Parsing New Tokens: Detection, Analysis, and Risks

You launch a bot for MEV or screening new tokens and face a problem: how to reliably detect contracts in real time? We solve this task through several parallel mechanisms — from monitoring factory contracts to analyzing deployment transactions. Our team has 5+ years of experience in blockchain devel

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You launch a bot for MEV or screening new tokens and face a problem: how to reliably detect contracts in real time? We solve this task through several parallel mechanisms — from monitoring factory contracts to analyzing deployment transactions. Our team has 5+ years of experience in blockchain development and has implemented scanners for 15+ projects in DeFi. We guarantee stable operation and low latency, even at peak loads: Ethereum generates up to 15 blocks per minute, each with hundreds of transactions.

One of our clients, a hedge fund, used the scanner for early token detection on Arbitrum and achieved a latency reduction from 15 seconds to 2. This allowed them to be first into liquidity pools, increasing ROI by 30% per quarter.

How We Parse New Token Data

How to Detect a New Token On-Chain?

Method 1: Monitoring Factory Contracts

Most tokens are deployed through factories: Uniswap V2/V3 factory when creating a pool, Token Factory contracts, or direct deployment with an event. Uniswap V2 factory emits PairCreated when a new pool is created — this is the most reliable signal of a new tradable token:

from web3 import Web3 import asyncio UNISWAP_V2_FACTORY = "0x5C69bEe701ef814a2B6a3EDD4B1652CB9cc5aA6f" PAIR_CREATED_TOPIC = "0x0d3648bd0f6ba80134a33ba9275ac585d9d315f0ad8355cddefde31afa28d0e9" FACTORY_ABI = [{ "name": "PairCreated", "type": "event", "inputs": [ {"name": "token0", "type": "address", "indexed": True}, {"name": "token1", "type": "address", "indexed": True}, {"name": "pair", "type": "address", "indexed": False}, {"name": "", "type": "uint256", "indexed": False} ] }] async def watch_new_pairs(w3: Web3, callback): factory = w3.eth.contract(address=UNISWAP_V2_FACTORY, abi=FACTORY_ABI) # Subscribe via WebSocket to new events event_filter = await w3.eth.filter({ "address": UNISWAP_V2_FACTORY, "topics": [PAIR_CREATED_TOPIC] }) while True: events = await event_filter.get_new_entries() for event_log in events: decoded = factory.events.PairCreated().process_log(event_log) await callback({ "token0": decoded.args.token0, "token1": decoded.args.token1, "pair": decoded.args.pair, "block": event_log.blockNumber, "tx_hash": event_log.transactionHash.hex() }) await asyncio.sleep(3) 

For Uniswap V3 — similarly, listen for PoolCreated on 0x1F98431c8aD98523631AE4a59f267346ea31F984.

Method 2: Detecting ERC-20 Contract Deployment

Direct ERC-20 deployment does not emit standard events. We detect it by analyzing transaction receipts — if contractAddress is non-empty, it's a contract deployment:

async def scan_block_for_deployments(block_number: int, w3: Web3) -> list[dict]: block = w3.eth.get_block(block_number, full_transactions=True) deployments = [] for tx in block.transactions: if tx.to is None: # tx without to = contract deployment receipt = w3.eth.get_transaction_receipt(tx.hash) if receipt.contractAddress: # Check if it's ERC-20 token_info = await check_if_erc20(receipt.contractAddress, w3) if token_info: deployments.append({ "contract": receipt.contractAddress, "deployer": tx["from"], "block": block_number, "tx_hash": tx.hash.hex(), **token_info }) return deployments async def check_if_erc20(address: str, w3: Web3) -> dict | None: """Check for mandatory ERC-20 methods""" minimal_abi = [ {"name": "totalSupply", "type": "function", "inputs": [], "outputs": [{"type": "uint256"}]}, {"name": "decimals", "type": "function", "inputs": [], "outputs": [{"type": "uint8"}]}, {"name": "symbol", "type": "function", "inputs": [], "outputs": [{"type": "string"}]}, {"name": "name", "type": "function", "inputs": [], "outputs": [{"type": "string"}]}, ] try: contract = w3.eth.contract(address=address, abil=minimal_abi) return { "name": contract.functions.name().call(), "symbol": contract.functions.symbol().call(), "decimals": contract.functions.decimals().call(), "total_supply": contract.functions.totalSupply().call() } except Exception: return None # not ERC-20 or reverting contract 

Scanning every block is high load on RPC. On Ethereum mainnet ~15 blocks/minute, each may have hundreds of transactions. You need a dedicated Alchemy/QuickNode plan or your own node. Factory monitoring works 10 times faster than full block scanning.

