Why Every CISO Needs to Read the AWS Generative AI Security Scoping Matrix

GenAI is the New Attack Surface — Are You Ready?

Generative AI (GenAI) is now officially past the hype stage and entered the “what can we practically do” phase

Whether you like GenAI or not — it’s here, and it’s transforming industries at an unprecedented pace.

As enterprises rush to adopt tools like ChatGPT, Amazon Bedrock, and MidJourney, the security landscape is shifting dramatically.

By 2026, Gartner predicts that over 80% of enterprises will have deployed GenAI-enabled applications — a staggering leap from less than 5% in 2023.

But with great innovation comes great security risk.

GenAI introduces a new attack surface, and traditional cybersecurity controls are no longer enough to secure it.

CISOs no longer have the option of saying no to GenAI

The problem ?

Traditional security models are built around protecting environments like servers, applications, data centers.

But GenAI doesn’t work like that.

Unlike static applications, GenAI learns, adapts, and can be manipulated in ways traditional software cannot.

CISOs have to ask the following questions:

• Where is the model hosted? → Third-party API (e.g., OpenAI, Anthropic) or self-hosted?

• What type of model is being used? → Pre-trained, fine-tuned, or fully custom?

• What data is being fed into it? → Is it handling PII, financial records, or internal IP?

• How resilient is the model to attacks? → Have we tested for prompt injections or adversarial manipulations?

Each of these questions represents a new attack vector that traditional security tools don’t address.

I have written before about how CISOs make two critical mistakes when trying to secure GenAI

1 — Over-Reliance on Security Tools

CISOs often focus too much on security tools like monitoring and intrusion detection, assuming they are enough to secure GenAI systems.

However, tools alone are insufficient without a holistic approach that includes governance policies, data protection, and continuous risk assessments.

Overemphasis on tools can lead to neglecting crucial areas such as user education, governance frameworks, and proactive threat modeling.

2 — Imbalanced GenAI Security Strategies

Many security strategies for GenAI are either too high-level (focusing only on broad policies like AI ethics) or too low-level (focusing only on technical aspects like model encryption).

A balanced approach is needed to ensure actionable security measures.

Key governance issues such as third-party GenAI API management, AI decision accountability, and regulatory compliance must be addressed alongside technical controls to prevent security gaps.

This is where the AWS GenAI Security Scoping Matrix comes in

The AWS Generative AI Security Scoping Matrix

AWS developed the Generative AI Security Scoping Matrix to help security leaders categorize GenAI use cases and apply appropriate security controls.

It defines five different security scopes, based on how much control and responsibility an organization has over the AI model.

https://aws.amazon.com/blogs/security/securing-generative-ai-an-introduction-to-the-generative-ai-security-scoping-matrix/

The Five GenAI Security Scopes

The AWS Security Scoping Matrix classifies AI use cases into five security scopes:

1 — Consumer App (Scope 1) → Using third-party GenAI apps (least control, highest risk of data leakage) like ChatGPT

2 — Enterprise App (Scope 2) → GenAI embedded into enterprise SaaS applications like Microsoft CoPilot

3 — Pre-Trained Model (Scope 3) → Building apps using external models via APIs.

4 — Fine-Tuned Model (Scope 4) → Customizing pre-trained models with business-specific data.

5 — Self-Trained Model (Scope 5) → Fully custom-built AI models (most control, highest responsibility).

Each scope has different security responsibilities.

For example:

• Scope 1 (Consumer AI apps) → You need data loss prevention (DLP) policies to prevent employees from pasting sensitive data into public AI tools.

• Scope 5 (Self-trained models) → You need full model governance, adversarial testing, and access controls to protect the AI’s outputs.

https://aws.amazon.com/blogs/security/securing-generative-ai-an-introduction-to-the-generative-ai-security-scoping-matrix/

The matrix also maps security disciplines across different AI implementations, focusing on:

1 — Governance & Compliance → Establishing accountability for AI decision-making.
2 — Legal & Privacy → Addressing GDPR, CCPA, and AI-specific legal risks.
3 — Risk Management → Identifying attack vectors like prompt injections & adversarial attacks.
4 — Security Controls → Applying IAM, encryption, and threat monitoring to protect AI models.
5 — Resilience → Ensuring AI systems remain available, robust, and resistant to attacks.

Why Every CISO Needs to Read This Matrix

In my (100% subjective) opinion, the AWS Generative AI Security Scoping Matrix is one of the best tools available to help cybersecurity leaders navigate the unique risks of adopting GenAI

A few key reasons:

• It bridges the gap between AI innovation and cybersecurity . AI teams move fast, but security needs a structured framework to keep pace

• It provides clear security strategies. CISOs can align security policies with the actual risks of their AI deployment.

• It maps real-world security controls to AI risks. From data encryption to threat detection, the matrix helps CISOs implement best practices effectively.

• Despite being AWS specific, it is open enough to be implemented by any organization

Still interested ?

Then check out my latest course on "Securing GenAI Systems with Best Practice Frameworks" below !

This course provides a comprehensive guide to understanding, assessing, and implementing robust security measures for Generative AI systems.

It explores key frameworks and methodologies, including Google SAIF and AWS Generative AI Scoping Matrix, empowering you to secure GenAI applications effectively.

What You Will Learn

• Fundamental principles and best practices for securing GenAI systems.

• Insights into common pitfalls in Generative AI security and strategies to avoid them.

• A deep dive into security frameworks like Google SAIF and AWS Generative AI Scoping Matrix.

• Implementation of security controls tailored for GenAI applications.

How To Get This Course

There are two ways you can get this course

• DIRECT LINK: You can buy my course on Udemy by clicking on this link

• FREE: If you are a paid annual subscriber, you get it for FREE. Thanks for supporting this newsletter !

Just click on the link below to redeem the voucher and enroll in my new course

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