Forensics for Planner-Executor Agents

A forensic analyst can replay every decision a planner‑executor AI made, see exactly which resources were accessed, and verify that no sensitive data leaked.

In practice, most organizations let these agents run directly against databases, Kubernetes clusters, or SSH endpoints. The agents receive credentials from a shared vault or environment variable, then issue commands without a unified audit trail. Cloud providers, container runtimes, and application logs each store separate logs, which makes it hard to stitch together a coherent picture of what the agent actually did. When a breach is suspected, investigators must chase down timestamps from multiple sources, often finding gaps where nobody recorded the agent’s activity.

That lack of visibility creates a paradox: teams want agents to act autonomously and quickly, but they also need to prove that every action was authorized and safe. Adding ad‑hoc logging to the agent’s code does not solve the problem because the agent can still exfiltrate data before a log entry is written, and the logs themselves may contain raw secrets. Even with role‑based access controls, no one can guarantee that a command will not violate policy, and no mechanism masks sensitive fields in responses before they reach downstream systems.

The missing piece is a control point that sits on the data path, where it inspects, approves, or blocks every request and response, and where it creates a complete audit record. Such a point must be able to enforce just‑in‑time approvals, mask confidential payloads, and capture a replayable session without requiring changes to the agent’s code.

Why forensics matters for planner‑executor agents

Planner‑executor agents often act on behalf of multiple services, chaining together database queries, container deployments, and remote command executions. If an attacker compromises the agent’s credentials, they inherit the agent’s reach across the entire environment. Forensic readiness means that after an incident, security teams can answer three critical questions: who initiated the action, what resources were touched, and whether any data was exposed. Without a reliable forensic record, organizations cannot meet audit requirements, cannot perform root‑cause analysis, and risk repeated exploitation.

Placing the gateway in the data path

hoop.dev provides a Layer 7 gateway that sits between the planner‑executor agent and the target infrastructure. The gateway proxies connections to databases, Kubernetes, SSH, and HTTP services, inspecting traffic at the protocol level. Because hoop.dev is the only point where traffic passes, it can enforce policies that would be impossible to guarantee inside the agent process.

hoop.dev records each session, creating a replayable log that captures every command and response. The gateway masks sensitive fields in real time, ensuring that confidential data never leaves the boundary in clear text. When a high‑risk operation is detected, hoop.dev routes the request for human approval before it reaches the target, providing just‑in‑time control without slowing down routine work. Additionally, hoop.dev blocks dangerous commands outright, preventing accidental or malicious damage.

Because the gateway holds the credential for the target connection, the agent never sees the credential. hoop.dev verifies the user’s OIDC token, reads group membership, and then applies fine‑grained policies based on that identity, keeping the enforcement logic outside the agent’s reach.

How hoop.dev enables forensic readiness

• Session recording – hoop.dev captures the full request‑response stream, allowing investigators to replay the exact sequence of actions.
• Inline data masking – sensitive values are redacted before they are stored or displayed, protecting data privacy during forensic analysis.
• Just‑in‑time approvals – risky commands trigger an approval workflow, ensuring that privileged actions are explicitly authorized.
• Command blocking – known dangerous patterns are prevented from executing, reducing the blast radius of a compromised agent.
• Credential isolation – the gateway stores the target credential, so the agent never accesses secrets directly.

The feature documentation describes in detail how these capabilities work. To get started quickly, follow the getting‑started guide, which walks you through deploying the gateway, registering a database, and configuring OIDC authentication.

For an overview of all supported connectors, visit the hoop.dev product page.

FAQ

Can hoop.dev integrate with existing planner‑executor frameworks? Yes. The gateway works with any client that speaks the native protocol (PostgreSQL, SSH, Kubernetes, etc.). Agents simply point their connection strings at the hoop.dev endpoint, requiring no code changes.

Does hoop.dev store raw session data? The gateway stores a replayable log that includes metadata and masked payloads. The gateway redacts sensitive fields according to the configured masking policies, and it never persists raw secrets.

How do I retrieve a forensic replay? The system indexes recorded sessions by user, time, and target. Using the web UI or API, you can filter for a specific session and stream the replay, which shows each command and the masked response in order.

Explore the open‑source implementation and contribute to the project on GitHub.