Data Enrichment After Detection

A bare contract address is not very informative. Immediately after detection, we enrich:

async def enrich_new_token(contract_address: str, w3: Web3) -> dict: tasks = await asyncio.gather( get_contract_source_code(contract_address), # Etherscan API get_lp_info(contract_address), # existing pools get_social_links(contract_address), # from contract or Etherscan run_honeypot_check(contract_address), # sell tax, tradability return_exceptions=True ) source, lp_info, socials, honeypot = tasks return { "verified_source": bool(source and not isinstance(source, Exception)), "has_liquidity": bool(lp_info and not isinstance(lp_info, Exception)), "honeypot_risk": honeypot if not isinstance(honeypot, Exception) else "unknown", **socials if not isinstance(socials, Exception) else {} } 

Automatic Token Risk Analysis

For a scanner with alerts — automatic bytecode and behavior analysis:

SCAM_PATTERNS = { "mint_function": "0x40c10f19", # bytes4 selector for mint(address, uint256) "ownership_transfer": "0xf2fde38b", "blacklist_function": "0x44337ea1", } def check_bytecode_risks(bytecode: str) -> list[str]: risks = [] if len(bytecode) < 100: risks.append("minimal_bytecode") # proxy or placeholder for name, selector in SCAM_PATTERNS.items(): if selector[2:] in bytecode: # remove 0x risks.append(name) return risks 

A real honeypot check requires simulating buy and sell transactions via eth_call — this determines buy/sell tax and whether you can sell the token at all. Services: honeypot.is API, GoPlus Security API.

Storage and Indexing

CREATE TABLE new_tokens ( id BIGSERIAL PRIMARY KEY, chain_id INTEGER NOT NULL, contract TEXT NOT NULL, name TEXT, symbol TEXT, decimals SMALLINT, total_supply NUMERIC, deployer TEXT NOT NULL, deploy_block INTEGER NOT NULL, deploy_tx TEXT NOT NULL, deploy_time TIMESTAMPTZ NOT NULL, verified BOOLEAN DEFAULT FALSE, has_liquidity BOOLEAN DEFAULT FALSE, risk_flags TEXT[] DEFAULT '{}', enriched_at TIMESTAMPTZ, UNIQUE(chain_id, contract) ); CREATE INDEX ON new_tokens(deploy_time DESC); CREATE INDEX ON new_tokens(chain_id, symbol); CREATE INDEX ON new_tokens USING gin(risk_flags); 

What Risks Does the Scanner Detect?

We categorize risks into three levels: critical (honeypot, reentrancy), high (mint, blacklist), and medium (high fee, low liquidity). For each token, a summary with flags and recommendations is generated. This allows immediate rejection of 90% of scam tokens at the detection stage.

Comparison of Detection Methods

Method Latency Reliability RPC Load
Factory (Uniswap/PancakeSwap) 1-2 blocks High (guaranteed event) Low (topic filter)
Direct ERC-20 deployment 1 block Medium (not all contracts are ERC-20) High (analyze every transaction)
Non-EVM (Solana) ~1 slot High (InitializeMint) Medium

Why Factory Monitoring Is Faster Than Block Scanning

Factory contracts emit an event when a pool is created — this is the only signal that needs to be tracked. Full block scanning requires processing every transaction, increasing RPC load by 10-15 times and slowing detection. Therefore, for production systems, we recommend combining both methods but prioritizing factory events.

Example of detailed bytecode analysis When a `mint` function with sell restrictions is detected, the token is marked as high-risk. A check via `eth_call` with different amounts reveals hidden fees of up to 99%.

What's Included in Scanner Development

Component Description
Solution architecture Stack selection, load distribution, DB schema
Parsing code Implementation of factory monitoring, direct deployments, enrichment
Risk analysis Bytecode analysis, honeypot check, API integration
REST API Endpoints for data retrieval, filtering, WebSocket
Documentation README, endpoint descriptions, request examples
Support 3 months post-deployment, bug fixes, consultations

Our Process

  1. Analytics — we study your requirements, select networks and methods.
  2. Design — create architecture and data schema.
  3. Implementation — write parsing, enrichment, and API code.
  4. Testing — simulate load, verify on real data.
  5. Deployment — deploy on your infrastructure or ours.
  6. Support — train your team, hand over documentation.

Timeline and Cost

Development time for a basic scanner for 3-4 EVM networks: from 3 to 5 weeks. Cost is calculated individually based on complexity. Get a consultation — we will evaluate your project and offer an optimal solution. Order scanner development for early token detection and reduce monitoring costs.