Create forensically sound bit-for-bit disk images using dd and dcfldd while preserving evidence integrity through hash verification.
日本語の概要は準備中です。原文の説明を表示しています。
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.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
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 |
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概要と使いどころ
Create forensically sound bit-for-bit disk images using dd and dcfldd while preserving evidence integrity through hash verification.
日本語の概要は準備中です。原文の説明を表示しています。
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.
日本語の概要は準備中です。原文の説明を表示しています。
Detect dangerous ACL misconfigurations in Active Directory using ldap3 to identify GenericAll, WriteDACL, and WriteOwner abuse paths
日本語の概要は準備中です。原文の説明を表示しています。
Perform static analysis of Android APK malware samples using apktool for decompilation, jadx for Java source recovery, and androguard for permission analysis, manifest inspection, and suspicious API call detection.
日本語の概要は準備中です。原文の説明を表示しています。
Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect BOLA/IDOR attacks, rate limit bypass, credential scanning, and injection attempts. Uses pandas for statistical analysis of request patterns and anomaly detection. Use when investigating API abuse or building API-specific threat detection rules.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze advanced persistent threat (APT) group techniques using MITRE ATT&CK Navigator to create layered heatmaps of adversary TTPs for detection gap analysis and threat-informed defense.
日本語の概要は準備中です。原文の説明を表示しています。