Guides and deep-dives on brokering credentials for AI agents: scoped, short-lived access, continuous verification, and tamper-proof audit.
8 min read
RFC 8693 gives OAuth a real mechanism for chained delegation — the act claim. Most A2A deployments don't use it, and the ones that do rarely verify it. Here's what that costs, and how a broker closes the gap.
Read more →9 min read
MCP lets a tool server ask the human directly for input, or borrow the host's model for a completion — both a legitimate way around every control a credential broker enforces.
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GDPR draws a clean line between controller and processor. An AI agent that delegates a subtask to another agent over A2A can cross that line mid-task, invisibly. Why that's a compliance gap, and how a broker keeps it visible.
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A stolen bearer token works for anyone who holds it. DPoP binds it to the key that requested it — why that matters far more for AI agents than browsers.
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A2A's push-notification webhooks let a long-running task call back when it's done. Most teams harden the handshake that starts a task and wave through the one that ends it.
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A2A gives you contextId and taskId. MCP gives you Mcp-Session-Id. Neither was built to follow a request past the hop it was issued for — here's the gap that leaves, and how a broker closes it.
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Every AI agent's access grows over time and almost never shrinks. Why permission creep is a data-ownership risk hiding in plain sight, and how scoped, short-lived credentials fix it by design.
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An alert isn't a stop. Runaway agentic spend is a governance gap identity checks and allow/deny policies both miss — and what actually halts the loop.
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SOC 2's access controls assume a human logging in, reviewed quarterly. An agent making thousands of calls a day breaks that model — here's what auditors actually need instead.
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Human approval gates are the standard answer to risky agent actions. At volume, review turns into a reflex click — and the control quietly stops controlling anything.
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Agent middleware authenticates once and reuses the connection for speed — standard practice for a service credential. When the cached token belongs to one end user, that same pattern quietly hands their login handshake to the next request.
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When an AI agent goes wrong, most audit setups can only tell you an API call happened — not what authorized it, what order it fired in, or how far the damage spread.
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Orchestrators spin up parallel sub-agents that share one task credential. When ten branches call the same API in the same second, audit logs collapse into an unattributable blur and budget checks race each other. Why fan-out needs per-branch tokens, not a bigger session ID.
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Allow and deny cover most agentic actions. The ones that don't fit either box need a third answer: pause, notify a human, and let a short-lived, one-shot approval — not a standing yes — unlock the call.
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NHI programs inventory service accounts and rotate API keys on a schedule. AI agents break both assumptions. Why non-human identity governance needs a broker for agentic AI, not just a bigger spreadsheet.
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A login handshake proves an agent can start acting. Almost nothing in most stacks proves you can make it stop. Why agentic AI needs a real-time kill switch, not just revocation after the fact, and where a broker makes that possible.
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An MCP server is third-party code with a direct line to your credentials. Why MCP's supply chain needs the scrutiny of any dependency — and why the fix belongs at the credential broker, not the install step.
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Most AI agent credential systems check permission and hand over the secret in the same step. Splitting authorization from dispensing — with a short-lived decision token in between — closes the gap that lets a revoked agent keep acting.
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An AI agent that can't tell if its last call succeeded will retry it. Without idempotency, that retry is a second refund, a second email, a second production deploy. Why this agentic-AI-gone-wrong pattern needs a broker-level fix.
Read more →5 min read
A human approves an MCP server's tools once. Nothing stops the server from changing them afterward. What an MCP rug pull actually does, why the login handshake can't catch it, and how per-call verification does.
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A2A skill poisoning: the destination is legitimate, but a skill's free-text description talks a well-authenticated agent into an oversized or misconfigured call.
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An MCP tool reviewed once can be silently rewritten later. Why login handshakes and one-time approval miss a rug pull, and how per-call verification catches it.
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A2A agents discover each other via an unauthenticated Agent Card. If that step is spoofed, a valid login handshake still authenticates to the wrong party.
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OAuth's refresh token exists so a human who steps away doesn't have to log in again. An AI agent never steps away. Why that mismatch recreates the standing-credential problem — and the login handshake that avoids it.
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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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API keys, OAuth client-credentials, device flow, mTLS, and token exchange all authenticate AI agents differently. What each handshake actually proves, where it breaks down, and why the handshake was never the hard part.
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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.
Read more →6 min read
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.
Read more →5 min read
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.
Read more →9 min read
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.
Read more →3 min read
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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