Agent Transaction Whitelist
An agent transaction whitelist is a strict rule set that limits what automated software can run. You build it by defining exact database queries or API calls the agent may send. Many teams start by giving AI agents a standard service role in the database. That broad role often lets the bot read or change any row in a table. When a prompt fails or loops, broad roles let the agent drop data or expose records. How an agent transaction whitelist works in practice To build an agent transaction whi
Open Policy Agent (OPA) + Transaction-Level Authorization: the complete guide
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An agent transaction whitelist is a strict rule set that limits what automated software can run. You build it by defining exact database queries or API calls the agent may send. Many teams start by giving AI agents a standard service role in the database. That broad role often lets the bot read or change any row in a table. When a prompt fails or loops, broad roles let the agent drop data or expose records.
How an agent transaction whitelist works in practice
To build an agent transaction whitelist, you must first map every task the bot does. Start by listing the exact tables, views, or endpoints the agent needs to read. Next, list the specific write actions the bot must run to finish its job.
In a native database setup, admins often create stored procedures for these allowed tasks. They revoke direct table rights from the agent role. Instead, they grant the agent permission to run only those specific stored procedures. Each procedure accepts fixed inputs and runs one safe, pre-approved statement inside the database.
For API workflows, teams place a policy check inside the agent runner or middleware. Before the agent sends a request, the runner compares the payload against an approved list. If the request matches a known pattern, the runner forwards it to the backend service. If the agent tries a new command, the runner blocks the call and logs an error.
What native role setups solve and where they fall short
Native roles and stored procedures stop an agent from touching tables outside its scope. They also ensure the agent logs in with its own distinct key and identity. Database logs will show which service account opened the session and when it started.
Still, static database roles only check who logs in and which object they touch. They cannot inspect raw queries in flight when agents need flexible read permissions. Building a new stored procedure for every slight query change takes too much engineering time. Because of this friction, teams often fall back to granting broad read or write roles.
Open Policy Agent (OPA) + Transaction-Level Authorization: architecture patterns and best practices
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Once an agent has direct table permissions, native roles cannot stop bad queries in flight. A confused agent might run a huge scan that locks up the primary database. It might also pull columns that hold sensitive user data like emails or card numbers. Native roles also lack a step to pause a risky write and ask a human first. To close this gap, teams need a way to inspect and filter every command in flight.
Best practices for maintaining agent rules over time
Keep your allowed list small when you launch a new agent into production. Start with read-only rules and watch the logs to see what the bot tries to run. When the agent needs to change data, require a human to review the action first.
You should also pair command rules with data masking on the results. Even an approved read query can return phone numbers or national IDs in the output. Masking rewrites matched fields in results before the payload reaches the agent model. Review your rule logs every week to remove old permissions that the agent no longer uses.
Check database and API queries on the wire
Identity tools, roles, and network rules decide who opens a session. Setup alone cannot check what each query does or mask sensitive values in a response once a session starts. When workflows touch Postgres, MySQL, SQL Server, MongoDB, ClickHouse, Kubernetes APIs, SSH, or internal HTTP APIs, hoop.dev runs beside those services as an open-source proxy, a sidecar for your Postgres or API. It inspects requests coming in and results going back on the wire.
Your login details and client tools stay as they are while hoop.dev guardrails refuse bad deletes or drops before they run. On responses, hoop.dev data masking rewrites matched sensitive values in memory. Furthermore, hoop.dev holds SOC 2 Type II, is MIT licensed, and writes every query and decision to an audit trail that generates evidence for HIPAA, GDPR, and PCI DSS. See the source on GitHub.
Frequently asked questions
What is the difference between a role and a transaction whitelist?
A role decides which database or table an account can open after logging in. A transaction whitelist checks the exact command or query before the system runs it.
How do you handle dynamic inputs in an allowed transaction?
You define a fixed query template with safe placeholders for the changing values. The policy checks that the command structure matches the template and validates the input types.
What happens when an agent tries to run a blocked transaction?
The policy engine stops the command before it reaches the database or service. It can return a safe error message to the agent or pause for human approval.