Do you know why we need security at every layer of an AI system?
Most people say:
“To protect data.”
That’s true… but it’s only half the story. Let’s take a real example 👇
An LLM like Llama-3.1-70B, when deployed using NVIDIA NIM, is not just a model, it also includes:
- ~350 software packages
- Hundreds of dependencies
- Multiple third-party libraries (OSS)
- Deeply interconnected components
Now think about this:
If even ONE component is vulnerable…
– The entire system can be at risk.
This is why security in AI is NOT just about Data protection! It’s about Securing the entire software supply chain at EVERY layer:
- Base OS
- Containers
- Libraries
- APIs
- Model runtime
- Orchestration (Kubernetes, etc.)
Let’s say you fix one vulnerability:
- You update a package
- That breaks a dependency
- Which affects another component
- Which may impact model behavior
Security fixes can affect across the entire system. This is why AI security is different. It’s not just “secure the app”
👉 It’s “secure the ecosystem”
Security must exist at every layer!
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