Chain Analysis/Forensics Skill

Expert on-chain analysis and transaction forensics for security investigations and incident response.

Capabilities

• Transaction Tracing: Follow fund flows across addresses and protocols
• Pattern Detection: Identify suspicious patterns (wash trading, rugpulls, sandwich attacks)
• MEV Analysis: Analyze MEV activity and flashbots bundles
• Address Clustering: Group related addresses and identify ownership
• Cross-Chain Tracking: Track bridged assets across chains
• Forensic Reports: Generate detailed investigation reports

MCP/Tool Integration

Tool	Purpose	Reference
Phalcon MCP	Transaction analysis, exploit detection	phalcon-mcp
whale-tracker-mcp	Large transaction monitoring	whale-tracker
bicscan-mcp	Address risk scoring	bicscan
dune-analytics-mcp	Custom queries, analytics	dune
Etherscan MCP	Block explorer data	etherscan

Transaction Tracing

Basic Flow Analysis

# Get transaction details
cast tx 0xTxHash --rpc-url $RPC

# Decode transaction input
cast 4byte-decode $(cast tx 0xTxHash --rpc-url $RPC | grep input)

# Get internal transactions via Etherscan API
curl "https://api.etherscan.io/api?module=account&action=txlistinternal&txhash=0xTxHash&apikey=$KEY"

Tracing with Tenderly/Phalcon

// Phalcon trace analysis
const trace = await phalcon.analyzeTransaction(txHash);

// Identify key flows
const flows = {
  valueTransfers: trace.transfers.filter(t => t.value > 0),
  tokenTransfers: trace.erc20Transfers,
  internalCalls: trace.calls.filter(c => c.type === 'CALL'),
  delegateCalls: trace.calls.filter(c => c.type === 'DELEGATECALL')
};

Address Analysis

Profile Building

const addressProfile = {
  address: '0x...',

  // Basic metrics
  metrics: {
    firstTransaction: '2022-01-15',
    transactionCount: 1234,
    uniqueInteractions: 56,
    totalValueTransferred: '1000 ETH'
  },

  // Activity patterns
  patterns: {
    activeHours: [14, 15, 16], // UTC hours
    frequentProtocols: ['Uniswap', 'Aave'],
    averageTxFrequency: '5/day'
  },

  // Risk indicators
  riskFlags: {
    tornadoCashInteraction: false,
    sanctionedAddressInteraction: false,
    knownExploitPattern: false,
    highFrequencyTrading: true
  },

  // Related addresses
  clusters: [
    { address: '0x...', confidence: 0.95, reason: 'Funding source' },
    { address: '0x...', confidence: 0.8, reason: 'Common recipient' }
  ]
};

Clustering Heuristics

1. Deposit Address Reuse: Same deposit addresses across exchanges
2. Multi-Input Transactions: Addresses used together in single tx
3. Timing Analysis: Coordinated transaction timing
4. Amount Patterns: Matching amounts minus fees
5. Contract Interactions: Shared smart contract usage patterns

MEV Analysis

Sandwich Attack Detection

-- Dune Analytics query for sandwich detection
WITH potential_sandwiches AS (
  SELECT
    block_number,
    transaction_index,
    "from",
    "to",
    value,
    LAG("from") OVER (PARTITION BY block_number ORDER BY transaction_index) as prev_from,
    LEAD("from") OVER (PARTITION BY block_number ORDER BY transaction_index) as next_from
  FROM ethereum.transactions
  WHERE block_number > {{start_block}}
)
SELECT *
FROM potential_sandwiches
WHERE prev_from = next_from
  AND prev_from != "from"
  -- Additional filters for DEX interactions

Flashbots Bundle Analysis

// Analyze flashbots bundles
const bundleAnalysis = {
  bundleHash: '0x...',

  transactions: [
    { index: 0, type: 'frontrun', profit: '0.5 ETH' },
    { index: 1, type: 'victim', loss: '0.3 ETH' },
    { index: 2, type: 'backrun', profit: '0.4 ETH' }
  ],

  totalMEV: '0.9 ETH',
  miner: '0x...',
  minerPayment: '0.45 ETH'
};

Suspicious Pattern Detection

Rugpull Indicators

const rugpullIndicators = {
  // Contract analysis
  contract: {
    hasHiddenMint: true,          // Owner can mint unlimited
    hasDisableTrading: true,      // Can disable selling
    hasBlacklist: true,           // Can block addresses
    highOwnershipConcentration: true, // >50% in few wallets
    unverifiedContract: true,
    recentDeployment: true        // <7 days old
  },

