AI security in 2024: What’s new?

The rapid evolution of AI technology poses significant security risks, including deepfakes and AI-powered phishing attacks, which can be difficult to detect and defend against. As AI becomes increasingly integrated into various systems, its potential vulnerabilities are expanding, making it crucial for organizations to develop a comprehensive AI security strategy. Current vulnerabilities include prompt injection, data biases, and zero-day attacks, and mitigations such as robust system prompts, internal testing, crowdsourced testing, and continuous vulnerability assessment are essential to protect against these risks. The growing use of open-source models also introduces new risks, including the potential for threat actors to exploit them. Governments around the world are starting to regulate AI development and deployment, with regulations such as the EU's AI Act and the US Executive Order 14110 aiming to ensure safe model development and rollout. To get started with AI security, organizations should identify current risks, set up initial defenses, and consider long-term robust defenses through red teaming, crowdsourced security, and continuous vulnerability assessment.

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