🔥 practical tips from the NVIDIA Red Team on building AI safety

I wrote this after I saw an alert from the NVIDIA Red Team today and it really stayed with me. If you are new to artificial intelligence, NVIDIA builds much of the hardware and tools that power global AI systems. Their Red Team actively searches for safety issues before those issues turn into real harm. When they raise a concern I pay attention. Their latest update felt important so I created this gentle beginner friendly breakdown for anyone building consumer facing AI apps and learning at the same pace I am.

FOR ANYONE JUST STARTING OUT

If you feel unsure or intimidated please remember this. You belong in this space. You do not need perfect knowledge to move forward. You can ask beginner questions. You can learn slowly or quickly. You can return to this later. You can grow at your own pace. You are not behind. You are not alone. Every builder in this community started exactly where you are right now and you are welcome here.

A QUICK NOTE FOR ANYONE WHO FEELS OVERWHELMED

You can copy and paste any part of this post into your favorite AI tool and ask for a simpler explanation. You can ask for beginner level language. You can ask for examples. You get to decide how you learn.

DISCUSSION: NVIDIA AI Red Team has observed three common vulnerabilities in the implementation of AI systems. The first vulnerability involves directly executing LLM-generated code, which could lead to remote code execution in the case of direct or indirect prompt injection. The second vulnerability is related to insufficient access controls in RAG data sources, which could allow a user to read data they are not privileged to read or write data to the data store. The third vulnerability is related to active content rendering of LLM outputs, which could lead to information leakage via images or other network requests.

DO NOT LET YOUR APP RUN CODE THAT A LARGE LANGUAGE MODEL WRITES

A large language model or LLM can write computer code. If your app runs that code automatically you open the door for attackers. An attacker can trick the model into creating harmful commands. You protect your system when you limit the model to a small set of approved actions or place any generated code inside a locked sandbox where nothing else can break.

PROTECT THE DATA YOU CONNECT TO YOUR AI SYSTEM

Retrieval Augmented Generation or RAG pulls outside information into your app to help the LLM answer questions. If you use loose permissions an attacker can read private information or insert content meant to confuse the model. You protect your data when you create clear rules that define who can read information and who can change it.

BE CAREFUL WHEN YOU DISPLAY LINKS IMAGES OR FORMATTED TEXT FROM THE MODEL

A large language model can generate links images and formatted text such as HyperText Markup Language or HTML and Markdown. Attackers can hide tricks inside those items. You create a safer app when you inspect every link block unknown image sources and limit formatting when your app does not need it. AI tools can do this for you.

USE AI TOOLS TO CHECK YOUR CODE AND REVIEW YOUR SAFETY DESIGN

One excellent way to build safer with AI is to research which AI tools help build safer apps. You can paste a code snippet into your AI tool and ask it to review the logic for safety concerns. You can ask it to look for unsafe patterns such as direct execution of model generated code. You can ask your tool to scan your Retrieval Augmented Generation workflow for weak permission rules. You can ask it to evaluate your system design for exposed links unprotected inputs or insecure formatting. You can ask it to explain every suggestion in plain language. When you do this you learn faster and you build safer systems with more confidence.

FOCUS ON THE MOST IMPORTANT RISKS FIRST

Many new builders try to secure everything at once and quickly feel overwhelmed. You do not need to do that. NVIDIA highlights a few areas that cause most early safety problems. Unsafe execution of LLM generated code. Weak data permissions inside RAG systems. Unchecked links images or HTML formatting. You strengthen your system quickly when you focus on these areas first.

SECURITY TOUCHES THE ENTIRE APP NOT JUST THE MODEL

Many safety risks come from the design around the model rather than the model itself. You build safer systems when you think carefully about where you store information what actions your app allows the model to trigger and how you present results to your users. Strong choices in these areas create real protection.

SAFE LEARNING RESOURCES FOR BEGINNERS

Google Learn AI AI Essentials

Microsoft Learn Responsible AI Overview

DeepLearning dot ai Generative AI for Everyone

NVIDIA AI Essentials

The Alan Turing Institute AI Ethics and Safety Guides

Stanford Human Centered AI Beginner Library

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