Use Case

Give Claude Code and Cursor production access. Without the risk.

AI coding assistants need access to real infrastructure to troubleshoot, debug, and deploy. But they connect with your identity, your credentials, and your access level. Hoop gives them access with guardrails, masking, and human-in-the-loop approval for anything destructive.

See AI coding controls

The problem

Your AI assistant has the same access you do.

How it works

Agent reads freely. Agent writes with approval.

Hoop sits between the AI coding assistant and your infrastructure. The agent connects through the gateway, and Hoop applies controls based on what the agent is doing, not just who it is.

Read operationsPass through

The agent queries databases, reads Kubernetes state, and inspects logs. Hoop masks sensitive data in responses (PII, credentials, secrets) so the agent can troubleshoot without seeing customer data.

Write operationsRequires approval

When the agent needs to apply a fix, deploy a change, or modify configuration, Hoop routes the action for human approval. You see the exact command in Slack. You approve or deny. If denied, the feedback goes back to the agent.

Blocked operationsAlways blocked

Destructive commands like DROP, DELETE namespace, and rm -rf are blocked outright. The agent never executes them, regardless of what the LLM generates.

The workflow

From broken pod to applied fix. With a human in the loop.

  1. Agent connects

    Agent connects to Kubernetes through Hoop to troubleshoot a failing pod.

  2. Agent reads freely

    Agent reads pod logs, describes deployments, and inspects configs. All read operations pass through with sensitive data masked.

  3. Fix proposed, approval requested

    Agent identifies the issue and proposes kubectl apply -f fix.yaml. Hoop routes this to the on-call engineer via Slack.

  4. Denied with context

    The engineer reviews the fix. It is wrong. They deny and leave a note: wrong namespace.

  5. Agent adjusts, fix applied

    The agent receives the denial and adjusts. It resubmits with the correct namespace. Approved. Fix applied.

Data masking

The agent sees what it needs. Nothing more.

Hoop intercepts every query response and masks PII, credentials, and payment data before it reaches the model. The agent can still troubleshoot. It just never sees real customer data.

Guardrails

DROP TABLE never reaches your database.

Destructive commands are blocked before execution. No approval flow, no Slack notification, no chance. The agent receives a denial and adjusts its approach.

Audit trail

Every command. Every decision. One log.

Every agent session is recorded with timestamps, commands, approvals, denials, and masked fields. Replay any session for incident review or compliance audit.

ORGANIZATIONAL IMPACT

From governed sessions to enterprise compliance.

Every Claude Code session through Hoop generates audit evidence automatically. Your security team sees organizational risk reduction — not just individual developer sessions.

DROP TABLE blocked before execution — outage prevented
47,293 PII fields masked across Claude Code sessions
Every command logged with full context for audit
Incidents PreventedThis Quarter
$0 exposure avoided
CRITICAL
DROP TABLE users blocked
Est. 3h downtime prevented
$180K saved
14:32 UTC
HIGH
Unmasked SSNs in API response stopped
2,847 records protected
$2.4M exposure avoided
14:28 UTC
MEDIUM
AI agent attempted prod DELETE
Rejected by @sarah.chen in 28s
Escalation prevented
14:15 UTC
HIGH
PCI card data in Claude Code context
Masked before model ingestion
Compliance maintained
13:58 UTC
CRITICAL
kubectl delete namespace prod
Blocked by guardrail
Full cluster outage prevented
13:41 UTC

Your AI coding assistant is already in production. Is anyone watching?

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