AI is a powerful security tool, but not the final authority

The rapid advancement of AI has accelerated software development, automation, and cyberattacks. It helps organizations analyze threats faster, prioritize risks, and reduce the workload of security teams. However, AI should not be the final authority on whether software is allowed to run.

Most modern security tools rely on probabilistic models that estimate how likely a file or activity is to be malicious. While this approach is effective for detection and investigation, it is not reliable enough for critical enforcement decisions.

Today, attackers generate constantly evolving malware, while developers increasingly rely on AI-generated code and open-source components without manual review. In this environment, identifying risk is no longer sufficient to prevent attacks.

This is why the Zero Trust for Code approach is gaining importance. Software should not be executed until its behavior has been evaluated against security policies. Decisions must be explainable, consistent, and auditable.

Recent incidents, such as the LiteLLM supply chain compromise, demonstrate that detecting malicious code after it has already run is often too late - the damage has already been done.

AI remains a powerful tool for identifying patterns, analyzing large datasets, and accelerating investigations. However, the final decision on whether software should execute should be based on deterministic, policy-driven controls rather than probabilistic predictions.

The future of cybersecurity lies in combining AI-powered analysis with enforceable security policies, enabling organizations to innovate quickly without compromising security or trust.