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Using AIagentssecurely.

AI agents plan several steps on their own and call tools along the way: they read files, write emails, change code or query databases. That turns a wrong or manipulated answer into a wrong action. This guide classifies the key risks according to OWASP and shows how to limit permissions, require approval for consequential actions, treat third-party content as untrusted, vet MCP servers and run agents in isolation and traceably. It ends with a checklist for the move into production.

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Using AI Agents Securely: Permissions, Approvals, MCP Servers and Logging

Format
PDF, A4
Length
8 pages
Size
104 KB
Updated
Oct 25, 2026
Sources
8
Usage
Redistribution in unchanged form permitted
Read as a Web Page

WHO IT IS FOR

Who This
Is for.

Risks according to OWASP, principles for permissions and approvals, vetting and isolating MCP servers, a three-stage rollout and a checklist before production.

  • IT management and IT security who approve and operate AI agents
  • Development teams that build or integrate agents, tools or MCP servers
  • Business units planning agents with access to email, files or business applications
  • Management deciding on use and limits

7 SECTIONS

What Is
Inside.

Every technical statement in the document names its source. The revision date appears on every page.
  • 01

    What makes agents riskier than chat

    Agents act: the key risks according to the OWASP Top 10 for LLM Applications 2025 and the Top 10 for Agentic Applications 2026.

  • 02

    Six principles for permissions and approvals

    What OWASP recommends against excessive agency and prompt injection, as rules for your agents.

  • 03

    Identities and credentials

    Dedicated, narrowly scoped and short-lived access instead of shared administrator accounts.

  • 04

    Vetting and operating MCP servers

    The Model Context Protocol connects agents to tools; every server is code with access. Here is how to vet one.

  • 05

    Example: how a tool implements the principles

    Claude Code features according to Anthropic’s documentation, as an example for vetting any agent tool.

  • 06

    Rollout in three stages

    Expand autonomy step by step and review continuously, each stage with logs and clear accountability; a TOMORIS recommendation.

  • 07

    Checklist before production

    To tick off before an agent works with real data and systems.

EXCERPT

Six principles for permissions and approvals

  1. Limit tools to what is necessary

    Offer only the extensions the agent needs for its task, and within them only the necessary functions: an agent that summarizes emails needs to read, not send or delete. Avoid open-ended tools such as arbitrary shell commands or URL fetches (OWASP LLM06, mitigations 1 to 3).

  2. Minimize permissions

    Give each tool only the permissions it needs, for example read access to one table instead of the whole database, and run it in the context of the respective user (LLM06, mitigations 4 and 5).

  3. Require approval for consequential actions

    A human confirms high-impact actions before they are executed: sending, deleting, paying, changing permissions, publishing (LLM06, mitigation 6; LLM01, mitigation 5).

  4. Do not leave authorization to the model

    The target system decides according to its own rules whether an action is allowed, not the language model. Every request made through a tool is checked there against the security policy (LLM06, mitigation 7: complete mediation).

  5. Treat third-party content as untrusted

    Websites, documents, emails and tool descriptions from MCP servers can contain instructions. They are processed separately and labeled, and must not trigger actions without review (LLM01, mitigation 6; MCP specification).

  6. Log and limit

    Log and monitor tool calls and actions in target systems, and limit rates and budgets so that misbehavior is noticed before major damage occurs (LLM06; OWASP ASI02, mitigation 5).

An example from OWASP LLM06: an assistant that summarizes emails is built with an extension that can only read, signs in with an OAuth grant limited to read-only scope, and every email it drafts is sent only by the human after review.

SOURCES

Supported
by Sources.

  1. OWASP Top 10 for LLM Applications 2025: LLM06 Excessive Agency (opens in a new tab)Causes, mitigations 1 to 7, limiting through logs and rate limits, email assistant example
  2. OWASP Top 10 for LLM Applications 2025: LLM01 Prompt Injection (opens in a new tab)direct and indirect prompt injection, mitigations 4 to 6
  3. OWASP Top 10 for Agentic Applications for 2026 (December 9, 2025) (opens in a new tab)Least Agency, ASI01 to ASI04 and ASI10 with mitigations
  4. Model Context Protocol, specification 2026-07-28 (opens in a new tab)Section Security and Trust & Safety
  5. Model Context Protocol: Security Best Practices (2026-07-28) (opens in a new tab)Token Passthrough, Local MCP Server Compromise
  6. Model Context Protocol: Local Server Security (2026-07-28) (opens in a new tab)Provenance, tool descriptions, isolation, credentials, network, checklist
  7. Anthropic: Claude Code Security (opens in a new tab)Permissions, sandbox, prompt injection, MCP, team security
  8. Regulation (EU) 2026/1744 (Digital Omnibus Regulation on AI) (opens in a new tab)new Art. 4 of Regulation (EU) 2024/1689, in force since July 27, 2026

This guide is a TOMORIS recommendation based on the sources listed. Product features are described according to vendor documentation as of October 25, 2026, and may change. It does not replace a security test or legal advice.

YOUR NEXT STEP

From Paper
to Practice.

We review with you what is already implemented in your environment and put the rest into practice: as a project with EXPERTS or as ongoing operations with GRID.