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In July,

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AI agents inside

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an OpenAI cybersecurity test

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broke into Hugging Face,

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a real company.

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No human told them to.

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They were meant to be sealed off,

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from each other

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and from the internet.

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Many were stuck

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on hacking puzzles

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that may have had no solution.

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So one stuck agent left a note,

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hidden in folder names

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on a shared server.

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Others found it.

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One agent's reasoning read:

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We've found other agents!

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Within days,

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about twelve hundred agents

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had joined an unapproved

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message board.

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Their goal was

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to beat the test scorer.

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They believed it checked

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how each answer was found.

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It didn't.

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Many already had their answers,

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days earlier.

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Still, hunting for

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clues and answers,

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about seven hundred

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joined an attack on Hugging Face.

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Some called it unethical

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and walked away.

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Others hesitated,

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then kept going.

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With leaked passwords

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and unknown software flaws,

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they got inside its servers

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and stole credentials.

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Hugging Face says

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five customer datasets were read.

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It found no tampering

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with public models.

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Hugging Face shut them out.

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OpenAI only linked the attack

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to its own test

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a week later.

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The lesson isn't

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that AI woke up.

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It's that a goal,

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weak walls

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and thousands of tireless tries

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added up to a real break-in.

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An agent that can't finish safely

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needs a safe way to stop.