AI & API: Double Rainbow for Cybersecurity

We’ve talked before about how AI is a double edged sword for API security, both helping bolster defenses and introducing new risks. But we haven’t really gone into detail about just how interconnected the two are. In this post, we’ll explore the interconnectedness of AI and API security, and the importance of both in 2025.

The basics of AI Security

In this day and age, it is impossible to discuss any kind of cybersecurity without mentioning AI. AI is the newest wave in technology and is continuing to revolutionize the security space. 

Because of its novelty, the concept of AI security is still not widely understood, but the OWASP Top 10 LLM risk list helps clarify the biggest challenges developers are facing in regards to AI security.

We won’t go over the whole list here, but some of the biggest issues involve prompt injection attacks, misuse of data, sensitive information disclosure and DDoS attacks.

What is interesting is that most of these issues boil down to various ways that attackers can abuse LLMs to get them to either disclose sensitive information, query other platforms repeatedly creating DDoS attacks, and more advanced attack capabilities. These capabilities vary depending on the model and method used, but across the board, we are seeing that AI itself can operate as a tool to the detriment of both its own security, and cybersecurity on the whole.

But what about the AI models themselves?

The AI models themselves are being jailbroken in various ways. Part of this in due to the “AI race,” or the way developers are attempting to churn out new models increasingly quickly in order to compete with one another on a global scale. 

A good example of this is China’s rapid (and, as we’ve explored before, highly premature) release of LLM “DeepSeek,” which has been found to both be exploitable, and potentially, copied from other AI models against their terms of conduct.

APIs in AI Security

We’ve talked before about how there’s no AI without APIs. They power the little connections between all kinds of platforms, and artificial intelligence is no exception. Many of the AI vulnerabilities and breaches we are seeing in the recent months are related to API vulnerabilities. 

For instance, OpenAI faced a recent API defect in ChatGPT’s API, which would allow an attacker to feed a long list of URLs pointing to the same site at the API, causing the crawler to go off and hit each one.

So it’s easy to see how a lack of API security can affect your AI posture. Similarly, poor AI security can affect your APIs adversely.

AI for APIs

The AI revolution has had both positive and negative impacts in the API security space. We spoke about this in more detail in a recent webinar with cyber expert Sounil Yu (watch the recording here, to learn more). 

In essence, LLMs and other AI models give security teams advanced and expedited capabilities to develop technology, which is generally a positive thing. However, the speed with which we are advancing means developers often fall behind in regards to security, and AI is only widening this gap. 

Additionally, AI gives hackers and bad actors advanced capabilities to generate infinite attack sequences, hit applications with repeated requests resulting in DdoS attacks, and more. So while AI can help in the right hands, the damage it can do in the wrong hands cancels this out. 

Indeed, we are seeing this in action right now with the sheer volume of AI-based attacks and vulnerabilities that are being reported on- and this is only a small percentage of what is probably actually happening. 

AI & API: The Double Rainbow

After reading this blog, it’s probably abundantly clear that AI and APIs have a symbiotic- and sometimes toxic- relationship that cannot be summarized adequately in a short-form post. In fact, our understanding of AI is continually adapting and changing, so it’s hard to pin down all the ways the two interact and affect each other, as we are still learning the extent in real-time.

But what we know now is that AI cannot function without APIs operating all the connections behind the scenes to access seemingly infinite information and resources. 

And API security is heavily impacted by AI, both in positive and negative ways, as AI helps developers advance their technology and even automate certain security functions, but it also gives developers the capability to launch increasingly complicated attacks, which we are seeing across the board with the abuse of various AI models.

In this way, the two appear to be a double rainbow for cybersecurity. Operating both in tandem, and alongside one another, but without one, the other is nowhere near as bright or exciting. This has been a heavy post, so to those that have made it this far, we’ll leave you with this fun video that inspired the title of our blog. 

We hope that, despite its challenges and dangers, the development of AI can evoke the same wonder and excitement as the double rainbow seen above. AI is an ever-evolving technology, but one thing is clear: now that it is out in the world and developing so quickly, nothing in the cyber landscape will ever be the same.

FireTail is attempting to embrace this change, and we are adapting our capabilities to encompass AI security as well. For more information about this, visit FireTail.ai, and for general API and cybersecurity help, sign up for our free tier or request a free virtual demo here.