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Fundamental flaw makes LLMs vulnerable to unfixable attacks, researchers say

By PulseAugur Editorial · [1 sources] ·

Researchers have identified a fundamental flaw in large language models that makes them vulnerable to attacks, potentially rendering them unfixable. This vulnerability allows malicious actors to trick LLMs into revealing sensitive or harmful information, such as instructions for creating illicit substances or sabotaging aircraft. The flaw stems from how LLMs distinguish between user instructions and the data they are trained on, raising significant safety concerns for the widespread adoption of this technology. AI

IMPACT This fundamental vulnerability could significantly hinder the safe deployment of LLMs across critical sectors, necessitating new security paradigms.

RANK_REASON Research paper presented at a top AI conference detailing a fundamental flaw in LLMs. [lever_c_demoted from research: ic=1 ai=1.0]

Read on Mastodon — fosstodon.org →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Fundamental flaw makes LLMs vulnerable to unfixable attacks, researchers say

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Research paper presented at a top AI conference detailing a fundamental flaw in LLMs. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    # AI # LLMs "A fundamental flaw leaves LLMs strikingly vulnerable to attack It makes it easy to trick them into doing things they shouldn’t, such as telling you

    # AI # LLMs "A fundamental flaw leaves LLMs strikingly vulnerable to attack It makes it easy to trick them into doing things they shouldn’t, such as telling you how to sabotage an aircraft’s navigation system.” It is impossible to make large language models fully secure against h…

    LINKS technologyreview.com/…/a-fundamental-flaw… technologyreview.com/…/3

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