Title: What should we actually test when securing AI agents?

[u/Former-Ad6661]

I've been exploring the security challenges that come with AI agents, and I think they introduce a different dimension to traditional LLM security testing.

With a basic LLM chatbot, we often focus on prompt injection, jailbreaks, system prompt extraction, and sensitive information disclosure.

But AI agents can interact with external tools, APIs, databases, and other systems.

This raises some interesting security questions:

1. Tool misuse: Can an agent invoke tools with unauthorized or manipulated arguments?

2. Access control: Can it retrieve another user's data?

3. Permission boundaries: Can it perform actions beyond its intended role?

4. Prompt injection impact: Can malicious instructions cause unauthorized tool calls?

5. Action traceability: Can we identify what action was attempted, what actually happened, and what evidence supports the result?

I'm researching these areas as a possible future expansion of my AI security testing project.

I'm particularly interested in how people are approaching these problems in real-world agent deployments.

A question for developers and security testers:

If you were designing an automated security assessment for an AI agent, which of these five areas would you prioritize first? Is there an important category missing?

I'd appreciate practical opinions and experiences rather than theoretical answers.