Researchers tested an online store customer service assistant, bypassing guardrails and leaking the system prompt
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A security researcher conducted de-alignment testing on a backpack store's LLM assistant. By embedding instructions in product name tokens within a recommended backpack list, they successfully bypassed its two-layer guardrails of prompt and output. The assistant had no internet access and no programming capability, but the researcher repeatedly broke through the output filtering using ASCII encoding, acrostics, and ELITE language, and extracted the System Prompt configuration. Based on this, the researcher suggested that LLM assistants need focused protection, as cybercriminals are already eyeing such models.
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- El lado del mal / Chema AlonsoPerturbation and de-alignment testing of a backpack store's AI assistant
A security researcher conducted de-alignment testing on a backpack store's LLM assistant. By embedding instructions in product name tokens within a recommended backpack list, they successfully bypassed its two-layer guardrails of prompt and output. The assistant had no internet access and no programming capability, but the researcher repeatedly broke through the output filtering using ASCII encoding, acrostics, and ELITE language, and extracted the System Prompt configuration. Based on this, the researcher suggested that LLM assistants need focused protection, as cybercriminals are already eyeing such models.
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