Deep Learning Security - Edgentiq

Unveiling the Dual Nature of LLM Safety: A New Framework to Bypass Alignment

Revealing Adversarial Examples’ Fragility Through Occlusion

QURA: A Stealthy Backdoor Attack Exploiting Deep Learning Model Quantization

SASER: Unveiling Stealthy Stego Attacks on Open-Source LLMs

Unmasking Hidden Threats: Backdoor Vectors in Model Merging

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A Novel Approach to Neutralize Malware in Neural Network Checkpoints

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

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AI’s Hidden Weaknesses: How Adversarial Attacks Both Threaten and Protect Computer Vision

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Diffusion Models Craft Deceptive Point Clouds for Security Testing

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Stealthy Character Attacks Exploit Transparency in NLP Systems

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Generating Adversarial Faces: Exploiting Feature Space for Non-Adaptive Attacks

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Gen AI News and Updates

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Unveiling the Dual Nature of LLM Safety: A New Framework to Bypass Alignment

November 11, 2025

Revealing Adversarial Examples’ Fragility Through Occlusion

November 10, 2025

QURA: A Stealthy Backdoor Attack Exploiting Deep Learning Model Quantization

October 14, 2025