Securing AI Agents: 5 Security Risks Developers Should Test For

AI agents are moving beyond simple chat interfaces. They can interact with APIs, use tools, process sensitive information, and execute multi-step workflows.

But as their capabilities grow, so does their attack surface.

For developers building AI-powered applications, security testing should be part of the development process—not something added after deployment.

Here are five security risks worth testing when building AI agents.

Prompt injection occurs when malicious instructions in user input or external content attempt to manipulate an AI agent's behavior.

For example, an agent that summarizes web pages might encounter hidden instructions telling it to ignore its original task or reveal information it should not disclose.

AI agents often interact with tools such as APIs, databases, browsers, and code execution environments.

A model may produce an unexpected tool call, but the application's permissions and execution layer should prevent unauthorized actions.

Agents may process confidential business information, internal documents, API responses, or user-specific data.

Security testing should examine whether the agent reveals information beyond the current user's authorization.

An agent with broad permissions and limited safeguards can take actions that exceed the user's original intent.

This becomes particularly important when agents can modify records, send messages, execute code, or interact with production systems.

A successful demonstration does not prove that an AI agent is secure.

Agent behavior can change with different prompts, tools, model versions, permissions, and environmental conditions.

Developers should build repeatable evaluations that test expected behavior, known attack scenarios, and regression cases.

If you're developing an AI agent, begin with a simple security checklist:

The goal isn't to assume that a model will always behave correctly. It's to design the surrounding system so that failures are contained.

I'm building SecureMID, focused on AI agent security, and I'm interested in learning how developers approach this problem.

I'd appreciate practical experiences, testing approaches, and constructive feedback.

Disclosure: I'm sharing this from the perspective of someone building SecureMID. You can learn more at https://securemid.com.