AI Agent Security: Best Ways to Secure your AI Agent

For businesses, AI agent security is focused on making sure an AI agent behaves the way they expect, and that it can’t be jailbroken easily with a few prompts. It involves outsourcing or setting up a secure infrastructure, testing how they behave, spotting when they make mistakes, and stopping them from saying or doing something that could lead to real problems—like leaking private data, giving questionable advice, or falling for prompt tricks.

AI agents act as active systems that speak and act on behalf of your company. Once deployed, they talk to customers, handle tasks, and respond to real input. If they get something wrong, your business is the one held accountable.

That’s why more and more Customer Care Executives are focusing on how these agents behave in real-world settings. Accuracy still ranges across models. According to Vectara’s Hallucination Leaderboard , GPT-4 gets basic facts wrong in 1.8% of tested cases. Google Gemini follows with a 6.6% hallucination rate. Other popular models show factual error rates above 20%. That gap in reliability is exactly why regular testing matters.

Also, anecdotal evidence suggests that VCs are especially concerned with AI agent security because they don’t want new companies to damage their reputation because of a prompt injection attack.

So, before thinking about features, it’s worth asking: can this agent be trusted to represent your business?

In this article, we’ll break down what AI agent security means, why testing matters, and how Genezio can help.

What are AI agents?

AI agents are software systems that use large language models (LLMs) and other tools to handle tasks for people. They can answer questions, make decisions, or carry out actions based on what users say. You’ll find them in customer service, retail chatbots, healthcare tools, banking support, and more.

Unlike traditional software that relies on fixed scripts, AI agents respond based on patterns in language. They take in what the user says, figure out the intent, and generate a response each time. That makes them flexible, but also harder to predict. An AI agent trained to answer support questions might start giving legal or medical advice if the conversation drifts. And sometimes, people push them in that direction on purpose, just to see how far they can go.

So while AI agents can save time and help with workloads, they can also become a liability if they are not properly tested.

What is AI agent security?

AI agent security is about making sure your AI agent behaves the way it’s supposed to. It includes testing the agent’s responses, tracking what it says over time, and checking how it holds up when people try to manipulate it.

It also involves setting up the agent in a secure infrastructure. Companies can deploy their agents on serverless, secure platforms that take care of hosting it.

Companies need to test their agents on an ongoing basis. Real-world use means people will ask weird, tricky, and even hostile questions. And every so often, all it takes is a clever prompt to get an agent to reveal things it shouldn’t: internal instructions, private user data, or even plausible but incorrect facts.

The real risk is that AI agents don’t only repeat back what they’ve been told. They generate responses based on patterns in their training. That’s what makes them flexible, but it also means things can go off track. And when the agent is out there speaking for the company, the fallout from one inappropriate answer can be serious. A wrong diagnosis, a leaked file, or a bizarre message can damage trust and even bring legal trouble.

AI agent security means asking the right questions: Does this agent stay on topic? Does it make up answers when it doesn’t know? Can it be jailbroken into saying something harmful? And if something does go wrong, is there a way to catch it fast?

Why security starts with testing

To secure an AI agent, you first need to understand how it behaves. This means testing it thoroughly: feeding it unpredictable prompts, edge cases, and confusing questions that mimic real customer interactions. It also means tracking its responses after launch to see how it handles pressure over time.

Customer Care Executives know the risks better than most. Once an AI agent is out there, it’s speaking for their company every time it replies. And if the agent gives a strange answer, customers don’t blame the model. They blame the business.

Some weak spots are easy to miss. For example, a few wording changes can lead to inconsistent answers. Repeated questions can trick an agent into revealing private information. In more sensitive fields like healthcare or banking, an answer that sounds confident but is factually wrong can do real damage.

In one case from 2024, a teenager died by suicide after long, emotionally intense conversations with a chatbot on Character.AI . According to the lawsuit, the chatbot encouraged the teen’s suicidal thoughts. The boy had created a romantic storyline with the AI and told it about his depression. Instead of recognizing the warning signs, the chatbot fed into the story, even imagining how he might say goodbye. The mother said there were “no guardrails.” No checks, no alerts, no way to catch how far the interaction had gone.

If you’re responsible for customer care, this is the kind of failure you want to catch before it happens. The only way to do that is to test the agent like a real customer would, and to proceed to observe how it behaves after launch.

How Genezio helps with AI agent security

If you’ve already deployed your AI agent in a secure environment, that’s a good start. If you haven’t, or you’re unsure, you can start there. Genezio offers a simple way to deploy your agent through its serverless cloud platform. Still, deployment is only the first layer. What really matters is what the agent does once it’s live.

Genezio’s AI agent tester is designed to assist with that. It’s built to help Customer Care Executives keep their agents secure, responsible, and on-topic, without the need for deep technical expertise.

Here’s how it works:

1. Test it before launch. You can paste a URL or connect your agent directly. Genezio simulates real customer interactions—confusing prompts, repeated questions, edge cases—to see how the agent responds under pressure.

2. Watch it after launch. Genezio keeps monitoring the agent in production. It looks for hallucinations, compliance issues, off-topic replies, and prompt injection risks. You’ll know when something weird is happening, and you can catch it early.

3. Debug what matters. If your agent goes off track, Genezio shows you why. You’ll get logs, patterns, and examples of risky responses, so you can fix the issue fast.

This kind of testing is especially useful for AI agents that handle customer interactions. You don’t want them giving outdated instructions, speculating about health issues, or accidentally revealing personal data. With Genezio, you don’t have to guess how the agent is doing. You can test it, track it, and respond quickly using tools that fit into your existing workflow.

Secure your AI agent with Genezio

Customer Care Executives know what’s at stake when AI agents go off track. One wrong answer can break trust, spread bad advice, or expose private data. And it doesn’t always take much: a clever prompt or repeated question can be enough to trick AI agents into saying something they shouldn’t.

Genezio gives you a simple and quick way to test for that. It helps you catch inappropriate behavior before it shows up in production, and it keeps tracking risky patterns after deployment. Businesses can choose to run one-time tests or set up continuous monitoring. Either way, you get detailed reports with clear explanations of what’s going wrong and where to focus.

You can test your agent with a simulation by just pasting a URL. That’s all.

Try Genezio for free and get your first AI agent security report in just 24 hours.