Guides and deep-dives on brokering credentials for AI agents: scoped, short-lived access, continuous verification, and tamper-proof audit.
8 min read
An AI agent's login handshake proves which agent is calling. It rarely proves who the agent is acting for. Why that gap matters for A2A and MCP delegation chains, and how a broker closes it.
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Teams build detailed logs and traces to catch AI agents gone wrong — then those same logs end up holding the credentials and customer data they were meant to protect. Here's the redaction gap, and how to close it.
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From a coding agent that deleted a production database to a chatbot that invented a policy — six real AI agent incidents and the credential, authorization, and audit gaps behind each.
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Every AI agent outlives the task it was built for. Why agent offboarding is a governance and data-ownership gap, not just security hygiene, and how a credential broker makes revocation instant.
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An AI agent can pass every login handshake and still be tricked into calling your cloud metadata endpoint. How SSRF turns a legitimate agentic action into an incident, and where the guard actually has to live.
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Private data, untrusted content, and an exfiltration path — the 'lethal trifecta' behind agentic AI gone wrong, and why credential-layer observability closes it.
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A malicious tool description can turn a well-authenticated AI agent into a confused deputy. How MCP tool poisoning works, why login handshakes alone don't stop it, and the broker pattern that does.
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MCP's OAuth handshake proves an agent connected to your server. It says nothing about what a tool description talked the agent into doing next. Why MCP incidents keep happening at the tool layer, and how a broker closes the gap.
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A valid MCP token doesn't mean a wise call. The confused deputy problem in agentic AI, and how a broker enforces policy on every tool call, not just the connection.
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A2A lets one AI agent configure another system, not just call its tools — a bigger blast radius than MCP. Here's the handshake and credential carve-out that makes it safe.
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The A2A protocol standardizes how AI agents authenticate to each other. What the handshake proves, what it doesn't, and why every call still needs a broker behind it.
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Every team wiring an AI agent to an API mints its own credential. Nobody centrally counts them. Here's why shadow AI agents are a data-ownership and traceability problem, not just a security one — and how a broker fixes it.
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AI agents rarely fail by being unauthenticated. They fail by losing track of whose data they're touching. Three real failure patterns in agentic AI, and how a credential broker enforces data ownership on every call.
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Agentic actions rarely stay inside one agent. Here's the difference between observability and traceability for multi-agent AI, and how to trace one task across every hop it triggers.
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A sloppy login handshake is how an AI agent ends up reading data it never should have touched. What authentication and data ownership need to look like for agentic AI — and where a credential broker fits.
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1Password acquired Apono and shipped a Credential Broker for AI agents. Standing keys are over — here's why, and where brokering at issuance differs from brokering every call.
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ISO/IEC 42001 asks you to govern what your AI systems do. A credential broker turns several Annex A controls into enforced policy — here's the honest mapping.
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Auth0 is an identity platform for users and services; Fullmakt is a credential broker for AI agents. How the two differ — and how they work together.
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How the Model Context Protocol and OAuth 2.1 fit together to let AI agents call your tools with scoped, revocable access — and where a broker fits in.
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When an AI agent acts on your behalf, you need to answer which agent did what, when, and for whom. Here's how a cryptographically chained audit log makes that answer trustworthy.
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Why handing an AI agent a long-lived API key is a liability, and how short-lived, scoped credentials give agents exactly the access they need — and nothing more.
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