Top 10 AI Security Risks Every Developer Must Understand

As AI becomes central to modern software development, understanding its vulnerabilities is crucial. Developers must be aware of security threats that can compromise AI integrity and user trust. Key risks include data poisoning, adversarial attacks, and model inversion, which manipulate or extract sensitive model data. Additionally, challenges like bias, unauthorized access, and lack of explainability can impact fairness and transparency. By identifying and mitigating these risks early, developers can build AI systems that are not only smart—but secure and ethical.