explaingit

wepoets1107/btc-collision-hunter

19PythonAudience · generalComplexity · 1/5Setup · easy

TLDR

A Python art project that generates Bitcoin private keys and checks for funded wallets, not to find any, but to collectively prove how impossibly unlikely that is. It visualizes Bitcoin's security through shared participation and a live dashboard.

Mindmap

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  root((repo))
    What it does
      Generates private keys
      Checks wallet balances
      Tracks global count
      Live dashboard
    The Point
      Cryptographic art
      Proves impossibility
      Collective proof
    How it works
      Runs 1 hour daily
      10 addresses per second
      Reports to GitHub issue
      No keys saved to disk
    Audience
      Curious learners
      Bitcoin enthusiasts
      Art project fans
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Code map

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Things people build with this

USE CASE 1

Run the script to participate in a collective art project that demonstrates Bitcoin's security by attempting random wallet guesses.

USE CASE 2

Use the public dashboard to watch a live tally of how many addresses humanity has collectively checked, and how many funded wallets were found.

USE CASE 3

Share the project with non-technical people to make the astronomical scale of Bitcoin's security feel real, not just theoretical.

USE CASE 4

Learn how Bitcoin private keys and addresses relate to each other by reading through a minimal, well-explained Python script.

Tech stack

PythonBitcoinGitHub Issues

Getting it running

Difficulty · easy Time to first run · 5min

Download and run the Python script. No special dependencies or accounts needed. Configure the run time and it will check 10 addresses per second, saving only a counter to disk, no private keys are ever stored.

License not mentioned in the explanation.

In plain English

This is a small Python program that generates Bitcoin private keys one by one and checks whether each key corresponds to a wallet that holds any money. The project describes itself as "cryptographic performance art" and is upfront about the core mathematical reality: the chance of randomly hitting a funded wallet is so close to zero that you could run the program every second for trillions of times the age of the universe and still expect nothing. The whole point is that impossibility. Bitcoin's security depends on there being an astronomically large number of possible keys, around 2 to the power of 160 possible addresses. There are roughly 50 million funded addresses worldwide. Finding one by random guessing would require on average 2 to the power of 133 attempts. The program runs anyway, as a kind of collective proof of that limit. Anyone can download and run the script. By default it runs for one hour per day at a set time, checking 10 addresses per second. Participants report their running count to a shared GitHub issue, and an automated process aggregates the global total every 10 minutes. A public dashboard shows how many addresses the collective effort has checked so far, along with a running tally of how many wallets have been found (the expected answer: zero). On the privacy side, no private keys are ever saved to disk. Each key is derived on the fly from a counter value using a standard cryptographic function and thrown away immediately after the balance check. The counter itself is saved so the program can resume without repeating addresses it has already checked. This is not a practical tool for finding Bitcoin. It is an interactive art project built around demonstrating, through collective action, a mathematical fact that words alone cannot make feel real.

Copy-paste prompts

Prompt 1
I have the btc-collision-hunter Python script. Explain in simple terms what a Bitcoin private key is, what a wallet address is, and how one is derived from the other, as demonstrated by this code.
Prompt 2
Using btc-collision-hunter as a reference, help me understand why 2^133 random guesses makes finding a funded Bitcoin wallet effectively impossible. Show me the math in plain English.
Prompt 3
I want to modify btc-collision-hunter to display a real-time probability estimate on screen, something like '1 in X chance so far'. How would I add that to the existing script?
Prompt 4
Help me write a short explainer post about the btc-collision-hunter project for a non-technical audience, focus on why it's art, not a hacking tool, and what it reveals about Bitcoin security.
Prompt 5
I want to set up btc-collision-hunter to run automatically once a day on my computer and post my address count to the shared GitHub issue. Walk me through how to do that step by step.
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