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🔥 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.
2 likes • Nov '25
Thanks so much for this post! I'm definitely feeling a little overwhelmed here. Really appreciate the list of learning resources at the end. Have you used them all? Is there a best place to start with them?
Intro
Lawrey is my name. At 73 I am aspire to market my freelance writing. I have been a licensed carpenter, a building and renovation contractor, and was employed for 27 years with Toronto Transit in the carpentry maintenance division. With A.I. I am taking a course just now at 44 consecutive days of intro. Just scratching this big surface but I expect to continue to find help with managing my writing, marketing, and useful learning, hopefully I can learn to be of more help to others as well. Great advertising by Tony Robbins and Dean Graziosi along with the high power of A.I. has drawn me to this community which I think will continue to grow by leaps and bounds. Fun fact: I have not yet named my bot but my woods connection has me considering CHIP or Chippy, please offer me your view of which is more A.I.like ?
1 like • Nov '25
@Lawrey Jack Smashnuk if you’re taking votes for your bots name I vote for Chip. I’d be worried about what kind of advice I’d be getting from a bot named Chippy… (glad I took the time to spell check my comment before sending… ha!)
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Paul Maddock
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