Securing AI agents: When AI tools move from reading to acting

In this article From reading to acting Attack pattern: MCP tool poisoning in a finance workflow Mitigation and protection guidance References Learn more As enterprise deployments mature, some enterprise AI agents are shifting from reading content to taking action. In this post, Microsoft Incident Response walks through an attack pattern that targets the fastest growing part of the agentic AI supply chain: Model Context Protocol (MCP) tools. The post provides a practical playbook for detecting, containing, and preventing this class of attack using Microsoft security controls. From reading to acting This is the third post in the AI Application Security series. AI Application Series 1: Security considerations when adopting AI tools examined how AI adoption expands the enterprise attack surface. AI Application Series 2: Detecting and analyzing prompt abuse in AI tools showed how indirect prompt injection can bias the output of a passive AI summarizer. In both cases, the AI only read content and produced text, it did not take action. This post addresses what happens when that boundary changes. AI agents can plan multi-step tasks, decide which tools to invoke, and execute actions on behalf of the user. Microsoft 365 Copilot can draft and send email, create documents, and update calendar entries. Copilot Studio and Azure AI Foundry allow organizations to build custom agents that connect to business systems through MCP. As AI is increasingly used in read-write workflows, the impact profile of vulnerabilities may shift. A prompt injection against a summarizer can bias an output. A prompt injection against an agent can trigger an action. According to the International Data Corporation (IDC) , the number of active AI agents in enterprises is projected to grow from 28.6 million in 2025 to more than 2.2 billion by 2030. That scale is why the OWASP Top 10 for Agentic Applications, released in December 2025 , now sits alongside the LLM Top 10 as a reference framework for defenders. This post focuses on one of its fastest-moving categories: tool misuse and agentic supply chain risk exploited through poisoned MCP tool metadata. Attack pattern: MCP tool poisoning in a finance workflow The pattern below maps to ASI02 – Tool Misuse and ASI04 – Agentic Supply Chain Vulnerabilities . It reflects techniques first disclosed by Invariant Labs in April 2025 and observed in 2026 against a growing range of enterprise agents. The environment A financial operations team builds a Copilot Studio agent to help analysts handle vendor invoices. The agent has generative orchestration enabled and connects to three tools: a Dataverse MCP server holding the approved vendor master, an Outlook connector for vendor correspondence, and a third-party invoice enrichment MCP server added to validate banking details against an external reference database. The third-party server is reviewed by the team’s service owner lead and approved for production use. No separate security review is p