Vulnerabilities introduced during the AI model training phase: data poisoning, backdoor injection in the dataset, model inversion to extract training data, membership inference attacks, and manipulation of learning parameters. Includes adversarial training techniques, dataset validation, data supply chain protection, and hardening of the training process for machine learning and deep learning models.