Security flaws in artificial intelligence systems—such as adversarial attacks, data poisoning, and model inversion—expose sensitive data and undermine decision-making. These vulnerabilities affect developers, enterprises, and end-users relying on AI for automation, diagnostics, or finance. Addressing them benefits cybersecurity professionals and organizations by preventing breaches, ensuring trust, and safeguarding critical AI-driven operations.
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