Blog Article

The Importance of a Generative AI Bill of Materials for Security

Arnav Bathla

8 min read

In the rapidly evolving landscape of Generative AI, organizations are increasingly leveraging both open-source and closed-source LLMs to build innovative products. As these AI capabilities become more integrated into business operations, the security implications become more significant and complex. For security engineers and CISOs, understanding and managing the risks associated with these technologies is paramount. One essential tool in this endeavour is the Generative AI Bill of Materials (Gen AI BOM).

What is a Gen AI BOM?

A Generative AI Bill of Materials is a comprehensive list detailing all the components, both software and hardware, used in the construction of a generative AI system. This includes data sets, models, APIs, third-party libraries, and any underlying tools or platforms, such as those provided by Hugging Face or integrated with search functionalities.

The Gen AI BOM goes beyond traditional software BOMs by including specific elements pertinent to AI, such as training data provenance, model versioning, and the dependencies of various AI tools and libraries. It is designed to provide a full transparency view, allowing security professionals to assess vulnerabilities, compliance with regulations, and overall system integrity.

Why is Gen AI BOM Crucial for Security?

1. Visibility and Transparency

The first step in securing any system is understanding what it consists of. In the context of AI, this is often complicated by the layered and interconnected nature of AI models and their data sources. A Gen AI BOM provides a clear, detailed map of the components in use, making it easier to identify potential security vulnerabilities, such as dependencies on compromised libraries or outdated tools.

2. Compliance and Auditability

With industries facing increasing regulation around data usage and AI deployments (e.g., GDPR, CCPA, and upcoming AI-specific regulations), having a detailed BOM helps organizations ensure and demonstrate compliance with relevant laws. This is particularly important when using mixed sources of software components (open-source and proprietary), as different licensing and compliance requirements may apply.

3. Vulnerability Management

AI systems are as vulnerable as the sum of their parts. Each component in an AI stack could potentially harbor vulnerabilities that might be exploited by malicious actors. A Gen AI BOM enables security teams to perform thorough vulnerability assessments across the entire stack, update components proactively, and respond to threats more effectively.

4. Supply Chain Security

AI tools often depend on numerous external sources and third-party services. Each of these represents a potential entry point for threats. A comprehensive BOM helps in mapping out the supply chain, identifying less secure links, and implementing stronger controls where needed.

5. Data Security and Privacy

For AI models, data is not just an input but a foundational building block. The Gen AI BOM includes detailed information about the origins, handling, and processing of data sets, helping to prevent data breaches and misuse, and ensuring data privacy standards are met.

Implementing Gen AI BOM

For effective implementation, organizations should integrate the creation and maintenance of the Gen AI BOM into their development and deployment workflows. This involves:

  • Regularly updating the BOM as components are added, removed, or updated.

  • Ensuring that all team members, from developers to security analysts, understand and utilize the BOM in their respective roles.

  • Using automated tools to track component changes and potential vulnerabilities continuously. This is where you can use Layerup to ensure you have proper auditability for your Gen AI BOM.


As Generative AI continues to reshape industries, the complexity and security challenges associated with these technologies will inevitably increase. For security engineers and CISOs, the Gen AI BOM is not just a tool but a necessity in the toolkit for maintaining robust security postures, ensuring compliance, and ultimately safeguarding the organization's technological investments. Embracing these practices now will not only address current security needs but also prepare organizations for the future landscape of AI-driven innovation.

If you're looking to adopt a sophisticated product for Gen AI BOM, reach out to us at Layerup. We can show you how enterprises are using Layerup to establish Gen AI BOM practices and bring visibility into Gen AI vulnerabilities.

Securely Implement Generative AI


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