Black-Box Attacks - Edgentiq

Gradient-Guided Sampling: A Balanced Approach to Stronger AI Attacks

AI’s Hidden Blind Spots: When Drastically Altered Images Fool Models

AgentTypo: Exploiting Visual Vulnerabilities in Multimodal AI Agents Through Typographic Prompt Injection

Web Agents Can Be Subtly Manipulated Through Combined Visual and Textual Tweaks

Data Quality, Not Just Quantity, Shapes AI Robustness

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A New Black-Box Approach to Transferable Prompt Injection Attacks on Large Language Models

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Prompt-Only OverThinking: A Stealthy Approach to Manipulate LLM Reasoning Efficiency

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TAIGen: A Fast and High-Quality Method for Adversarial Image Generation

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Targeting Shared Vulnerabilities in 3D Models with Critical Feature Guidance

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Teaching AI to Craft Smarter Digital Deceptions: A Knowledge Distillation Approach

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Stealthy Character Attacks Exploit Transparency in NLP Systems

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AdViT: Unmasking Vulnerabilities in Interpretable Vision Transformer Systems

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DeRAG: How Short Prompts Can Hijack AI’s Information Retrieval

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Unveiling a New Vulnerability in Distributed AI: How Intercepted Edge Features Empower Adversarial Attacks

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Gen AI News and Updates

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Gradient-Guided Sampling: A Balanced Approach to Stronger AI Attacks

November 4, 2025

AI’s Hidden Blind Spots: When Drastically Altered Images Fool Models

October 23, 2025

AgentTypo: Exploiting Visual Vulnerabilities in Multimodal AI Agents Through Typographic Prompt Injection

October 7, 2025