An adversarial attack is a deliberate attempt to fool an AI system with carefully crafted inputs that look normal to humans but cause the model to fail. A few altered pixels can make an image classifier mislabel a stop sign, and cleverly worded messages can trick a chatbot into ignoring its safety rules. For a bank whose fraud filter or a retailer whose product-recognition system faces motivated attackers, testing against such manipulations, known as red teaming, is essential before deployment.