AI agents are growing at a rapid pace. Companies increasingly use these tools for drug discovery, customer service, marketing, writing code and research—complex tasks humans previously performed. In fact, 78% of companies have active plans to implement AI agents into production. It’s clear: 2025 will be the year of AI agents.

But with great innovation come new risks. As AI agents become embedded in enterprise operations, they introduce a new set of security challenges and attack vectors. AI Runtime Security is here to tackle them.

AI Runtime Security is designed to secure AI applications, whether built on low-code/no-code platforms like Microsoft Copilot Studio or VoiceFlow—or even for AI agents developed with custom workflows. It offers robust protection for your agents by defending against a variety of potential threats, including:

• Prompt injections: Hackers manipulate generative AI systems by feeding them malicious inputs disguised as legitimate user prompts.
• Sensitive data leaks: Makes training data susceptible to leakage in application outputs.
• Malicious URLs: An AI model can be tricked into compiling a URL containing an attacker-owned domain with sensitive data embedded in the URL parameters. The app or end user may then attempt to fetch the URL, which sends the data to the attacker’s server.

Organizations need their AI agents to operate securely and effectively, so the AI Runtime Security API comes with critical safeguards to mitigate risks while maintaining performance.

If you’re unsure why this is critical, read on for a brief overview of AI agents and the need to secure them. You can also learn more on our upcoming webinar, “A Practical Guide to Securing Enterprise AI: LLMs, RAG and agentic AI."

How Does an AI Agent Differ from LLMs and Chatbots?

At a high level, AI agents are far more advanced than the typical question-answering chatbots to which we have become accustomed. They go beyond simple queries—they’re sophisticated, autonomous systems that take action on behalf of users. Instead of just responding, they actively think, decide, and adapt.

At its core, an AI agent is an intelligent software system that can:

• Perceive its environment: AI agents sense their environment to gather relevant information. This information could come from data streams, system inputs or other external sources. They constantly take in information to understand the world around them.
• Reason about what’s happening: Once the agent has all this data, it must process and make sense of the information. This is where the agent applies algorithms and logic to analyze information, similar to how humans reason through problems.
• Make decisions based on that reasoning: Based on the insights from reasoning, the agent must choose the best possible action to meet its objectives. Whether it's solving a complex issue or optimizing a process, the goal is always to select the most effective path forward.
• Take action autonomously: AI agents are built to operate independently. They don’t require human intervention for every decision. They can adapt to new information and changing environments, continuously moving toward their goals without being manually guided.

Because they are smart, adaptable and driven to take action independently, AI agents can be incredibly powerful tools for businesses. However, as we’ll see, the same autonomy and independent decision-making capabilities also introduce new security challenges.

What New Security Challenges Do AI Agents Present?

Let’s look closer at its inner workings and the architecture that makes these agents so powerful.

• Short-term memory: Helps the agent remember immediate, important details, such as the current task or any goals it’s working on.
• Long-term memory: Stores past experiences and knowledge. This is where the agent learns from its actions and adapts. Think of it as the agent’s ability to improve over time based on its history and experiences.
• Planning module: The agent’s strategy center determines how to achieve goals and accomplish tasks.
• Tools are external resources or functions the agent can use to help with tasks. The agent uses these tools as needed and integrates them into planning and decision-making processes to accomplish goals more effectively.

An AI agent is a well-organized system with memory, planning and tools that work together to help it think, learn and act autonomously. It’s a dynamic, evolving system capable of solving problems and improving over time—all on its own. Some agents operate in a multi-AI agent system, where multiple AI agents work together to tackle complex tasks, increasing their power and vulnerability.

How Can Attackers Exploit AI Agents?

As powerful as AI agents are, they come with their own set of security challenges. These challenges rely on getting the agent to change its behavior and act in the best interest of the attackers instead of your organization. These exploits include, but are not limited to, the following:

• Contextual data manipulation: By manipulating memory systems, attackers can corrupt stored information about past interactions and contextual data. Once false information is injected or existing memory content is modified, attackers can force agents to make incorrect decisions, ignore security protocols, or act against user interests while appearing to operate normally. The persistence of this attack makes it particularly dangerous, as corrupted memory can influence agent behavior across multiple sessions and interactions.
• Tool exploitation attack: Through carefully crafted prompts, attackers can trick AI agents into unintentionally misusing legitimate tools and access permissions. This exploitation can enable unauthorized access to sensitive data or system resources without triggering standard security alerts.
• Fabricated output distortion: Attackers can intentionally generate false or unreliable outputs by exploiting AI agents' tendency to make assumptions when faced with incomplete or ambiguous information. This vulnerability is particularly dangerous in autonomous systems, where agents act on these fabricated outputs without human verification. It could lead to unauthorized actions or compromised decision-making, affecting system security and reliability.

The Road Ahead for Securing AI Agents

This year, we are focused on enhancing the security of AI agents to better address the emerging threats we’ve identified. In addition to reinforcing these existing protections, we are also exploring innovations that will make it easier for organizations to discover, protect, and monitor threats related to AI agents.

We aim to ensure that AI agents remain secure and trustworthy as they evolve and become even more integral to enterprise operations. This proactive approach will help organizations like yours stay ahead of new threats and ensure the continued safe deployment of AI technologies.

To learn more about AI Runtime Security and how our API can help protect against runtime threats, sign up for a personalized demo.