Without audit trails, an AI coding agent can rewrite production code unnoticed, leaving a hidden trail of changes that no human ever sees.
Many organizations treat Devin, the AI‑driven code generator, like any other service account. Teams bake a single long‑lived credential into CI pipelines, and the organization grants the agent wide‑scope permissions across GCP projects. The result is a direct, unrestricted line from the agent to databases, Kubernetes clusters, and storage buckets. No intermediate hop records what queries were run, which files were edited, or which secrets were accessed. When a mistake occurs, the team has no reliable way to answer who changed what and when.
That unrestricted line is the core of the problem. Teams want to know exactly which commands Devin issued, but the current setup offers no checkpoint. The request still reaches the target resource directly, bypassing any approval workflow, inline masking, or command‑level audit. The lack of a gate means the organization cannot prove that a particular change was authorized, nor can it automatically hide sensitive values that might appear in logs or API responses.
Enter hoop.dev. hoop.dev sits in the data path between Devin and every GCP service it talks to. By acting as an identity‑aware proxy, hoop.dev intercepts each wire‑level request, applies policy, records the full session, and then forwards the request to the target. The gateway holds the credential needed to reach the backend, so the AI agent never sees the secret itself.
Why audit trails must be enforced at the gateway
Setup components, such as OIDC tokens, service‑account roles, and IAM policies, determine who Devin is and what it may request. Those pieces are essential, but they stop at authentication. They do not provide visibility into the actual commands or queries that cross the network. hoop.dev provides the only place where enforcement can happen because it sits on the protocol layer, inspecting traffic before it reaches the backend.
When Devin asks for a Cloud SQL connection, hoop.dev records the exact SQL statement, the user identity attached to the request, and the time of execution. If the statement contains a credit‑card number, hoop.dev masks that field in the response before it is logged. If a dangerous Kubernetes API call appears, hoop.dev pauses the request and routes it to a human approver. hoop.dev stores every interaction as a replayable session, giving engineers a complete audit trail that satisfies internal governance and external auditors.
How hoop.dev builds the audit trail for an AI agent
First, the organization registers Devin as a connection in the hoop.dev UI. The registration includes the target GCP resource, the service‑account credential that hoop.dev will use, and the set of groups that may invoke the connection. Next, the system handles identity via OIDC; Devin presents a token issued by the corporate IdP, and hoop.dev validates it, extracting group membership to drive policy decisions.
During each session, hoop.dev captures request metadata, payload, and response. The gateway stores the recorded sessions in a durable location that you can query later. This creates a reliable audit trail that ties every action back to a verified identity.
Practical steps to get started
To bring this capability to your environment, follow the getting‑started guide that walks you through deploying the hoop.dev gateway, configuring the GCP agent, and registering Devin as a connection. The documentation explains how to define just‑in‑time approval policies, set up masking rules for secret fields, and enable session replay. All of the heavy lifting, credential storage, OIDC verification, and policy enforcement, happens inside the gateway, so your existing CI pipelines and developer tools require no code changes.
Because hoop.dev is open source, you can inspect the source code, contribute improvements, or run the gateway in a fully air‑gapped environment. The project’s GitHub repository contains the Docker Compose quick‑start, Helm charts for Kubernetes, and detailed architecture diagrams.
Explore the hoop.dev GitHub repository to see the full source and start a local instance for testing.
FAQ
- How does hoop.dev capture every action performed by an AI coding agent? hoop.dev sits in the data path, intercepting the wire‑level protocol. It records the request, response, and metadata before forwarding the traffic, so no action can bypass the audit.
- Will inserting a gateway add noticeable latency? The gateway adds a small, predictable overhead because it processes traffic at the protocol layer. In practice the latency is negligible compared with network round‑trip times, and the security benefits far outweigh the cost.
- Can I view sessions that occurred before hoop.dev was deployed? hoop.dev can only record sessions that pass through it. Historical data must be collected by other means; however, once deployed, every new interaction is automatically captured.
For a deeper dive into policy configuration and masking options, consult the hoop.dev learn documentation. The getting‑started guide provides step‑by‑step instructions for a production‑grade deployment on GCP.
