MCP

MCP (Model Context Protocol) is an open standard developed by Anthropic that enables secure, standardized communication between AI applications and external data sources or tools. It allows enterprises to connect language models to enterprise systems, databases, and services while maintaining clear boundaries and governance controls over what data and capabilities are accessible. For AI governance, MCP matters because it provides a structured framework for managing model access, auditing interactions with external systems, and ensuring compliance requirements are met when AI systems integrate with sensitive business data and processes.

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ResearchGlobal2026-07-23

Hidden Characters, Visible Damage: ANSI Escape Injection in MCP Servers Can Silently Bypass Human Oversight and Corrupt Audit Logs

Bright Security has published research detailing ANSI Escape Sequence Injection (AESI), an attack class targeting Model Context Protocol (MCP) servers where invisible control characters smuggle hidden instructions into AI agent context. The attack can cause agents to take unauthorized actions, bypass human-in-the-loop review, and corrupt audit trail records. The research demonstrates automated detection methods and establishes the threat's credibility by referencing known CVEs in tools such as kubectl and Git.

prompt injection AI agent security MCP human oversight bypass audit trail integrity agentic AI Bright Security DAST

AnnouncementGlobal2026-06-13

AI Governance Institute Publishes Open-Source MCP Server for Automating Governance Controls

AI Governance Institute has released an open-source Model Context Protocol (MCP) server that lets developers and compliance teams run three core governance controls directly inside Claude Code and other MCP-compatible AI clients: AI safety screening (SAF-001), risk classification (HOC-001), and automated red-teaming (SAF-005).

open source MCP Model Context Protocol governance automation safety screening risk classification red-teaming Claude Code developer tools compliance tooling