Description:
AI systems face threats such as prompt injection, data leakage through APIs, model tampering, and poisoned training data, which can derail decisions and expose secrets. Organizations must map attack surfaces across models, data pipelines, and third‑party integrations to gauge real risk, including AI security threats.
Staying vigilant, adopting layered defenses, and testing with realistic attack scenarios helps teams stay ahead without slowing innovation.
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