Overview We often think of adversarial attacks targeting images or text, but audio models — including voice assistants, speech recognition systems, and audio classifiers — are just as vulnerable. Adversarial audio attacks exploit small, often imperceptible changes in sound to… Read More ›
Overview As synthetic media floods the internet, researchers and companies have turned to AI watermarks — invisible digital signatures embedded into AI-generated content — as a way to trace and verify authenticity. But just like DRM, these defenses are already… Read More ›
Overview AI is not just a tool for defenders — it’s now a weapon in the hands of attackers. With the rise of large language models (LLMs), adversaries can now generate functional malware, obfuscated code, and exploit payloads at a… Read More ›
Overview Phishing is no longer riddled with typos and bad grammar. Thanks to large language models (LLMs), attackers can now generate convincing, context-aware, and linguistically flawless phishing content at scale. What was once a human-limited social engineering tactic is now… Read More ›
Overview Modern AI systems don’t emerge from a vacuum — they’re built on layers of dependencies: public datasets, third-party model weights, code libraries, pre-trained embeddings, and cloud APIs. This complex supply chain introduces a critical risk: AI supply chain attacks… Read More ›
Overview Computer vision models are remarkably powerful — they detect tumors, unlock your phone, and power autonomous vehicles. But what if you could fool them with a few strategically placed pixels? Welcome to the world of adversarial examples — a… Read More ›