SKILLS/analyzing-ransomware-payment-wallets/SKILL.md
Traces ransomware cryptocurrency payment flows using blockchain analysis tools such as Chainalysis Reactor, WalletExplorer, and blockchain.com APIs. Identifies wallet clusters, tracks fund movement through mixers and exchanges, and supports law enforcement attribution. Activates for requests involving ransomware payment tracing, bitcoin wallet analysis, cryptocurrency forensics, or blockchain intelligence gathering.
npx skillsauth add pinkpixel-dev/skills-collection-1 analyzing-ransomware-payment-walletsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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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.
requests, json, and hashlib librariesParse 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)
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", []),
}
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)
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),
}
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
| 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 |
testing
When the user wants a full ASO health audit, review their App Store listing quality, or diagnose why their app isn't ranking. Also use when the user mentions "ASO audit", "ASO score", "why am I not ranking", "listing review", or "optimize my app store page". For keyword-specific research, see keyword-research. For metadata writing, see metadata-optimization.
testing
Clarify requirements before implementing. Use when serious doubts arise.
tools
Complete reference and build guide for ASI:One (ASI1) — the AI platform by Fetch.ai built for agentic, Web3-native applications. Use this skill IMMEDIATELY and ALWAYS when the user mentions ASI1, ASI:One, Fetch.ai AI API, building with ASI1, integrating ASI:One, asking about ASI1 models, tool calling with ASI1, ASI1 image generation, ASI1 agentic LLM, Agentverse, uagents, Agent Chat Protocol, structured output with ASI1, or OpenAI-compatible wrappers for ASI1. Also trigger when the user says things like "use ASI1 instead of OpenAI", "build an app with ASI:One", "ASI1 API", or references docs.asi1.ai. This skill covers everything needed to build production apps - setup, all models, all API features, tool calling, image gen, agentic orchestration, structured data, session management, streaming, LangChain integration, uagents / Agent Chat Protocol, and TypeScript/Node.js patterns.
data-ai
When the user wants to analyze their own app's actual performance data from App Store Connect — real downloads, revenue, IAP, subscriptions, trials, or country breakdowns synced via Appeeky Connect. Use when the user asks about "my downloads", "my revenue", "how is my app performing", "ASC data", "sales and trends", "my subscription numbers", "App Store Connect metrics", or wants to compare periods or top markets. For third-party app estimates, see app-analytics. For subscription analytics depth, see monetization-strategy.