Blog
Insights & Deep Dives
Technical perspectives on AI agent governance, behavioral analysis, and security architecture from the team building MITRITY.
Securing the Swarm: MITRITY Announces Native Kubernetes & Istio Mesh Governance for Agentic AI
Enterprise teams are deploying AI agents as microservices in Kubernetes — and Istio secures the network, but it doesn't speak AI intent. The MITRITY Mesh Authorizer injects intent-based, zero-trust governance directly into the Istio data plane via Envoy ext_authz: zero-code, SPIFFE-bound identity, delegation-chain enforcement on east-west traffic, and opt-in per-agent egress control.
You Know What's In Your Software. But Do You Know What Your AI Agents Are Doing? Enter the AIBOM.
Traditional SBOMs list the static libraries you ship — but autonomous AI agents discover MCP servers and invoke tools at runtime, far beyond any static manifest. The AI Bill of Materials (AIBOM) is a live, runtime inventory of every tool and MCP server your agents actually invoke, with drift advisories, an automatic risk overlay, and full traceability.
The Multi-Agent Blind Spot: How to Stop AI-to-AI Privilege Escalation
When agents collaborate, a compromised low-privilege bot can weaponize a high-privilege peer to execute actions it could never authorize directly. Traditional security only sees the last actor in the chain. Here's why governing a multi-agent swarm requires lineage and privilege intersection — and how MITRITY's delegation engine blocks AI-to-AI privilege escalation inline.
Getting Started with Intent-Aware Governance: A Practical Walkthrough
A practical guide to implementing AI agent governance without sacrificing development velocity — backed by two open-source demonstration agents you can run in minutes.
Why Your AI Agents Shouldn't Hold the Keys to the Kingdom
Pasting permanent credentials into an agent's config is the modern equivalent of leaving the master key under the doormat. Here's why agents should borrow secrets, not own them — and how just-in-time leases shrink the attack surface to seconds.
Securing the Agentic Stack: Privacy-First Threat Intelligence for AI
Traditional threat intel relies on IPs and file hashes. AI agents need something different. Here's how MITRITY built behavior-based, privacy-first threat intelligence designed specifically for the unique vulnerabilities of autonomous agents.
Your Customer Service Agent Just Gave Away Your Pricing Strategy
AI agents handling customer interactions have access to the most sensitive data in your organization — customer PII, account details, internal policies, and business logic. Without governance, they will leak it, one helpful response at a time.
When Your AI Agent Reprices Your Entire Catalog at 2 AM
AI agents are transforming e-commerce operations — managing inventory, adjusting prices, and fulfilling orders autonomously. Without real-time governance, a single miscalculation can wipe out margins, oversell inventory, or ship orders to the wrong addresses.
Your Payment Agent Just Issued 200 Refunds to the Same Account
AI agents processing payments, managing refunds, and handling billing disputes operate in the highest-stakes environment in your stack. Without inline governance, a single compromised or misconfigured agent can drain funds, expose card data, and create compliance violations that take months to remediate.
Intent-Aware Governance: Why Autonomous AI Agents Need a New Control Model
AI agents are autonomous, fast, and increasingly powerful. Traditional security tools were not built for systems that reason, adapt, and act independently. Intent-aware governance is the control model designed for this reality.
Real-Time Behavioral Drift Detection for Autonomous Agents
A technical deep-dive into the ML pipeline behind sub-millisecond behavioral drift detection — from edge-deployed DriftGuard models to centralized TrustGraph threat analysis.
Shared Threat Intelligence Without Shared Data: Privacy-First Cross-Tenant Protection
How MITRITY enables cross-tenant threat intelligence for AI agent attacks without exposing any tenant's data — using behavioral hashing, anonymized contribution, and tenant-scoped matching.