AI Security: Defending Probabilistic Systems & New Threats

Security engineers must now defend probabilistic systems, not just deterministic software. This means understanding new AI threat vectors like prompt injection and data poisoning. The most destructive AI-based attacks exploit boundaries where untrusted input meets system instructions. AI systems need to be treated as unpredictable, goal-driven actors. This requires continuous behavioral validation and supervision, rather than static security rules. Traditional security skills are still foundational, but they must be extended with AI-specific capabilities. These include AI threat modeling and adversarial testing. Success in AI security depends on building resilience and visibility. Organizations need to invest in specialized monitoring and cross-functional collaboration between security and machine learning teams. This is crucial for incident response with systems that learn and adapt. The bottom line is that AI is creating a new generation of sophisticated attacks, challenging basic ideas about threat detection and prevention.