By joining Silverfort, Fabrix's vision expands beyond AI-native decisioning into real-time runtime enforcement, creating a new autonomous identity security model that evaluates and enforces every access decision instantly – across humans, machines, and AI agents.
Most identity risks aren’t caused by missing controls, but by assumptions that don’t hold in practice. As authentication spans multiple systems, “unknown-unknowns” emerge; risks that break no rule and trigger no alert, yet quietly undermine security.
In this final part, we move from mechanisms to guarantees, showing what security properties AI agents truly gain once information-flow control is enforced at the planner level.
Raz Rotenberg, CEO of Fabrix Security, explains why the 2026 CrowdStrike, AWS & NVIDIA Cybersecurity Startup Accelerator marks a meaningful shift for identity security.
This article explains and contextualizes the Microsoft Research paper Securing AI Agents with Information-Flow Control, focusing on how planners, memory, and labels shape safe agent behavior.
RAG moves AI in IAM from theory to action. This blog breaks down practical use cases and the architecture needed to build safe, compliant, and effective IAM agents.
RAG keeps AI in Identity and Access Management accurate and reliable. It ensures decisions are based on real, up-to-date data, not guesses or outdated information.
Access approvals in large organizations have turned into an “approve all” reflex — endless requests, no context, and mounting risk. AI Agents are changing that. By analyzing context, peer behavior, and usage data, they make access decisions that are consistent and explainable.
