5 Things You Need to Know About Securing AI-Native Software
5 Things You Need to Know About Securing AI-Native Software
2 PagesThis guide explains the key risks and considerations in securing AI-native applications. It defines agentic systems as autonomous systems capable of multi-step decision-making and highlights new threats such as data poisoning, package hallucination, and agent misuse. The tables on pages 1–2 show where risks originate—models, APIs, and data—and what can go wrong in each area. It also introduces essential capabilities like AI-BOM visibility, policy guardrails, and telemetry. The key takeaway is that securing AI-native software requires understanding dynamic system behavior and implementing controls across models, data, and interactions—not just code.
