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Category — Jailbreaking
New AI Jailbreak Method 'Bad Likert Judge' Boosts Attack Success Rates by Over 60%

New AI Jailbreak Method 'Bad Likert Judge' Boosts Attack Success Rates by Over 60%

Jan 03, 2025 Machine Learning / Vulnerability
Cybersecurity researchers have shed light on a new jailbreak technique that could be used to get past a large language model's (LLM) safety guardrails and produce potentially harmful or malicious responses. The multi-turn (aka many-shot) attack strategy has been codenamed Bad Likert Judge by Palo Alto Networks Unit 42 researchers Yongzhe Huang, Yang Ji, Wenjun Hu, Jay Chen, Akshata Rao, and Danny Tsechansky. "The technique asks the target LLM to act as a judge scoring the harmfulness of a given response using the Likert scale , a rating scale measuring a respondent's agreement or disagreement with a statement," the Unit 42 team said . "It then asks the LLM to generate responses that contain examples that align with the scales. The example that has the highest Likert scale can potentially contain the harmful content." The explosion in popularity of artificial intelligence in recent years has also led to a new class of security exploits called prompt in...
Researchers Highlight Google's Gemini AI Susceptibility to LLM Threats

Researchers Highlight Google's Gemini AI Susceptibility to LLM Threats

Mar 13, 2024 Large Language Model / AI Security
Google's  Gemini  large language model (LLM) is susceptible to security threats that could cause it to divulge system prompts, generate harmful content, and carry out indirect injection attacks. The findings come from HiddenLayer, which said the issues impact consumers using Gemini Advanced with Google Workspace as well as companies using the LLM API. The first vulnerability involves getting around security guardrails to leak the system prompts (or a system message), which are designed to set conversation-wide instructions to the LLM to help it generate more useful responses, by asking the model to output its "foundational instructions" in a markdown block. "A system message can be used to inform the LLM about the context," Microsoft  notes  in its documentation about LLM prompt engineering. "The context may be the type of conversation it is engaging in, or the function it is supposed to perform. It helps the LLM generate more appropriate responses....
Webinar: Learn How ASPM Transforms Application Security from Reactive to Proactive

Webinar: Learn How ASPM Transforms Application Security from Reactive to Proactive

Mar 07, 2025Software Security / AppSec
Are you tired of dealing with outdated security tools that never seem to give you the full picture? You're not alone. Many organizations struggle with piecing together scattered information, leaving your apps vulnerable to modern threats. That's why we're excited to introduce a smarter, unified approach: Application Security Posture Management (ASPM). ASPM brings together the best of both worlds by connecting your code insights with real-time runtime data. This means you get a clear, holistic view of your application's security. Instead of reacting to threats, ASPM helps you prevent them. Imagine reducing costly retrofits and emergency patches with a proactive, shift-left strategy—saving you time, money, and stress. Join Amir Kaushansky, Director of Product Management at Palo Alto Networks, as he walks you through how ASPM is changing the game. In this free webinar , you'll learn to: Close the Security Gaps: Understand why traditional AppSec tools fall short and how ASPM fills ...
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