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.
Discover how Fabrix combines deterministic matching, heuristics, and AI to power reliable access reviews, risk scoring, and compliance to unify fragmented user accounts into a single, accurate identity.
Access decisions shouldn’t rely on guesswork. This research report shows how identity intelligence backed by statistical analysis uncover real entitlement patterns, helping teams review access faster, more accurately, and with far better context.
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.
A real-world benchmark evaluating how leading large language models perform on enterprise access review decisions—measuring not just correctness, but the quality and defensibility of their reasoning.
Raz Rotenberg, CEO of Fabrix Security, explains why the 2026 CrowdStrike, AWS & NVIDIA Cybersecurity Startup Accelerator marks a meaningful shift for identity security.
In this Identity Jedi Podcast episode, Fabrix CEO Raz Rotenberg explores how AI is reshaping identity security, why legacy IAM is falling behind, and what the future demands.
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.
