All posts

Segregation of Duties for Claude Skills

When a single Claude skill can read, write, and delete data across multiple services, the organization pays a hidden price: accidental data exposure, regulatory fines, and loss of trust. The cost of a rogue or mis‑configured skill quickly multiplies because there is no clear boundary between who can do what. Why segregation of duties matters for Claude Skills Teams often treat an AI skill as a convenient wrapper around a set of API keys. Those keys are checked into source control, shared amon

Free White Paper

DPoP (Demonstration of Proof-of-Possession) + Claude API Security: The Complete Guide

Architecture patterns, implementation strategies, and security best practices. Delivered to your inbox.

Free. No spam. Unsubscribe anytime.

When a single Claude skill can read, write, and delete data across multiple services, the organization pays a hidden price: accidental data exposure, regulatory fines, and loss of trust. The cost of a rogue or mis‑configured skill quickly multiplies because there is no clear boundary between who can do what.

Why segregation of duties matters for Claude Skills

Teams often treat an AI skill as a convenient wrapper around a set of API keys. Those keys are checked into source control, shared among developers, and granted admin‑level access to databases, storage buckets, and internal APIs. The result is a single credential that can perform any operation the skill needs, but also any operation the skill should never perform. Without a separation of responsibilities, a mistake in prompt engineering or a compromised model can lead to unauthorized data extraction, destructive commands, or compliance violations.

Current practice: a shared credential with no guardrails

In many organizations the workflow looks like this:

  • A DevOps engineer creates a service account for the Claude skill.
  • The account receives a static secret that is stored in a configuration file.
  • The skill uses that secret to connect directly to each target system.
  • There is no per‑request approval, no audit of which prompts caused which API calls, and no masking of sensitive fields in responses.

This unsanitized state gives the skill unrestricted power. If the skill is prompted to retrieve a customer’s credit‑card number, it can do so and write the value to a log file that is later exposed. The organization loses the ability to prove who initiated the action, and the blast radius of a single mistake expands to every downstream system.

Improving identity but still missing enforcement

Moving from a hard‑coded secret to a non‑human identity, such as an OIDC‑issued token or a short‑lived service account, addresses credential rotation and reduces the risk of secret leakage. The token is scoped to a set of resources, and the identity provider can enforce least‑privilege policies. However, the request still travels straight from the Claude skill to the target service. The gateway that would inspect each call, enforce policy, and record the interaction is absent. At this stage the organization still lacks:

  • Real‑time approval for high‑risk operations.
  • Inline masking of sensitive response fields.
  • Comprehensive session recordings for later forensic analysis.
  • The ability to block disallowed commands before they reach the backend.

Those gaps mean that even with strong identity, the core security controls required for segregation of duties are not enforced.

Introducing hoop.dev as the enforcement layer

hoop.dev is a layer‑7 gateway that sits between Claude Skills and the infrastructure they need to reach. By placing the gateway in the data path, hoop.dev becomes the only place where policy can be applied. The gateway inspects every protocol‑level request, applies masking, requires just‑in‑time approval for risky actions, blocks disallowed commands, and records the entire session for replay.

Continue reading? Get the full guide.

DPoP (Demonstration of Proof-of-Possession) + Claude API Security: Architecture Patterns & Best Practices

Free. No spam. Unsubscribe anytime.

Because hoop.dev is the active component in the data path, the following enforcement outcomes are guaranteed:

  • hoop.dev records each interaction, creating a persistent audit trail that ties a specific prompt to the exact API calls made.
  • hoop.dev masks sensitive fields such as credit‑card numbers or personal identifiers before they are returned to the Claude skill.
  • hoop.dev requires a human approver for operations that exceed a predefined risk threshold, enforcing segregation of duties at the moment of execution.
  • hoop.dev blocks commands that violate policy, preventing accidental or malicious data loss.

All of these outcomes exist only because the gateway sits in the data path; the identity setup alone cannot provide them.

High‑level deployment steps

To apply segregation of duties to Claude Skills, follow these conceptual steps:

  1. Deploy the hoop.dev gateway using the provided Docker Compose or Kubernetes manifests. The deployment includes a network‑resident agent that runs close to the target services.
  2. Register each target (database, HTTP API, etc.) as a connection in hoop.dev. The gateway stores the credentials, so the Claude skill never sees them.
  3. Configure an OIDC or SAML identity provider for the Claude skill. The skill obtains a short‑lived token that hoop.dev validates on every request.
  4. Define masking rules and approval policies that reflect the organization’s segregation of duties requirements. For example, mask any field matching a credit‑card pattern and require approval for DELETE operations on production tables.
  5. Update the Claude skill’s client configuration to point to the hoop.dev endpoint instead of the raw service address. The skill now talks to the gateway, which forwards allowed traffic to the backend.

All of the detailed configuration lives in the official documentation. The getting started guide walks through the initial deployment, and the learn section explains how to author masking and approval policies.

Benefits for segregation of duties

By inserting hoop.dev into the request flow, organizations achieve true separation of responsibilities:

  • Developers can author Claude skills without granting them unrestricted access; the gateway enforces the least‑privilege boundary.
  • Security teams retain visibility into every action, satisfying audit requirements and reducing investigative effort.
  • Compliance officers gain concrete evidence that segregation of duties policies are being enforced, because each session is recorded and can be replayed on demand.
  • The risk of accidental data exposure is limited, as sensitive fields are masked before they ever reach the skill.

FAQ

Do I still need to rotate the service account secret?

Yes. The identity provider should continue to issue short‑lived tokens. hoop.dev validates each token, but rotating the underlying secret remains a best practice.

Can hoop.dev work with multiple Claude skills simultaneously?

Absolutely. Each skill receives its own identity token, and the gateway applies the same masking and approval policies per request, preserving segregation of duties across all agents.

What happens to logs if the gateway is compromised?

hoop.dev records each session and retains the audit trail in storage configured by the operator. Even if the gateway process is compromised, the recorded evidence remains available for forensic analysis.

Get involved

hoop.dev is open source and welcomes contributions. Explore the code, raise issues, or submit pull requests on the GitHub repository.

Open source

Save the open-source gateway for agent data access

Hoop is MIT-licensed infrastructure for controlling how AI agents reach production data. Star hoophq/hoop so you can inspect it, deploy it, or share it when your team starts governing agent access.

Star and save the repo →More posts