Privacy Analysis: Guided Examples
This section walks you through real Bitcoin transactions and shows you exactly what chain analysis companies can figure out about them. By studying these examples, you will learn what to look for in your own transactions and how to avoid common privacy mistakes.
Each example uses Boltzmann entropy to measure the ambiguity in the transaction. If you are not familiar with Boltzmann entropy, we recommend reading the Boltzmann Entropy section first - it explains the mathematical foundation of transaction privacy in beginner-friendly terms.
Each example shows:
- What the transaction looks like on-chain
- What an analyst can figure out
- How serious the privacy leak is
- What you can do differently next time
Browse by Example
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Batch Payment
A common transaction: 1 input sending to 5 outputs. Learn what round amounts and batch patterns reveal.
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:material-combine:{ .lg .middle } UTXO Consolidation
The worst privacy mistake: combining 10 UTXOs into 1. See why the link probability matrix shows 100% certainty.
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Whirlpool CoinJoin
A privacy win: 5 inputs, 5 equal outputs. Learn why the link probability is 34.2% (not 20%) and what Boltzmann entropy really means.
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Stonewall
A steganographic transaction: 3 inputs, 4 outputs with 2 equal pairs. Learn how it creates plausible deniability with 4 interpretations.
How to Audit Your Own Privacy
- Go to am-i.exposed
- Paste a Bitcoin address or transaction ID
- Review your privacy score and findings
- Follow the recommendations
- Re-scan after making improvements
Your Queries Are Not Fully Private
Analysis runs client-side, but your browser makes API requests to mempool.space. Their servers can see your IP address and which addresses you look up.
For stronger privacy: - Use Tor Browser - Wait before querying a recent transaction - Self-host with your own mempool.space instance