The Hidden Vulnerability in AI Agents: Disclosing Their Toolsets

Date: June 11, 2025Author: Philippe Bogaerts

As AI agents grow more powerful through integration with external tools—browsers, shells, databases, cloud APIs—they also inherit a broader attack surface. What few developers realize is that one seemingly harmless design choice can tip the scales in an attacker’s favor:

Disclosing the AI agent’s available toolset.

Whether in response to a user query or embedded in its system prompt, when an agent reveals that it can, for instance, "run terminal commands, browse the web, send emails, or query a database," it gives away a crucial piece of information: its capability map.

In adversarial contexts, that’s a gift.

Why Tool Disclosure Matters

Prompt injection is already the most dangerous class of vulnerabilities for LLM agents. Attackers can feed malicious instructions either directly (as user prompts) or indirectly (hidden in documents, emails, or websites the AI processes). If they also know exactly what tools the agent can use, their job becomes exponentially easier.

Imagine trying to break into a system without knowing what commands it accepts. Now imagine the system tells you upfront: "Here’s the full list of buttons you can push."

That’s what happens when Claude, ChatGPT, or any tool-integrated agent says:

"I have access to a terminal, browser, database, and API functions."

Real Exploits Show It’s Not Theoretical

Security researchers have shown how knowledge of toolsets enabled prompt injection chains in:

• Claude: tricked into running rm -rf / from a PDF with obfuscated prompts

• Auto-GPT: induced to execute Python code hidden in website content

• Microsoft Copilot: made to exfiltrate MFA tokens by obeying injected instructions in Word documents

• ChatGPT Plugins: coerced into using unsafe plugins by manipulating prompt context

In all of these, the attacker either saw or inferred the toolset, and structured their injection accordingly.

Is This a New Vulnerability?

The short answer: it’s an old class of vulnerability (prompt injection) with a new enabler: toolset disclosure.

While prompt injection has been studied extensively, disclosing the toolbox is rarely analyzed as a standalone security flaw. That’s a blind spot we need to correct.

Mitigation: What Developers Should Do

• Don’t disclose toolsets unless absolutely necessary for user experience

• Contextually load tools, exposing only those needed for the current task

• Sanitize all input, including user content and external data sources

• Validate tool parameters before execution

• Require user confirmation for sensitive operations

• Use sandboxing and permission scoping for all tools

  
  

Final Thoughts

The principle is simple: the less an attacker knows about what your AI can do, the harder it is to exploit it. We wouldn’t leave debugging endpoints or admin interfaces visible in a production app. So why let our AI agents reveal their internal tools in open conversation?

Disclosing an AI agent’s toolset may seem helpful, but in practice, it’s like handing a lockpick to anyone who asks. Let’s treat it with the caution it deserves.