Analyzing Ransomware Payment WalletsSAFE

817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io standard · Works with Claude Code, GitHub Copilot, Codex CLI, Cursor, Gemini CLI & 20+ platforms · 29 security domains ·

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
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.

  '
domain: cybersecurity
subdomain: ransomware-defense
tags:
- ransomware
- blockchain
- cryptocurrency
- forensics
- threat-intelligence
- bitcoin
version: 1.0.0
author: mahipal
license: Apache-2.0
nist_csf:
- PR.DS-11
- RS.MA-01
- RC.RP-01
- PR.IR-01
mitre_attack:
- T1657
- T1486
mitre_f3:
  version: '1.1'
  tactics:
  - monetization
  - stealth
  techniques:
  - id: F1018
    name: Convert to Cryptocurrency
    tactic: monetization
    source: f3
  - id: F1017
    name: Conversion to Physical Monetary Instruments
    tactic: monetization
    source: f3
  - id: F1017.001
    name: 'Conversion to Physical Monetary Instruments: Cash'
    tactic: monetization
    source: f3
  - id: F1047
    name: Transfer of funds
    tactic: monetization
    source: f3
  - id: F1045
    name: Structuring
    tactic: stealth
    source: f3
---

# 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
```

## Verification

- Confirm wallet address for

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

What the source does

Filesystem

none-observed

Network

declared (2 observation(s))

Shell

none-observed

Dependencies

pinned

Secrets in source

none-found

Findings (0)

No findings outside the package's declared scope.

Gates applied: no_behavioural_pass.