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A fundamental flaw leaves LLMs strikingly vulnerable to attack

MIT Technology Review AIThursday, July 30, 2026 at 10:15 AM

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A fundamental flaw leaves LLMs strikingly vulnerable to attack
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It is impossible to make large language models fully secure against hacks because of a fundamental flaw in how they work, a team of researchers argue in a paper presented at the International Conference on Machine Learning, a top AI conference, this month.

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RedScroll Briefing

Extractive editorial brief — not a reprint of the original

What happened

It is impossible to make large language models fully secure against hacks because of a fundamental flaw in how they work, a team of researchers argue in a paper presented at the International Conference on Machine Learning, a top AI conference, this month.

Why it matters

AI developments move capital, regulation, and competitive advantage across the tech stack.

Background

MIT Technology Review AI reported on this under ai. RedScroll surfaces the signal with an extractive brief — not a reprint of the original article. Read the source for full reporting.

Timeline

  1. MIT Technology Review AI published: A fundamental flaw leaves LLMs strikingly vulnerable to attack

  2. Story is in today’s RedScroll edition. Follow the original source for updates.

Economic impact

Secondary effects may show up in markets and supply chains linked to Fundamental and Flaw.

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MIT Technology Review AI

Original reporting by MIT Technology Review AI. RedScroll provides an extractive briefing only.