  // Token metrics
  tokenMetrics: {
    liquidityLocked: false,
    lockDuration: 0,
    holderCount: 50,
    top10HoldersPercent: 85
  },

  // Trading patterns
  tradingPatterns: {
    artificialVolume: true,       // Wash trading detected
    sellPressure: 'high',
    buyWallsArtificial: true
  },

  riskScore: 95 // 0-100
};

Wash Trading Detection

-- Identify circular trading
WITH transfers AS (
  SELECT
    "from",
    "to",
    contract_address,
    value,
    block_time
  FROM erc20_ethereum.evt_Transfer
  WHERE contract_address = {{token_address}}
    AND block_time > NOW() - INTERVAL '7 days'
)
SELECT
  a."from" as trader,
  COUNT(DISTINCT b."to") as counterparties,
  SUM(a.value) as total_volume,
  COUNT(*) as trade_count
FROM transfers a
JOIN transfers b ON a."to" = b."from" AND a."from" = b."to"
WHERE a.block_time < b.block_time
  AND b.block_time < a.block_time + INTERVAL '1 hour'
GROUP BY a."from"
HAVING COUNT(*) > 10
ORDER BY total_volume DESC

Cross-Chain Tracking

Bridge Transaction Mapping

const crossChainTrace = {
  originChain: 'ethereum',
  originTx: '0x...',
  originAddress: '0x...',

  bridge: 'Wormhole',
  bridgeMessage: '0x...',

  destinationChain: 'arbitrum',
  destinationTx: '0x...',
  destinationAddress: '0x...',

  amount: '100 USDC',
  timestamp: {
    origin: '2024-01-15T10:00:00Z',
    destination: '2024-01-15T10:15:00Z'
  }
};

Multi-Chain Address Mapping

// Track address across chains
const multiChainProfile = {
  primaryAddress: '0x...',

  chainPresence: {
    ethereum: { address: '0x...', balance: '10 ETH', txCount: 500 },
    arbitrum: { address: '0x...', balance: '5 ETH', txCount: 200 },
    optimism: { address: '0x...', balance: '3 ETH', txCount: 100 },
    polygon: { address: '0x...', balance: '1000 MATIC', txCount: 50 }
  },

  bridgeHistory: [
    { from: 'ethereum', to: 'arbitrum', amount: '5 ETH', date: '2024-01-10' },
    { from: 'ethereum', to: 'optimism', amount: '3 ETH', date: '2024-01-12' }
  ]
};

Forensic Report Template

# Blockchain Forensic Investigation Report

## Executive Summary
- **Investigation ID**: INV-2024-XXX
- **Date Range**: 2024-01-01 to 2024-01-15
- **Subject**: [Address/Protocol/Incident]
- **Conclusion**: [Brief finding]

## Key Findings

### 1. Fund Flow Analysis
[Diagram and description of fund movements]

### 2. Address Attribution
| Address | Attribution | Confidence | Evidence |
|---------|-------------|------------|----------|
| 0x... | Attacker | High | Funding pattern |
| 0x... | Mixer | Medium | Tornado Cash |
| 0x... | Exchange | High | Known deposit |

### 3. Timeline
| Timestamp | Event | Addresses | Amount |
|-----------|-------|-----------|--------|
| T+0 | Initial exploit | 0x... | 1000 ETH |
| T+1h | Consolidation | 0x... | 1000 ETH |
| T+2h | Mixer deposit | Tornado | 100 ETH |

### 4. Attack Vector
[Technical description of how the incident occurred]

### 5. Total Impact
- Funds Lost: $X
- Users Affected: Y
- Contracts Exploited: Z

## Appendix
- Full transaction list
- Address clustering data
- Supporting evidence

Process Integration

This skill integrates with:

• incident-response-exploits.js - Exploit investigation
• economic-simulation.js - Market impact analysis
• smart-contract-security-audit.js - Post-audit monitoring

Tools Reference

Tool	Purpose	URL
Etherscan	Explorer, API	etherscan.io
Dune Analytics	Custom queries	dune.com
Nansen	Wallet labels, flows	nansen.ai
Arkham Intelligence	Entity attribution	arkhamintelligence.com
Chainalysis Reactor	Investigation platform	chainalysis.com
TRM Labs	Risk scoring	trmlabs.com
Phalcon	Tx analysis	phalcon.blocksec.com

See Also

• agents/incident-response/AGENT.md - Incident commander agent
• skills/bug-bounty/SKILL.md - Disclosure coordination
• incident-response-exploits.js - Full incident process