I did it.

I can flag scam tokens on Base.

(With 94% accuracy)

Building, not sure what yet but sharing my journey.

Prev. @rainbowdotme, @metamask

Santiago, Santiago Metropolitan Region, Chile

Instead of attempting smart contract audits, I developed a neighborhood-based algorithm, based by the principle:

If you interact with a scammer, you're also likely a scammer.

I trained graph neural network models to understand:

• How tokens interact

• The behavior of their neighborhoods

• Subgraph patterns that indicate scams

Why am I doing this?

While in SF some days ago, I was blown away by what’s happening in the AI space.

So I'm giving it a try.

I believe AI algorithms can far beat us reading data from a blockchain.

I'm experimenting with this idea to expand its applications beyond just scam alerts.

If you have ideas please let me know.

But first, I need to make it work in real time.