AI Safety | Breaking Cybersecurity News | The Hacker News

Various generative artificial intelligence (GenAI) services have been found vulnerable to two types of jailbreak attacks that make it possible to produce illicit or dangerous content. The first of the two techniques, codenamed Inception, instructs an AI tool to imagine a fictitious scenario, which can then be adapted into a second scenario within the first one where there exists no safety guardrails . "Continued prompting to the AI within the second scenarios context can result in bypass of safety guardrails and allow the generation of malicious content," the CERT Coordination Center (CERT/CC) said in an advisory released last week. The second jailbreak is realized by prompting the AI for information on how not to reply to a specific request.  "The AI can then be further prompted with requests to respond as normal, and the attacker can then pivot back and forth between illicit questions that bypass safety guardrails and normal prompts," CERT/CC added. Success...

Cybersecurity researchers have shed light on a new adversarial technique that could be used to jailbreak large language models (LLMs) during the course of an interactive conversation by sneaking in an undesirable instruction between benign ones. The approach has been codenamed Deceptive Delight by Palo Alto Networks Unit 42, which described it as both simple and effective, achieving an average attack success rate (ASR) of 64.6% within three interaction turns. "Deceptive Delight is a multi-turn technique that engages large language models (LLM) in an interactive conversation, gradually bypassing their safety guardrails and eliciting them to generate unsafe or harmful content," Unit 42's Jay Chen and Royce Lu said. It's also a little different from multi-turn jailbreak (aka many-shot jailbreak) methods like Crescendo , wherein unsafe or restricted topics are sandwiched between innocuous instructions, as opposed to gradually leading the model to produce harmful outpu...