The SaaS Security Future: 3 Ways LLMs are Revolutionizing SaaS – Source:


Source: – Author: Joseph Thacker, Sr. Offensive Security Engineer @ AppOmni

As the digital world continues to evolve with artificial intelligence (AI) innovation, there will be an increasing reliance on Software-as-a-Service (SaaS) solutions. This is because nearly every product today is being deployed and sold as SaaS due to the ease of use and seamless onboarding. For developers working on AI software, this results in quicker revenue.

Large language models (LLMs) are going to enhance existing SaaS solutions as well as empower the rapid development of thousands of brand new applications.

The downside of this increased adoption of SaaS is that this will present additional and even more unique security challenges to the organizations and end-users that increasingly rely on these SaaS apps.

Securing SaaS is a tough security challenge. With the incorporation of LLMs into SaaS-focused cybersecurity solutions, some of the pain in securing SaaS apps will be alleviated.

Here are three ways I think LLMs will positively impact SaaS security and cybersecurity more broadly.

1. Understanding Complex Security Controls

First, LLMs can play a pivotal role in demystifying the confusing landscape of SaaS security. With their ability to understand and articulate complex ideas in an accessible way, they will be a huge asset for security engineers.

Imagine this: You’re about to change a configuration setting in your ServiceNow platform. Before you proceed, you want to understand the potential risks. Here’s where an LLM can step in to provide an explanation of the security implications, helping you navigate decisions with much more confidence.

Or consider another scenario: You’re contemplating allowing self-registration on your Workday careers page. But what about the risks? Again, LLMs can offer valuable insights, supporting your decision-making process.

2. Spotting the Unusual: Anomaly Detection

Next on the list is anomaly detection. While LLMs’ “embeddings” — which transform text input into a multidimensional vector array — may seem confusing, they are ultimately just boiling down information into numbers. Those numbers can be compared against each other to determine the distance between them. If the distance is large, the information is significantly different. The potential of this capability is yet to be fully harnessed. Below is a simplified example as LLMs have many more dimensions, but it’s the same principle.

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Category & Tags: Analytics & Intelligence,Security Bloggers Network,AO Labs,Artificial Intelligence,Blog,SaaS Security,SaaS Security Posture Management – Analytics & Intelligence,Security Bloggers Network,AO Labs,Artificial Intelligence,Blog,SaaS Security,SaaS Security Posture Management


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