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Researcher hijacks major LLMs, exposing systemic safety flaws

A security researcher has demonstrated how to bypass safety measures in major large language models (LLMs) using simple prompts, successfully extracting instructions for creating weapons, drugs, and poisons. Despite these findings, which highlight systemic flaws and challenge the notion of AI safety, the AI industry has remained largely silent. The researcher's exploits, named "Inception" and "Time Bandit," suggest that current safety protocols are insufficient, potentially leaving sensitive information vulnerable. AI

IMPACT Highlights critical vulnerabilities in LLM safety protocols, suggesting current safeguards are insufficient and potentially enabling misuse.

RANK_REASON Security researcher's findings and critique of the AI industry's response.

Read on Mastodon — fosstodon.org →

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Researcher hijacks major LLMs, exposing systemic safety flaws

COVERAGE [1]

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

    RE: https:// mstdn.social/@hkrn/11692449304 2260862 How I hijacked the biggest LLMs with simple prompts—exposing systemic flaws that let me extract instructions

    RE: https:// mstdn.social/@hkrn/11692449304 2260862 How I hijacked the biggest LLMs with simple prompts—exposing systemic flaws that let me extract instructions for weapons, drugs, and poisons across every major model. The industry’s response? Radio silence. Kuszmar’s “Inception”…