micsapp Analyzing Ransomware Payment Wallets
When to Use
- An organization has been hit by ransomware and the ransom note contains a Bitcoin or cryptocurrency wallet address that needs investigation
- Law enforcement or incident responders need to trace where ransom payments flowed after the victim paid
- Threat intelligence analysts are attributing ransomware campaigns by clustering payment infrastructure across incidents
- Investigators need to determine if a ransomware group is reusing wallet infrastructure across multiple victims
- Compliance or legal teams need evidence of fund flows for prosecution, sanctions enforcement, or insurance claims
Do not use this skill for live payment interception or to interact directly with ransomware operators. All analysis should be passive and read-only against public blockchain data.
Prerequisites
- Python 3.8+ with
requests,json, andhashliblibraries - Access to blockchain explorer APIs (blockchain.com, WalletExplorer.com, Blockstream.info)
- Familiarity with Bitcoin transaction model (UTXOs, inputs, outputs, change addresses)
- Understanding of common obfuscation techniques (mixers, tumblers, peel chains, cross-chain swaps)
- Optional: Chainalysis Reactor license for enterprise-grade cluster analysis
- Optional: OXT.me for advanced transaction graph visualization
Workflow
Step 1: Extract Wallet Address from Ransom Note
Parse the ransom note to identify the payment address(es):
Common address formats:
Bitcoin (P2PKH): 1A1zP1eP5QGefi2DMPTfTL5SLmv7DivfNa (starts with 1)
Bitcoin (P2SH): 3J98t1WpEZ73CNmQviecrnyiWrnqRhWNLy (starts with 3)
Bitcoin (Bech32): bc1qar0srrr7xfkvy5l643lydnw9re59gtzzwf5mdq (starts with bc1)
Monero: 4... (95 characters, much harder to trace)
Ethereum: 0x... (40 hex chars)
Step 2: Query Blockchain Explorer for Transaction History
Retrieve all transactions associated with the wallet:
import requests
def get_wallet_transactions(address):
"""Query blockchain.com API for address transactions."""
url = f"https://blockchain.info/rawaddr/{address}"
resp = requests.get(url, timeout=30)
resp.raise_for_status()
data = resp.json()
return {
"address": address,
"n_tx": data.get("n_tx", 0),
"total_received_satoshi": data.get("total_received", 0),
"total_sent_satoshi": data.get("total_sent", 0),
"final_balance_satoshi": data.get("final_balance", 0),
"transactions": data.get("txs", []),
}
Step 3: Map Fund Flow and Identify Clusters
Trace outputs from the ransom wallet to downstream addresses:
Fund Flow Analysis:
━━━━━━━━━━━━━━━━━━
Victim Payment ──► Ransom Wallet ──► Consolidation Wallet
├─► Mixer/Tumbler Service
├─► Exchange Deposit Address
└─► Peel Chain (sequential small outputs)
Key indicators:
- Consolidation: Multiple ransom payments aggregated into one wallet
- Peel chains: Sequential transactions with diminishing outputs
- Mixer usage: Funds sent to known mixer addresses (Wasabi, Samourai, ChipMixer)
- Exchange cashout: Deposits to known exchange wallets (Binance, Kraken hot wallets)
Step 4: Cross-Reference with Known Wallet Databases
Check addresses against known ransomware infrastructure:
# Check WalletExplorer for entity identification
def check_wallet_explorer(address):
url = f"https://www.walletexplorer.com/api/1/address?address={address}&caller=research"
resp = requests.get(url, timeout=30)
data = resp.json()
return {
"wallet_id": data.get("wallet_id"),
"label": data.get("label", "Unknown"),
"is_exchange": data.get("is_exchange", False),
}
Step 5: Generate Attribution Report
Compile findings into a structured intelligence report:
RANSOMWARE WALLET ANALYSIS REPORT
====================================
Ransom Address: bc1q...xyz
Family Attribution: LockBit 3.0 (based on ransom note format)
Total Received: 4.25 BTC ($178,500 at time of payment)
Total Sent: 4.25 BTC (wallet fully drained)
Number of Payments: 3 (likely 3 separate victims)
FUND FLOW:
Payment 1: 1.5 BTC → Consolidation wallet → Binance deposit
Payment 2: 1.0 BTC → Wasabi Mixer → Unknown
Payment 3: 1.75 BTC → Peel chain (12 hops) → OKX deposit
CLUSTER ANALYSIS:
Related wallets: 47 addresses identified in same cluster
Total cluster volume: 156.3 BTC ($6.5M USD)
First activity: 2024-01-15
Last activity: 2024-09-22
Verification
- Confirm wallet address format is valid before querying APIs
- Cross-reference transaction timestamps with known incident timelines
- Validate cluster associations by checking common-input-ownership heuristic
- Compare findings against OFAC SDN list for sanctioned addresses
- Verify exchange attribution against multiple sources (WalletExplorer, OXT, Chainalysis)
Key Concepts
| Term | Definition |
|---|---|
| UTXO | Unspent Transaction Output; the fundamental unit of Bitcoin that tracks ownership through a chain of transactions |
| Cluster Analysis | Grouping multiple Bitcoin addresses believed to be controlled by the same entity using common-input-ownership and change-address heuristics |
| Peel Chain | A laundering pattern where funds are sent through many sequential transactions, each peeling off a small amount to a new address |
| CoinJoin/Mixer | Privacy techniques that combine multiple users' transactions to obscure the link between sender and receiver |
| Common Input Ownership | Heuristic that assumes all inputs to a single transaction are controlled by the same entity |
Tools & Systems
- Chainalysis Reactor: Enterprise blockchain investigation platform with entity attribution and cross-chain tracing
- WalletExplorer: Free tool that clusters Bitcoin addresses and labels known services (exchanges, mixers, markets)
- OXT.me: Advanced Bitcoin transaction visualization with UTXO graph analysis
- Blockstream.info: Open-source Bitcoin block explorer with full API access
- blockchain.com API: Free API for querying Bitcoin address balances and transaction histories
- OFAC SDN List: U.S. Treasury sanctioned address list for compliance checking