The Loggie blog
AI agent access control: how to set permissions for your team
Design AI agent permissions around specific jobs, with separate identities, reusable Loggie policies, endpoint restrictions, approval rules, and revocation checks.
A reporting assistant needs to read project tasks. An operations assistant may also need to create them. If both use the same credential with the same permissions, every reporting run carries access it does not need.
Start an AI agent access-control policy with the job: which data does this assistant need, which actions may it take, and who can authorize exceptions? In Loggie, those decisions become assignments between agent identities, connected tools, and policies. You can inspect a request against those assignments instead of relying on a prompt that says "please be careful."
Separate the connection from the identity
A connection holds the provider configuration and authentication needed to reach a service such as Asana. An agent identity has its own Loggie key. Its assigned access determines which connections and operations it can use through Loggie.
That separation lets an administrator connect a provider once and assign different access to different assistants. It also puts a clear boundary around revocation: suspending one identity does not require handing a replacement provider token to every other assistant.
Name identities by responsibility and environment. weekly-project-reader is easier to review than agent-2. Give a production workflow a different identity from the test assistant used to develop it. Avoid one shared key across a team, because a shared identity makes requests harder to attribute and forces unrelated workflows to share an access lifecycle.
Provider permissions remain relevant. If the connected account can see an entire company workspace, a broad read policy may expose more than one project. Loggie's endpoint restriction and the provider's resource-level permissions solve different parts of the problem.
Write down the intended requests
Use a small permission inventory before configuring the policy. The following is a proposed setup, not a set of built-in Loggie roles:
| Workflow | Data it needs | Permitted action | Human review |
|---|---|---|---|
| Weekly project report | Tasks and owners | Read the required task endpoints | Review the report before sharing |
| Operations follow-up | Tasks and project context | Read tasks; request task creation | Approve each creation |
| Marketing analysis | Approved campaign metrics | Read reporting operations | Approve any later publishing workflow separately |
| Finance reconciliation | Selected billing records | Read the required records | Keep payment and refund operations unavailable |
The inventory should identify actual operations, not just tool names. "Asana access" is too vague to tell a reviewer whether an assistant can delete a task.
Discover the API using the identity you are configuring:
loggie discover
loggie discover asana --method GET --search tasks --limit 10
loggie discover asana --endpoint /tasks --method GET
Use your connection's actual slug. For a first implementation, choose one workflow and one connection. The Claude Code reporting tutorial is a read-only example with a concrete output to check.
Configure the policy in layers
Begin with read access if the job only retrieves data. Review the connection's endpoint classifications and its handling of unknown endpoints. For a narrow policy, deny unknown operations and add the ones the workflow actually needs.
Do not equate read-only access with "every GET is safe" or "every POST is a write." APIs differ, and GraphQL can send queries and mutations to the same path using POST. Review the operation and classification as well as the HTTP method.
Use endpoint restrictions to reduce the available surface. For a REST API, a rule for a particular method and path is narrower than a wildcard over a whole API. An endpoint path rule cannot contain a query string. Allowing /tasks therefore does not enforce a particular project query parameter. Use provider-side access restrictions where that distinction matters.
When a workflow genuinely needs a write, grant the required underlying access and restrict the permitted operations. Add approval requirements for the actions a human must review. A read-only identity is not a substitute for a correctly configured write-with-approval policy; a denied request may never reach the approval stage.
Set a per-minute request limit suitable for the job. This can constrain a runaway polling loop, but it is not a daily spending cap. A small number of requests may still perform costly operations upstream, so limit those operations separately.
For supported JSON responses, use response redaction rules to remove selected values the task does not need. For example, a summary may need a contact's organization but not their email address. Configure the actual field or path and verify the resulting response. Redaction rules are not automatic personal-data detection and should not be assumed to cover every file or non-JSON response.
Loggie also supports exact-value rules for selected REST request-body fields. These can constrain a known field, but they do not express arbitrary business logic. A field equality check is not a budget engine or a general resource-authorization system.
Reuse policies with explicit assignments
Once the reporting policy works, reuse it for compatible connections and identities. Loggie associates a reusable policy with its provider definition and API type; it is not a universal role that can be applied to unrelated services.
Assignments are explicit identity-and-connection pairs. Review those pairs before saving a change to a shared policy, since an edit can affect several workflows. Calling a policy "Marketing" does not automatically connect it to your company directory, enroll new employees, or confer access to every marketing tool.
Natural-language policy drafting can help produce an initial rule set. Read the generated rules before assigning them, especially wildcard paths and approval conditions. Test the resulting access rather than treating the policy's name or description as proof of enforcement.
Test allowed and denied behavior
Use disposable provider data for the first checks. A misconfigured rule may allow the very action you intend to block.
- Run a required read and inspect the returned fields.
- Attempt a prohibited operation against a safe test resource. Confirm a Loggie policy denial, not just a provider error.
- Submit an approval-required action and confirm it remains pending until reviewed.
- Check redaction with a known test value and confirm the assistant cannot see it.
- Suspend the test identity and confirm a new request with its old key fails.
Record the identity, connection, and relevant request-log entries with the result. A successful happy-path report proves that access works; it does not prove that unwanted access is blocked.
Include pending actions in offboarding
When a workflow ends, remove its assigned access or suspend the identity and revoke the key as appropriate. Review and reject pending approval requests explicitly. Do not assume that changing a policy automatically cancels previously queued actions.
Remove local saved credentials and secret-environment entries from the retired runtime too. loggie logout clears the CLI's saved configuration, not the server-side key.
Finally, check for access outside Loggie: provider tokens, browser sessions, or another connector available to the same assistant. A policy on Loggie requests cannot govern those alternate routes. The OpenClaw setup guide shows how to keep provider credentials out of an agent runtime, and the Slack approval guide covers the lifecycle of a queued write.