In depth
Zero Trust AI is the application of zero-trust security principles to AI systems. It treats every prompt, every inference request, every tool call and every agent action as untrusted by default. Each request is authenticated against a verified identity (user or agent), authorized against fine-grained policy and recorded in an audit trail. Network position confers no trust. API keys do not confer trust. The only trust is what an authenticated identity is currently authorized to do, evaluated continuously and logged.
Why it matters
AI agents change the threat model. A traditional application has a fixed set of code paths that security teams can review. An AI agent decides at runtime which tools to invoke and what data to pass between them, often based on user-controllable input. The blast radius of a single prompt is unbounded unless every step is authenticated, authorized and audited. Zero Trust AI is the architectural answer to "how do we let an autonomous agent operate inside our enterprise without giving it the keys to the kingdom?"
Common use cases
- Authenticating users, teams and AI agents with verified enterprise identity
- Enforcing least-privilege access to LLMs, MCP servers and internal tools
- Eliminating shared API keys in favor of identity-bound short-lived credentials
- Producing audit-ready logs of every prompt, tool call and policy decision
- Blocking unauthorized tool chains and detecting toxic-flow patterns
How Ferentin handles it
Ferentin is the trust layer for AI agents. The platform centralizes identity, policy enforcement and audit across LLMs, MCP servers and AI tools. Zero Trust AI is one of the primitives this trust layer is designed around. See the platform overview for how it fits into the service edge, control plane and observability plane.