Most organizations are using AI in some way today, whether they know it or not. Some are merely beginning to experiment with it, using tools like chatbots. Others, however, have integrated agentic AI directly into their business procedures and APIs. While both types of organizations are undoubtedly realizing remarkable productivity and efficiency benefits, they may not know they are putting themselves at a significant security risk.
AI-powered systems that interact with sensitive customer data can also unintentionally expose that data due to API vulnerabilities. To make matters worse, attackers can manipulate AI queries to extract data. What does this mean? This means that organizations integrating AI agents must prioritize API security.
Understanding the AI-API Connection
AI agents rely on APIs to function properly. APIs act as bridges between agentic AI and internal systems like CRM platforms or ERP systems, allowing the AI agent to perform functionalities such as customer data retrieval, transaction processing, or inventory management.
Companies may assume that internal API communications with AI agents are inherently secure because they take place inside the organization’s network. Unfortunately, this isn’t the case. In reality, AI agents are often connected to the Internet, either directly or through APIs, and, as such, can act as a pathway for attackers to reach internal systems – especially when the internal API is insecure.
What’s more, AI agents can lack context awareness. This means that they don’t understand the appropriate boundaries and limitations around the data and functionality they can access. As a result, agents are vulnerable to attackers misusing or tricking them to gain unauthorized access to internal systems or expose sensitive information. Let’s look at how they can do that.
Security Risks in AI Agents
What does all this mean from a security perspective? How do attackers take advantage of the AI-API connection? Let’s explore.
API Connection Chaos
Complexity creates security risks, and the developing interconnectedness of AI agents is no exception. An effective AI agent isn’t a single entity, but a collection of APIs and potentially other AI agents. For example, a customer service AI agent might be connected via API to a CRM to gather account data, one or more applications to gather diagnostic data and reset passwords, and even other AI agents to carry out specific tasks like issuing a refund, looking up credit card transactions, etc. This one customer service AI agent actually consists of multiple APIs and other agents, all of which creates greater risk for the types of attacks described below.
Business Logic Attacks
Take an AI support bot that can reset customer passwords, for example. Although this functionality is legitimate and part of the bot’s business logic, it is also a potential vulnerability. Attackers could try to exploit weaknesses in the password reset business logic to gain unauthorized access to customer accounts.
For example, the bot’s API, or the API to which it’s connected, may have an authentication or authorization vulnerability. This could allow an attacker to impersonate a legitimate user, reset their password, and then take over their account. The issue is that the bot, without proper context awareness, may not fully understand the security implications of the password reset functionality it has been given.
Prompt Injection
When APIs forward user inputs directly into agentic AI without proper validation, attackers can craft specific queries or prompts that manipulate the AI into revealing more information than intended, including sensitive data. Moreover, as AI agents access external data sources through APIs, attackers can plant crafted prompts within external data, which the AI then processes, leading to unintended behaviors or data leaks.
Wallarm’s Approach to Protecting AI Agents
We’ve established the risks to AI agents and the importance of API security in protecting them. But what API security measures do you need? Wallarm’s solution for protecting agentic AI combines advanced API security features with sophisticated session-level protection to deliver comprehensive, real-time defense against automated threats. Here’s how it works.
AI Discovery
Wallarm’s API Discovery module includes automated identification of the business flow associated with API endpoints, including identifying AI/LLM endpoints. Organizations can start protecting their AI apps and agents by making sure they know they’re out there.
API Abuse Prevention Module
Wallarm’s API Abuse Prevention module is designed to safeguard AI systems by using advanced detection techniques that continuously analyze traffic patterns. Specifically, the module monitors:
- Request frequency and intervals between requests
- Query abuse (e.g., high volume of requests or parameter variations)
- User-agent headers
- IP rotation patterns
This granular analysis enables Wallarm to detect suspicious API activity, including account takeover attempts, security crawlers, and scraping bots that might otherwise exploit AI agents. By self-learning normal traffic profiles and identifying anomalies, the system continually adapts to emerging threats, ensuring that AI systems remain secure from potential exploitation.
Session-Level Visibility
Traditional security measures often rely solely on evaluating individual API requests, which attackers can bypass by rotating IP addresses or using distributed attacks. Wallarm’s solution enhances protection by providing session-level visibility—essentially “walking” the entire session, not just the requests identified as malicious.
This means that if an attacker compromises an account, Wallarm can identify and mitigate the threat based on the entire session rather than just the IP address. This granular control makes it significantly harder and more expensive for attackers to continue their exploits.
Unified API Security and Real-Time Threat Mitigation
Wallarm can be deployed as a reverse proxy or API gateway, which means it stands in front of AI agents to inspect and secure the APIs they use to interact with internal systems and data. This deployment not only protects the AI agents but also secures the underlying APIs and the broader system infrastructure. Moreover, Wallarm’s real-time monitoring and threat mitigation capabilities ensure that any suspicious activity is addressed immediately, providing a dynamic and robust defense against attacks as they unfold.
Comprehensive and Integrated Coverage
By combining API Abuse Prevention, session-level protection, and real-time threat detection, Wallarm offers a unified solution for securing AI agents and their associated APIs. This integrated approach ensures that every layer of communication—from individual sessions to the broader API traffic—is monitored and protected against automated threats, making Wallarm a leading choice for organizations seeking robust AI security.
Want to find out more about how Wallarm protects AI agents? Click here.
