agent, the settings below map to its documented console and API controls. If you are starting a new deployment, consult the current AgentCore documentation and do not assume that a Classic console path or field name is available.
Reduce the action surface with action groups
Expose only required functions
An action group is the agent’s declared tool surface. You can define individual function details or provide an OpenAPI schema. Include only operations the use case needs; do not add a broad administrative API merely because the backend exposes it. Keep each function description precise and mark every value that is genuinely required. Accurate descriptions and required-parameter declarations help the agent select an intended operation rather than improvise one.
The Add an action group documentation describes two fulfillment choices:
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- Return control to the application: Bedrock returns the predicted action and parameters in the
InvokeAgentresponse, allowing your application to inspect, authorize, execute, or reject the operation.
Returning control is the tighter execution boundary when your application must apply business rules, display a custom approval screen, perform a second authorization check, or call a non-AWS system itself. The agent proposes; your code decides whether anything actually runs.
Disable unused groups
The action-group API includes an actionGroupState field that can allow or disallow invocation. Disable groups that are not needed for a deployment, tenant, environment, or release. Removing an unused function from the schema is even clearer, but changing the state provides a practical way to keep a definition while preventing calls. Test the prepared version after changing the state; an unprepared draft is not the configuration your runtime will necessarily use.
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Design parameters as a security boundary
Do not rely on prose such as “use carefully” to constrain a tool. Enumerate allowed operations, require identifiers and scope values, and reject unexpected values in the Lambda or application executor. For example, a function that cancels an order should require an order identifier and should validate that the caller is allowed to cancel that order. The schema limits what the model can propose; executor-side validation limits what a malformed or manipulated proposal can do.
Require confirmation for consequential functions
Enable per-function confirmation
For function details, AWS exposes requireConfirmation with ENABLED or DISABLED. The console presents the equivalent user-confirmation setting. Enable it for operations that should occur only after explicit end-user consent, such as deleting data, submitting an order, changing an account, sending a message, or initiating a charge.
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When confirmation is enabled, the proposed invocation and its inputs are returned through the InvokeAgent flow. The user can confirm or deny before the action proceeds. AWS states: “To ensure that certain actions are implemented only after explicit user consent, we recommend that you request confirmation from the end user before invoking the function.” See Get user confirmation before invoking action group function.
AWS also notes that requesting confirmation may safeguard an application from actions caused by malicious prompt injection. Confirmation is therefore appropriate even when a request appears to come from a trusted conversation: the approval step gives the user a chance to inspect the actual function and inputs.
What confirmation does and does not do
- It creates an explicit approval gate in the agent flow.
- It does not expand or reduce IAM permissions; a confirmed call still needs valid AWS authorization.
- It does not validate that a parameter is correct or that the requested business operation is legal.
- It does not replace executor-side checks, rate limits, transaction controls, or audit logging.
For especially sensitive operations, return control to your application and combine the Bedrock confirmation step with your own authorization and approval workflow.
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Keep user input enabled when required information may be missing
Why the user-input setting matters
Bedrock can use the special AMAZON.UserInput action group to ask the user for missing parameters. Enable the console’s User input setting when a function cannot be safely called without information that may not be present in the conversation, such as a resource identifier, date, quantity, destination, or confirmation detail. The procedure is documented in Enable user input in Amazon Bedrock.
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Why disabling it can cause unintended calls
AWS warns that disabling user input prevents the agent from requesting additional details when it lacks enough information to complete an API request. Its documentation says: “If you disable user input, the agent doesn’t request the user for additional details. if it needs to invoke an API in an action group, but doesn’t have enough information to complete the API request.” In that situation, the model may select defaults or make a best guess, potentially hallucinating a function call. See Disable user input in Amazon Bedrock.
Disable user input only when every callable operation has safe, deterministic defaults and your executor independently rejects incomplete or ambiguous requests. Do not treat a default value as consent.
Use IAM and Lambda policies to bound effective access
Scope the Bedrock service role
The service role is the AWS authorization boundary behind the agent. It needs a trust relationship that allows the required Bedrock service principal and identity-based permissions for the resources used by the agent. The exact permissions depend on enabled features, which can include foundation-model access, action schemas, knowledge bases, Guardrails, KMS keys, collaborators, or provisioned throughput.
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Grant only permissions for configured features and the resources they need. If an agent has no knowledge base, it should not receive knowledge-base permissions; if it does not use a customer-managed KMS key, do not add unrelated key permissions. AWS’s service-role guidance describes the trust relationship and feature-dependent permissions.
Restrict each action-group Lambda
A Lambda used to fulfill an action group also needs a resource-based policy permitting Bedrock to invoke it. That policy should identify the intended function and, where supported, constrain the source account or agent context. The Lambda execution role should grant only the downstream operations that function performs. A function that reads tickets should not share an execution role capable of deleting databases.
IAM cannot tell whether a language model selected the right business operation. It can, however, make an incorrect or manipulated proposal less damaging by limiting which resources and API operations the executor can reach.
