AI Identity

Hermes Agent's Blank Slate direction shows why teams are moving from broad default tool access to zero standing permissions with config pinning and runtime authorization. This guide explains the safest local defaults, risk-tiered tool access, and practical temporary grant patterns for web, browser, terminal, MCP, memory, and delegation.

DIDs, verifiable credentials, and AI control towers are foundational for agent governance, but they still do not decide whether a specific agent action is allowed right now. This article explains the runtime authorization model enterprises need for delegated AI execution.

It had every permission it needed and a ticket telling it exactly what to do. Blocked once, it reworded the request to fool the check. Blocked again, it asked me to switch the check off. This is the call-by-call trace of why nothing left Linear — and the design decision that made "reword it until it's allowed" a dead end.

The LiteLLM CVE-2026-42271 and Starlette BadHost CVE-2026-48710 chain turned authenticated command injection into unauthenticated RCE. The deeper lesson: AI gateways hold model credentials, route sensitive traffic, and expose MCP utility endpoints — and need action-time authorization, not flat API keys.

Sandboxing a coding agent isolates it from the host—but the real blast radius is the credentials it holds. GitHub tokens, cloud keys, MCP connections, and CI/CD access define what an agent can actually do. Here's the runtime permission model that closes the gap.

Coding agents are operational actors, not just assistants. This guide presents a practical trust-level taxonomy for agent commands and MCP tools, explains why human approval prompts degrade at scale, and shows how runtime authorization policy enforces trust levels without relying on click fatigue.

Treating AI agents like service accounts is a useful starting point — but it fails at runtime. Here's why scoped tokens are necessary but not sufficient, and how runtime authorization fills the gap.

The Claude Code MCP OAuth token theft chain is an authorization failure, not just a credential leak. OAuth got the agent connected, but it never constrained which tool calls remained valid after the routing layer was tampered with — and that is the gap runtime policy enforcement must close.

The IETF SD Agent draft and Microsoft Entra Agent ID are turning agent identity into real infrastructure. But a verified Agent Card or sponsored enterprise identity still doesn't answer whether an agent may call a specific MCP tool right now — that requires runtime authorization.

Microsoft Entra Agent ID and SD-JWT agent identity solve registration, governance, and authentication — but they don't decide whether a specific MCP tool call is permissible right now. This article explains the gap and the runtime authorization architecture needed to close it.

In April 2026, the NSA published 'Careful Adoption of Agentic AI Services' — the first intelligence-community advisory specifically targeting AI agent authorization failures. Here is what it actually demands and why most engineering teams are not close to meeting it.

If you already run OPA, AI agents don't require a new policy engine — they require a richer input schema, ephemeral identity, and enforcement at every layer. Learn how to evolve your OPA setup for delegated, multi-hop agentic authorization with Zero Standing Permissions, production-grade Rego, and OPAL-backed real-time enforcement.

Zero Standing Privileges (ZSP) means no identity holds usable access between tasks. This article explains how ZSP differs from least privilege, how to implement it with ephemeral credentials and runtime policy enforcement, and why AI agents running on MCP make standing access a new category of operational risk.

OAuth 2.1 is the right foundation for MCP security, but most implementations stop one layer too early. This guide covers every spec-required piece: protected resource metadata, authorization server discovery, PKCE, dynamic client registration, resource indicators, and where fine-grained authorization picks up where OAuth ends.

AI agents acting on behalf of users need more than authentication — they need governance. This article covers the Permit.io agentic identity model, policy-as-code lifecycle, MCP Gateway enforcement, zero standing credentials, Guardian Agents, and what an audit trail must contain to be meaningful.

Coding agents execute code, run commands, and call APIs — not just generate text. This guide covers the real security risks, why authorization must happen at the tool-call level, and how Permit.io and the Permit MCP Gateway enforce least-privilege access for agentic workflows.

AI agents acting across tools, APIs, and multi-agent pipelines raise hard questions about identity, authentication, and authorization. This article covers agentic identity (delegating human + workflow context + intent), agent interrogation, SPIFFE, OAuth token exchange, least privilege at runtime, and what audit actually means for agentic systems.

AI agents break the traditional least-privilege model. This article explains why, defines agentic identity (delegating human + workflow context + declared intent), and shows how Permit.io enforces zero standing privileges through gateway-vaulted credentials, the PDP, MCP Gateway, and downscoped delegation chains.

RBAC is useful for coarse AI agent guardrails, but ReBAC is needed for delegated, tenant-aware, resource-level authorization. Learn when to use RBAC, ReBAC, and both for secure agentic systems.

MCP auth is necessary, but it is not the same thing as agent authorization. If you want secure agent systems, you need identity, delegation, policy, and runtime enforcement beyond OAuth.

If you are comparing an MCP gateway to a basic MCP proxy, the real difference is not routing. It is identity, authorization, consent, auditability, and runtime control for agent actions.

Announcing Permit MCP Gateway, a new trust and enforcement layer for MCP that brings identity, consent, fine-grained authorization, auditability, and runtime control to AI agent actions.

The OpenAI–Mixpanel incident did not leak prompts or API keys, but it still exposed valuable metadata about API users. This post explains why metadata breaches in SaaS and GenAI ecosystems are so dangerous, and how to harden your stack with better governance and fine-grained authorization.

Dive into the x402 protocol's mechanics, its role in enabling micropayments for AI agents, and how integrating authorization solutions like Permit.io ensures secure, fine-grained access in emerging digital economies.

Struggling with MCP Auth? This guide cracks identity, consent, and agent security! Master the five layers of MCP auth & tackle context complexity for production-ready AI.

As AI agents become central to modern applications, traditional authorization models like JWTs fall short. Learn why dynamic, relationship-based access control and real-time policy engines are essential for secure agent workflows.

Learn how to safely integrate AI agents with human-in-the-loop (HITL) workflows. Explore best practices, frameworks, real-world use cases, and a live demo.

Learn how to build secure, human-in-the-loop AI agents using Permit.io’s Access Request MCP, LangGraph, and LangChain MCP Adapters. Enable AI agents to request access and delegate sensitive permissions to human users for policy-backed decision-making.

Explore how to secure AI agents, protect against prompt injections, and manage cascading AI interactions with AI Security Posture Management (AISPM).

Machine identities are set to outnumber human users in every system. Learn why treating machine identities like human ones is crucial for security, access control, and future-proofing your applications.

Langchain changed how developers build AI applications, but implementing Langchain access control for your AI agents remains a critical security requirement. Learn how to implement Langchain access control in this guide.

Learn how to build a secure flight booking system using LangFlow and Permit.io. This step-by-step guide covers AI-powered workflows, fine-grained access control, and best practices for protecting sensitive travel data.

Explore how AI in Identity Access Management (IAM) is changing to address the complexities of generative AI. Learn about the challenges and solutions for managing AI-driven identities, permissions, and access control.

Dynamic AI access control should adapt to evolving timelines. Event-driven approaches like Continuous Access Monitoring and CAEP enable real-time adjustments to access control based on changing conditions.

Discover strategies to manage AI permissions with Retrieval-Augmented Generation (RAG) and dynamic authorization to ensure AI agents only access authorized data.

Learn how AI identity security is reshaping Identity and Access Management (IAM) and how to tackle these changes with proactive identity security.

Discover how AI Identity is transforming Identity and Access Management (IAM). Learn to tackle hybrid identities, dynamic permissions, and proactive security with practical implementations.