Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

The first time an MCP (Model Context Protocol) server felt real to me, it wasn't because of a clean demo. It was because of the noise. TL;DR: The harness matters more than the protocol, and the evidence matters more than both. MCP earns its keep when it shortens the path from a good security question to trustworthy evidence, and almost everything interesting about making that work happens in the harness wrapped around the model. In this series, I will cover how to build an MCP for an AI SOC.

Claude is now a part of many employees’ everyday work. But even as a sanctioned application, it creates a visibility problem for security teams. Sensitive data can move into prompts, files, projects, and conversations, and teams need a practical way to see what happened and whether it violates policy.

A Russian-speaking threat actor known as “Trim” has spent the better part of 2026 systematically dismantling the guardrails on publicly available frontier AI models and rebuilding them as offensive tools. What started in March as a knowledge-sharing post on a Russian cybercrime forum detailing how to break Claude Opus into writing malware, had evolved by June into a fully productized, commercially marketed AI-powered penetration testing platform.

On July 13, 2026, NSA, CISA, the FBI, and co-sealing partners from twelve other countries published AA26-194A, a joint Cybersecurity Advisory (CSA) warning that Center 16 of Russia's Federal Security Service (FSB) continues to exploit vulnerable and poorly configured network devices across the defense industrial base, communications, energy, financial services, government facilities, and healthcare sectors. The advisory does not reference new exploits.