The TNO white paper on adversarial AI explores vulnerabilities in AI systems within the cyber domain. It outlines five main attack types—poisoning, backdoor, evasion, membership inference, and model stealing—each targeting different stages of the machine learning lifecycle. These attacks exploit gaps in training, deployment, and system access. While attack methods are rapidly advancing, defensive strategies remain underdeveloped. The paper stresses the need for both technical and tactical defenses, greater awareness, and research into robust, AI-resilient cybersecurity solutions to ensure safe deployment of AI in critical sectors.

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