API Security IS AI Security

Artificial Intelligence is transforming the cyber landscape at unprecedented speeds. While these advancements bring enormous potential, they also introduce new and evolving security risks that most organizations are unprepared to handle.Attackers are now exploiting AI models to gain access to sensitive information, or even to use the AI technology to launch their own attacks on other platforms. And these attacks are increasing exponentially, faster than security teams can keep up with.

According to CapGemini, 97% of organizations using generative AI have reported data breaches or security incidents linked to AI—highlighting the critical need for a robust AI security strategy.

They are able to get away with this because AI security is a mystery to many. And with so many entities rushing to push new models to the market such as OpenAI and DeepSeek, it is often overlooked until it is too late. But how can we ensure that we have a strong AI security posture if we don’t even know where to start?

Here at FireTail, we understand that AI security is just API security, with a few additional steps. 

AI Security is API Security

APIs are the ways that different systems communicate for simple interactions and transactions. 

APIs are the backbone of AI systems, powering all the behind-the-scenes functions that enable LLMs to operate at scale and speed. Without secure APIs, your AI strategy is at risk—period.

AI runs on APIs, and if those APIs aren’t secure, neither is your AI.

The diagram below illustrates the Large Language Model (LLM) reference architecture, which relies heavily on APIs. You can see on the right the different types of APIs that are used by AI models in the average LLM.

AI REFERENCE ARCHITECTURE:

Because of this, effective AI security starts with API security.

What does good AI and API security look like?

There are 6 pillars of effective AI & API security. We’ve touched on these a bit before, but effectively, AI & API security should both include the following…

1. Discovery- If you can't see it, you can't secure it. Effective AI & API security begins with knowing where you have connections, with which applications, data and to which providers.

2. Visibility-Maintain an AI and API inventory by automating the discovery process and making it continuous across code and cloud environments.

3. Observability- Monitor AI & APIs for risky traffic, attacks and errors. Use anomaly detection to identify deviations. Set up alerts.

4. Assessment- AI providers and APIs should be continuously analyzed for misconfigurations and vulnerabilities. Automate AI & API security posture management.

5. Enforcement- Ensure consistent policy and governance across the organization. Use runtime protection with call validation, data and authentication checks & injection prevention.

6. Audit- Stay compliant and aware of data exposure risks using a centralized audit trail of AI and API traffic.

AI Security Connection

AI is only as powerful as the data it can access, APIs are the bridge that gives them this access. In essence, APIs are the “control layer” for AI, as they dictate how it processes requests and replies. Therefore, an attacker can exploit AI models via API, as we are seeing increasingly across the current cyber landscape.

Securing AI means also securing the APIs that power it. 

AI security can be complicated, but if you remember that it’s just API security with some more steps, you’ll be just fine.

Protect your AI innovations with FireTail's unified AI and API security platform. See how our comprehensive approach can safeguard your AI initiatives against evolving threats. Request a demo today.