AI-Native LLM Security by Vaibhav Malik Ken Huang Ads Dawson

Author:Vaibhav Malik , Ken Huang, Ads Dawson
Language: eng
Format: epub
Publisher: Packt Publishing
Published: 2025-11-28T00:00:00+00:00

Table 9.2 – Demonstrating the OWASP Top 10 vulnerabilities’ relevance to cloud-based LLM applications

Each vulnerability presents unique challenges for LLM application providers, particularly in cloud environments where ease of deployment, scalability, and integration with third-party services can inadvertently introduce risks. Understanding these vulnerabilities enables providers to implement robust security measures, ensuring that their applications remain resilient against potential threats while maximizing the benefits of cloud-based solutions.

That being said, adopting a cloud provider’s infrastructure so that it can host an LLM application can be advantageous for developers. As well as their efficiency and cost-effectiveness, there are security-related benefits to using services provided by cloud providers to build LLM applications. Let’s consider an example of hosting an integrated code interpreter where a client can interact with a chatbot with coding capabilities. This was illustrated in Chapter 8, and it was shown to be a vector for attackers to foothold, pivot, laterally move, and potentially remain persistent through this kind of feature. This application integration can map to several of the OWASP Top 10 vulnerabilities, but the most prominent is Insecure Plugin Design.

Let’s look at the benefits of using cloud-based deployments for chatbots and conversational agents:

Isolation and security by design:Serverless architecture: By leveraging serverless computing services such as AWS Lambda, Google Cloud Functions, and Azure Functions, each code execution request runs in a stateless environment that is inherently isolated from other processes. This isolation means that if an attacker attempts to exploit vulnerabilities within the embedded code interpreter, their access is limited to that specific execution context, significantly reducing the potential blast radius of any attack.

Example: If malicious code is executed through the embedded interpreter, it cannot affect the underlying infrastructure or other running applications, as each function execution is contained within its own secure environment.

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