An executive-level introduction to agentic security and governance, designed to help CISOs understand emerging AI agent risks and prepare for adoption.
Geordie AI selected for monitoring and governing AI agents in real time.
A remote code execution vulnerability in Claude Desktop Extensions received a CVSS 10.0 score this week. Looking at the technical requirements for exploitation reveals something more nuanced - and more instructive for agentic AI governance.
Security researchers disclosed a tool chaining vulnerability in Claude Desktop Extensions rated CVSS 10/10, but this represents a known risk class in agentic AI systems – not a novel attack. We assess this as Medium severity and recommend organizations treat it as a governance opportunity for AI tooling extensions.
Eight high-to-critical n8n vulnerabilities disclosed in February 2026 invalidate earlier patching guidance. This advisory explains which versions are affected and why upgrading to n8n 2.5.2 or higher is now required.
Why OpenClaw matters less as a vulnerability story and more as a signal that personal autonomous agents have arrived.
A practical, deployment-level guide to patching recent mcp-server-git CVEs - explaining how uvx caching, pip installs, and outdated Docker images can leave systems vulnerable, and how to verify you’re actually fixed.
A practical breakdown of recent n8n vulnerabilities, explaining exposure, risk, and how to choose the right remediation path.
Critical vulnerability in n8n workflow automation allows authenticated attackers to achieve remote code execution through Git node exploitation
Authenticated attackers can escape n8n's Pyodide Python sandbox to execute arbitrary system commands with host privileges.
Critical unauthenticated remote code execution vulnerability in n8n workflow automation allows attackers to exploit content-type confusion in Form webhook file upload processing to read arbitrary files, steal credentials, and execute arbitrary code on the server.
Critical remote code execution vulnerability in n8n workflow automation platform allows authenticated users to execute arbitrary code on the server through specially crafted workflow expressions that escape the sandbox isolation.
Geordie won the Black Hat Europe 2025 Startup Spotlight. Read the recap on why scaling AI agents needs continuous visibility, behavioural observability, and real-time control.
What the next Model Context Protocol (MCP) release means for enterprise security and risk teams running AI agents in production.
ACE moves enterprise AI governance beyond static prompts to living playbooks. This research note explains the model, why prompts don't scale, and where enterprises can apply it today.
The autonomous nature of AI agents requires purpose-built agentic AI governance platforms. These complement MCP gateway infrastructure with behavioural observability, contextual risk assessment, and dynamic intervention capabilities.
As AI Agents evolve into autonomous actors, securing them requires techniques beyond identity and access controls. This article explores how taint analysis can extend visibility into agent workflows, uncover hidden risks, and strengthen enterprise AI security.
AI adoption is accelerating, but trust and accountability are essential. Learn how explainability, observability, and behavioural oversight help security teams meet regulations, manage risk, and scale AI Agents with confidence.
Building on research from Berkeley, this article outlines five barriers to enterprise AI adoption and the AI governance best practices to overcome them with visibility and accountability.
Enterprises are experimenting with AI agents, but scaling safely requires enterprise AI governance. This guide outlines how to move AI adoption from experimentation to enterprise-wide deployment with clarity, governance, and trust.
We started Geordie to build the governance layer for AI agents. By managing posture, observing behaviour, and providing contextual controls with audit-ready evidence, we make AI agent adoption safe, transparent, and enterprise-ready.
AI adoption is accelerating, but not every investment is safe. Risk mapping gives security and business leaders visibility to evaluate AI tools, weigh business impact against exposure, and make confident, accountable decisions that balance innovation with resilience.
AI Agents aren’t just software. They make decisions that can reshape your business. Left unchecked, that power creates new forms of risk. This guide helps executives cut through the hype and focus on visibility, governance, and accountability.
AI Agents can’t be black boxes. Leaders need clear visibility into how they operate to manage risk, meet compliance, and enable safe innovation across the enterprise.
APIs, MCPs, and A2A form the foundation of AI Agent systems, yet their roles are often fragmented. This article explains how they connect, align, and collaborate, giving leaders the clarity to evaluate, govern, and scale AI adoption with confidence.
Building AI Agents promises speed and scale, but developers know the pitfalls. Explore their insights on risks, friction points, and the steps leaders can take to enable safe, resilient adoption.
Endpoint controls like EDR and XDR remain critical to enterprise defense, but they weren’t built for AI Agents. As these systems operate beyond traditional endpoints, leaders need new approaches to gain visibility, reduce risk, and extend security with confidence.
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