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[ on-chain  ·  solana + evm ]

Token Risk Check

Paste any contract address for an instant on-chain risk assessment -- honeypot detection, liquidity analysis, holder concentration, and contract permissions.

Read the contract before the contract reads you. Honeypot, rug, and scam detection from on-chain state — not market data.

⚠️ Token Risk Check
✓ On-Chain Analysis
🔒 No Signup
⚡ Results in Seconds
🔍 Honeypot detection
💧 LP lock status
👥 Holder concentration
⚡ Solana + EVM
4.7 / 5 from 3,776 users Direct on-chain reads 🔐 Non-custodial — no wallet connect required Sub-5-second scan 🔗 Solana · Ethereum · Base · Arbitrum · BNB · Polygon · Avalanche 📊 52,242 risk checks run
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Unlimited Token Risk Checks

Verify every contract before buying. Honeypot detection, LP lock analysis, and holder concentration reviews across Solana and EVM.
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Live Detections
127 scans today
49K+Scans Run
6Chains
15+Risk Signals
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What the checker detects
Example signals · run a scan to see live results
⚠️Sell TaxDETECTED
💧LP LockUNLOCKED
🔑Mint AuthorityACTIVE
OwnershipRENOUNCED
🐋Whale Wallet42%
📅Token Age3 DAYS
🚨Approval RiskHIGH
CooldownACTIVE
🔄Last Update48H AGO
📉Liquidity 24h-12%
🚫Transfer LockENCODED
Freeze AuthENABLED
📋ContractVERIFIED
💰LP Depth$48K
🔗Blacklist FnPRESENT
🔍
Honeypot Detection
Simulates sell transactions to detect transfer locks, fee traps, and whitelist-only exit conditions before you buy in. Reads the contract directly — not market data. Works across Solana SPL tokens and all major EVM chains.
💧
Liquidity & Holders
Reviews pool depth, LP lock status, and top wallet percentages. Surfaces unlocked pools and concentrated wallets before the price collapses.
Results in Seconds
On-chain read — no API delays, no market data lag. Raw contract analysis returned in under 5 seconds.
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Token Risk Analysis -- Contract, Liquidity & Holders

🔗 TL;DR

A token's risk lives in three places: contract permissions (can the dev mint, freeze, or block sells?), liquidity structure (is the LP locked and deep enough to exit?), and holder distribution (can a handful of wallets dump the entire float?). The checker above reads all three directly on-chain in under five seconds.

Scan time< 5 sec
Signals checked15+
Cost (first check)Free

Fee on transfer risk revolves around a particular structural pattern embedded in a token’s smart contract where a fee is deducted every time tokens move between addresses. While this mechanism might appear straightforward as a simple transaction cost, its underlying implementation can vary widely and produce very different economic and security implications. The subtle ways in which the fee is assessed, allocated, and controlled play a critical role in shaping the token’s risk profile, yet the surface-level uniformity of a fee on transfer can obscure these complexities. This can sometimes create incentives or constraints that significantly affect market behavior, liquidity, and holder dynamics.

At a basic level, the fee deducted on each transfer can be directed toward several possible destinations. Some contracts burn the fee, effectively reducing total supply and creating a deflationary pressure. Others redistribute the fee proportionally to existing holders, incentivizing holding by rewarding long-term participants. Yet, in many cases, the fee is routed to a specific wallet controlled by the project team or a designated entity. This distinction is analytically important because it determines whether the fee serves a collective economic function or introduces a centralized extraction point. Fees sent to a private wallet controlled by a small group or a single key, especially without multisignature safeguards, can create a vulnerability where the controller might extract value from every transaction without broader community consent.

Ownership and control over this fee destination address arguably carries the most weight when assessing fee on transfer risk. If the fee proceeds flow to an address managed by a single private key or an entity with concentrated control, this can lead to potential misuse. The mechanism here is straightforward: whoever holds the private key can systematically drain value from each trade or transfer, potentially destabilizing liquidity pools or manipulating market dynamics. This risk is heightened if the controlling entity can arbitrarily move or convert these fees without transparent governance. Conversely, if the fee is automatically burned or redistributed proportionally to holders, the risk profile shifts significantly toward lower structural risk. However, it is important to note that even burning fees can have unintended consequences if the burn rate is excessively high or dynamically adjustable, as it can distort tokenomics and user incentives in unpredictable ways.

