Configuring AI coding agents access to AWS with session recording

When an internal AI coding agent is granted a long‑lived AWS access key, it can spin up resources, read data, and invoke services without any human seeing what it does. The convenience is tempting, but the lack of visibility means a rogue prompt or a buggy model could exfiltrate secrets, launch costly instances, or corrupt production workloads. Companies that rely on these agents often discover weeks later that an unexpected bucket was created or a critical table was altered, and there is no reliable record of the actions that led to the change.

Security teams therefore ask for session recording: a complete log of every command, API call, and response that the agent generates while interacting with AWS. The desire for session recording is clear, yet most organizations still let the request travel directly from the agent to the AWS endpoint. The connection bypasses any checkpoint that could capture the traffic, enforce approvals, or mask sensitive values. In that state, the request reaches the target unmediated, and no audit trail exists.

To close that gap, the access path itself must become the enforcement point. The gateway sits between the AI agent and AWS, intercepting the wire‑level protocol, applying policies, and emitting the required session recording. Only by placing a control surface in the data path can you guarantee that every interaction is observed and governed.

Why session recording matters for AI coding agents

AI agents generate code and configuration on the fly. Their output is often fed directly into cloud‑native tools such as the AWS CLI or SDKs. Because the model’s reasoning is opaque, a single malformed prompt can produce a series of privileged API calls that would be difficult for a human reviewer to anticipate. Session recording provides a forensic record that can be replayed to understand intent, verify compliance, and support incident response. It also deters misuse by making every action visible to auditors and reviewers.

Placing the gateway in the data path

hoop.dev acts as a Layer 7 identity‑aware proxy that sits between the AI coding agent and AWS. The agent authenticates to hoop.dev using OIDC or SAML, and hoop.dev validates the token, extracts group membership, and decides whether the request may proceed. The gateway holds the AWS credential internally, so the agent never sees the static key. All traffic to AWS flows through hoop.dev, giving the system a single point where policies can be enforced.

Enforcement outcomes provided by hoop.dev

• hoop.dev records each session, creating a replayable audit trail that includes every request and response.
• hoop.dev masks sensitive fields in AWS responses, preventing the AI agent from learning secrets that it does not need.
• hoop.dev enforces just‑in‑time approval for high‑risk operations such as creating IAM roles or modifying security groups.
• hoop.dev blocks commands that match deny‑list patterns before they reach the AWS API.
• hoop.dev retains the session for later replay, enabling post‑mortem analysis without impacting the original workload.

Because the gateway is the only place where traffic is inspected, these outcomes are guaranteed regardless of the agent’s internal logic. The setup phase, defining OIDC clients, provisioning service accounts, and assigning least‑privilege IAM roles, determines who may start a request, but it does not itself record or mask anything. The data path, implemented by hoop.dev, is the sole source of enforcement.

Getting started

To try this architecture, deploy the hoop.dev gateway using the official Docker Compose quick‑start. The deployment includes an OIDC configuration that integrates with your existing identity provider and a default policy set that enables session recording for all AWS connections. Once the gateway is running, register your AWS target in the hoop.dev UI, attach the appropriate IAM role, and grant the AI coding agent the required OIDC scopes. The agent will then connect through the gateway using its normal AWS CLI or SDK calls.

For step‑by‑step guidance, see the getting‑started documentation. The learn section provides deeper insight into policy authoring, masking rules, and approval workflows.

FAQ

Is session recording optional?

Yes. Policies can be scoped per‑resource or per‑user, allowing you to enable recording only for high‑risk AWS services while leaving low‑impact calls unrecorded.

Will the AI agent ever see the AWS secret?

No. hoop.dev stores the credential inside the gateway process, and the agent authenticates only with its OIDC token. The secret never leaves the data path.

How can I review recorded sessions?

Recorded sessions are stored in the backend configured for hoop.dev. The UI provides a searchable replay interface where you can filter by user, time range, or AWS service.

Ready to explore the implementation? Visit the GitHub repository to view the source code and contribute.