Understand the role of Guardrails
AWS lets you associate a selected Guardrail and version with an agent. Guardrails are described as safeguards against unwanted behavior in model responses and user messages. They can support content filtering and policy enforcement around what users submit and what the model returns. The setup flow is covered in Create and configure agent manually and the agent prerequisites.
A Guardrail is not a substitute for action definitions, IAM boundaries, confirmation, or application authorization. A content policy may block an unsafe response while still leaving an over-privileged function available; conversely, a perfectly harmless-looking prompt can request a destructive operation. Use Guardrails as a separate layer and record which Guardrail version is associated with the prepared agent.
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Choose an execution and approval pattern
| Design choice | Execution control | Blast-radius considerations | When it fits |
|---|---|---|---|
| Lambda fulfillment | Bedrock invokes the configured Lambda after selecting a function. | Depends on the Lambda resource policy, execution role, input validation, and downstream permissions. | Well-bounded, routine operations with a narrowly scoped executor. |
| Return control to application | The application receives the predicted action and parameters and decides whether to execute. | The application can apply authorization, approvals, validation, and custom logging before any side effect. | High-impact operations, multi-tenant systems, or workflows requiring business-policy checks. |
| Confirmation disabled | The action can proceed without an explicit end-user approval step. | Relies on schemas, IAM, executor validation, and the surrounding workflow. | Read-only or genuinely low-risk calls where an extra prompt would add little value. |
| Confirmation enabled | The user confirms or denies the proposed function and inputs before invocation. | Reduces accidental and prompt-injection-driven execution but does not change IAM. | Deletion, submission, messaging, purchases, account changes, and other consequential calls. |
| User input enabled | The agent can ask for missing required values. | Reduces guessed parameters and incomplete proposals. | Any operation whose required arguments may be absent from the conversation. |
| User input disabled | The agent cannot reprompt for additional details. | May lead to defaults or a best-guess invocation when information is missing. | Only tightly controlled operations with safe defaults and strict executor rejection. |
Configure and validate the settings
- Inventory the actions. List every operation the use case requires, classify each as read-only or state-changing, and remove anything not needed.
- Define the schema. Use function details or OpenAPI, describe behavior accurately, and mark required parameters explicitly.
- Select fulfillment. Choose Lambda only when its role and resource policy are narrowly scoped; otherwise return control to the application for policy checks.
- Set the action-group state. Disable unused groups through
actionGroupStateand verify that no active group exposes an administrative operation unnecessarily. - Set confirmation. Enable
requireConfirmationfor every consequential function. Test both confirmation and denial paths. - Enable user input. Turn on
AMAZON.UserInputwhen required values may be absent. Test a request with each required parameter omitted. - Scope IAM. Review the Bedrock service role, Lambda resource-based policy, Lambda execution role, and downstream resource policies. Remove permissions for unused features.
- Associate the Guardrail. Select the intended Guardrail and version for message and response safeguards.
- Save and prepare. AWS’s console instructions require saving and preparing configuration changes before testing. Confirm that the prepared version contains the intended groups, states, confirmation settings, user-input behavior, and Guardrail.
- Exercise failure paths. Try an unknown function, a missing identifier, an unauthorized resource, a denied confirmation, an injection-style instruction, and an executor error. The safe result is a refusal, reprompt, denial, or controlled error—not an unreviewed side effect.
Troubleshoot common unintended-action symptoms
The agent calls an operation it should not have
Inspect every active action group and its schema first. Disable or remove the operation, then check whether the prepared agent version is the one being invoked. Next review the service role and Lambda execution role; an over-broad permission can turn a small modeling mistake into a large effect.
The agent invents a parameter
Confirm that the parameter is marked required and that user input is enabled. Add executor-side validation that rejects empty, malformed, out-of-scope, or contradictory values. If a safe value cannot be obtained, return a controlled error or ask the user rather than silently applying a default.
The user never sees an approval question
Verify that confirmation is enabled on the specific function, not merely on another function in the same group. Confirm that the prepared version includes the change and that the application handles the confirmation response in the InvokeAgent flow.
A valid call fails with an authorization error
Check the Bedrock service role, Lambda resource-based policy, Lambda execution role, and target resource policy independently. Ensure the required feature permission is present, the resource ARN is correct, and any KMS or cross-account conditions match the deployment. Avoid solving the error by granting broad administrator permissions.
A practical baseline for safer agents
- Start with read-only functions and add write operations only when a documented use case requires them.
- Use return control for operations that need tenant checks, business rules, or a second approval system.
- Enable confirmation for every irreversible or externally visible action.
- Keep user input enabled unless missing values are impossible and safe defaults are proven.
- Make IAM and Lambda permissions no broader than the action schema.
- Associate a Guardrail for content safeguards and track its version.
- Save and prepare changes, then test denial, missing-input, malformed-input, and unauthorized-resource paths.
For new projects, verify whether AgentCore is the appropriate AWS path because Agents Classic is closed to new customers. For existing Classic agents, these layered controls provide the clearest way to limit tool access and reduce unintended execution.
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