Another layer of complexity arises when considering smart contract mutability, often facilitated through proxy upgrade patterns. Proxy upgrades enable contract logic to be changed post-deployment without issuing a new token. This means that fee parameters, including the fee percentage or recipient address, can be altered after launch. In such cases, the risk surface expands because the fee structure can be modified in ways that were not initially visible or expected by token holders. On networks with high base fees, elevated transaction costs can discourage frequent trading, which might mask malicious fee increases or the introduction of new fee destinations hidden within a contract upgrade. On the other hand, on low-fee networks, the low cost of transactions can enable attackers to rapidly exploit fee mechanisms or spam the network to trigger fees repeatedly, amplifying potential loss vectors. The interaction between contract mutability and network fee economics creates a nuanced landscape where fee on transfer risk manifests differently depending on external and internal technical factors.

It is crucial to underscore that the presence of a fee on transfer pattern alone does not inherently indicate malicious intent or exploitable risk. Many legitimate and well-structured projects leverage transfer fees to fund ongoing development, contribute to liquidity pools, or reward holders. These fees can be part of transparent and well-governed tokenomics that align incentives between users and the project team. The pattern becomes concerning primarily when fee flows are concentrated without multisig protection or when the contract’s upgradeability allows unilateral changes to fee parameters post-launch. Surface signals such as a fixed fee percentage or even the presence of a fee on transfer mechanism alone do not confirm risk. Instead, the critical factors lie in governance transparency, control mechanisms, and the ability—or inability—to change fee parameters after deployment.

Further complicating analysis is the question of holder behavior in light of fee on transfer structures. Fees that disproportionately affect certain transaction types, such as sells versus buys, can distort market behavior or trap liquidity. For instance, a higher fee on selling might discourage liquidity provision or lead to price suppression, while lower or zero fees on buying encourage accumulation. This asymmetry can sometimes create economic incentives that are misaligned with open market functioning, potentially leading to reduced volume or other unintended consequences. In some cases, these dynamics can be exploited by insiders or coordinated actors who understand the fee structure better than the broader market.

Lastly, liquidity pool characteristics must be considered when evaluating fee on transfer risk. Pools with shallow depth relative to market cap can exacerbate the impact of fee deductions on price volatility and slippage. This can sometimes create feedback loops where fees reduce liquidity, which in turn increases price impact and discourages trading activity. Combined with centralized fee control, thin liquidity pools can be conducive environments for value extraction or manipulation. Therefore, the context of liquidity alongside fee mechanisms is a vital dimension in any comprehensive risk assessment.

In sum, fee on transfer risk requires a layered analytical approach that examines not just the fee percentage but the destination, control mechanisms, contract mutability, network fee conditions, and liquidity context. The pattern itself does not confirm malicious intent but can sometimes signal structural vulnerabilities that warrant close scrutiny. Understanding the interplay of these factors helps reveal how ostensibly simple transfer fees can embed complex economic incentives and potential risks within a token’s architecture.

Pre-buy on-chain checklist

  • Mint authority renouncedConfirms supply is capped — no new tokens can be issued post-launch.
  • LP locked or burnedLiquidity cannot be removed in a single transaction. Lock duration and locker contract are both verifiable on-chain.
  • !Top 10 holders under 40%Lower concentration means coordinated dumps are mechanically harder. Above 40% is a structural caution.
  • !No active freeze authorityActive freeze means wallets can be paused at the contract level — no exit possible during a freeze.
  • ×No transfer restrictionsThe transfer function should accept any holder selling. Encoded sell blocks, whitelist exits, and hidden tax functions are honeypot signatures.

Frequently asked questions

Verify the contract address before you buy in. Paste it into the scanner above for the full on-chain breakdown.

Why on-chain signals matter

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Solana + EVM Checks SPL tokens and EVM contracts across Ethereum, Base, Arbitrum, BNB Chain, Polygon, and Avalanche.
⚙ Methodology
Every risk verdict is generated from three on-chain reads run in parallel: (1) direct contract bytecode analysis for honeypot patterns, mint/freeze authority, and blacklist functions; (2) liquidity pool inspection for LP lock status, depth, and removable percentage; (3) holder distribution from token-account snapshots. No editorial opinion is layered on the output. Read the full methodology →