Security Testing for AI Systems: Vulnerabilities and Countermeasures (heise.de)

• AI systems are vulnerable to attacks via manipulated training data and adversarial examples.
• Penetration tests and specialized security audits can uncover weaknesses.
• The article emphasizes the need for regular security reviews in AI development processes.

"The article provides an overview of security vulnerabilities in AI systems, especially through manipulated training data and faulty models. It describes effective testing methods such as penetration testing and adversarial testing to detect attacks and make systems more robust. The goal is to raise awareness of AI vulnerabilities and present practical testing approaches."