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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.
Free PDF · Guide
Using AI Agents Securely: Permissions, Approvals, MCP Servers and Logging
- Topic
- AI in Business
- Format
- PDF, A4
- Length
- 8 pages
- Size
- 104 KB
- Updated
- Oct 25, 2026
- Sources
- 8
- Usage
- Redistribution in unchanged form permitted
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.
- 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
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).
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).
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).
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).
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).
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.
- 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
- OWASP Top 10 for LLM Applications 2025: LLM01 Prompt Injection (opens in a new tab)direct and indirect prompt injection, mitigations 4 to 6
- 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
- Model Context Protocol, specification 2026-07-28 (opens in a new tab)Section Security and Trust & Safety
- Model Context Protocol: Security Best Practices (2026-07-28) (opens in a new tab)Token Passthrough, Local MCP Server Compromise
- Model Context Protocol: Local Server Security (2026-07-28) (opens in a new tab)Provenance, tool descriptions, isolation, credentials, network, checklist
- Anthropic: Claude Code Security (opens in a new tab)Permissions, sandbox, prompt injection, MCP, team security
- 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.
TOOLBOX
Explore
Further.
AI agent
What distinguishes an AI agent from a chat assistant and how it uses tools, explained in the glossary.
Learn MoreModel Context Protocol
How AI applications access tools and data sources in a uniform way via MCP, explained in the glossary.
Learn MorePrompt Injection
How hidden instructions in documents or web pages manipulate AI applications, explained in the glossary.
Learn MoreAI usage policy
Template for a policy on using AI in the organization, with permitted tools, data classes and AI literacy.
Learn More
AI IN BUSINESS
More on
This Topic.
- PDF
AI Usage Policy
Sample text with placeholders for AI assistants: approved tools, data classes, human review, labeling and training, plus the legal status of the AI Act after the Digital Omnibus.
View - PDF
AI Act at a Glance
Roles, prohibitions, high-risk, transparency, AI literacy, and penalties under the AI Act, with all deadlines after the amendment by Regulation (EU) 2026/1744, plus first steps for companies.
View - PDF
Using Generative AI Safely
What may go into a prompt, approved tools only, checking results, recognizing prompt injection, labeling and AI literacy under the AI Act, and reporting incidents: ready to post.
View
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.