How AI Penetration Testing Helps Prevent Adversarial Attacks and Data Poisoning

Artificial intelligence and machine learning systems are now embedded in critical business processes, from fraud detection and healthcare diagnostics to recommendation engines and autonomous systems. As adoption grows, so do the risks associated with these technologies. Unlike traditional software, AI systems rely heavily on data and complex models, making them vulnerable to unique attack vectors such as adversarial manipulation and data poisoning. These threats can silently compromise decision-