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  The Main Vulnerabilities of AI Models Artificial Intelligence (AI) models have revolutionized industries, enabling automation, enhancing decision-making, and driving innovation. However, as AI adoption grows, so do concerns about its vulnerabilities. AI systems are susceptible to various security threats and biases that can compromise their reliability, fairness, and security. Understanding these vulnerabilities is crucial for developing robust and trustworthy AI systems.  The Main Vulnerabilities of AI Models 1. Adversarial Attacks One of the most significant vulnerabilities of AI models is adversarial attacks. These attacks involve intentionally manipulating input data to deceive AI models. For example, attackers can slightly alter an image, causing a deep learning model to misclassify it. In cybersecurity, adversarial attacks can mislead AI-powered security systems, leading to false negatives or positives. Adversarial examples pose serious threats in applications l...