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analyzing-ransomware-payment-wallets

Traces ransomware cryptocurrency payment flows using blockchain analysis tools such as Chainalysis Reactor, WalletExplorer, and blockchain.com APIs…

Skill by mukul975

IndexedApache-2.0★ 34,941
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

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About

Traces ransomware cryptocurrency payment flows using blockchain analysis tools such as Chainalysis Reactor, WalletExplorer, and blockchain.com APIs, identifying wallet clusters and tracking fund movement through mixers and exchanges to support law enforcement attribution. Use when tracing ransomware bitcoin payments, performing cryptocurrency wallet forensics, or gathering blockchain threat intelligence on extortion payments.

Use cases: security, finance, legal

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Permissions

What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 25, 2026.

Tools
No tools found
Secrets
None asked for
Install scripts
None found
Runs as
Python package

Network hosts it talks to 3

  • blockchain.info · found in code
  • blockstream.info · found in code
  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/analyzing-ransomware-payment-wallets

What's inside

Skill name
analyzing-ransomware-payment-wallets
Description
Traces ransomware cryptocurrency payment flows using blockchain analysis tools such as Chainalysis Reactor, WalletExplorer, and blockchain.com APIs, identifying wallet clusters and tracking fund movement through mixers and exchanges to support law enforcement attribution. Use when tracing ransomware bitcoin payments, performing cryptocurrency wallet forensics, or gathering blockchain threat intelligence on extortion payments.
License
Apache-2.0
Instructions
148 lines in SKILL.md · view on GitHub

Before installing

  • Ships executable scripts
  • Instructions call the network

Files (4)

  • LICENSE
  • SKILL.md
  • api-reference.md · references/
  • agent.py · scripts/

SKILL.md (first lines)

# 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`, and `hashlib` libraries
- 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:

```python
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:

```python
# 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
```

From mukul975/Anthropic-Cybersecurity-Skills, Apache-2.0.

More from mukul975/Anthropic-Cybersecurity-Skills

Signals

Stars
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Forks
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Open issues
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Last commit (this folder)
Aug 2, 2026 (2 months ago)
Last release
Jun 22, 2026 (4 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
Apache-2.0
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

More from mukul975

Cite this page

analyzing-ransomware-payment-wallets skill. Agent Mart. https://agentmart.dev/skills/mukul975-analyzing-ransomware-payment-wallets (last updated 2026-10-24)