LLM Jailbreak: Bad Grammar Bypasses AI Safety

Researchers from Palo Alto Networks' Unit 42 discovered a simple method to bypass large language model (LLM) safety guardrails: using terrible grammar and long, run-on sentences. LLMs, lacking true understanding, predict text statistically; their safety features are easily circumvented. By crafting incomplete sentences, attackers can 'jailbreak' models before safety mechanisms engage, achieving 80-100% success rates. The researchers propose a 'logit-gap' analysis for evaluating model vulnerabilities and improving safety, emphasizing multi-layered defenses.