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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 3,944 users Direct on-chain reads 🔐 Non-custodial — no wallet connect required Sub-5-second scan 🔗 Solana · Ethereum · Base · Arbitrum · BNB · Polygon · Avalanche 📊 45,294 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
FreeFirst Check
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

Phishing wallet detectors represent a technical mechanism designed to identify and restrict interactions with addresses known or suspected to be involved in malicious activities such as scams, theft, or phishing attacks. These detectors can be implemented either within the token’s smart contract itself or externally through off-chain systems that interface with the contract. When embedded in the contract, the detector often manifests as a blacklist—a mapping of flagged wallet addresses—which actively prevents those addresses from transferring tokens or engaging with the contract in meaningful ways. Alternatively, the contract may query an external oracle or registry that maintains a dynamic list of suspicious addresses, enabling the contract to block transactions with those addresses in real time.

This structural approach to phishing detection aims to safeguard token holders by limiting the circulation of tokens to and from compromised or fraudulent wallets. Such a mechanism, however, operates invisibly with respect to market data; price charts and volume metrics do not reveal the existence or efficacy of a phishing wallet detector. Instead, it requires direct inspection of the contract code or an analysis of its integration with external data sources. This means that the presence and capabilities of a phishing detector are often opaque to casual observers, adding a layer of complexity to risk assessment.

One critical factor influencing the risk profile of phishing wallet detectors is the degree of control held by the contract owner or governing authority over the blacklist or detection list. If the list is mutable and can be updated by a single owner or centralized entity after the token’s launch, the potential for abuse arises. In such cases, the owner could theoretically blacklist legitimate token holders or arbitrarily restrict transfers, effectively controlling who can exit the token ecosystem or participate in trading. This introduces a structural risk where the owner’s power over the blacklist may be wielded not solely for protection but also as a tool for censorship or manipulation. Conversely, when the blacklist is immutable—hardcoded and unchangeable after deployment—or managed by a decentralized and transparent oracle system, the risk of arbitrary or malicious censorship is significantly reduced. This distinction is crucial because the presence of a phishing wallet detector alone does not by itself confirm malicious intent; the context of its governance and update mechanisms holds substantial weight in the risk evaluation.

Beyond the basics of blacklist mutability, additional governance controls can influence the trustworthiness of a phishing wallet detector. For instance, the implementation of multisignature (multisig) approvals or timelock delays on blacklist modifications introduces a system of checks and balances. These features require multiple parties to consent before any changes are made, reducing the likelihood of unilateral censorship or abuse. In contrast, contracts that consolidate control over blacklist management alongside other powerful features—such as pause functions that temporarily halt all token transfers or adjustable sell taxes that impose variable fees on sells—amplify exit risk. When the same authority controls these multiple levers, the combination can be used strategically to trap holders, block exits, or impose punitive costs, which may precipitate rapid liquidity withdrawal and sharp price declines, especially in tokens with thin liquidity pools relative to their market capitalization.

Transparency around the source and update process of the phishing wallet list adds another dimension to the analysis. Open-source lists maintained by community consensus or vetted by reputable third parties tend to inspire greater confidence than opaque, owner-managed registries that lack public accountability. Historical on-chain data showing how often the blacklist has been updated, the frequency of freeze or unblock events, and the context of these changes can provide valuable insight into whether the detector has been employed responsibly or exploited as a tool for exit blocking. Yet, the mere presence of blacklist updates or freeze events does not inherently imply bad faith; legitimate security responses to emerging threats can necessitate dynamic blacklist management.

When phishing wallet detectors are integrated with other structural patterns common in the crypto ecosystem, the overall risk profile can become more complex. For example, if the contract is upgradeable via proxy mechanisms, the owner might extend or modify the phishing detection capabilities post-launch, potentially expanding censorship powers without token holder consent. Similarly, if honeypot mechanics—such as restricting token transfers from certain addresses—exist alongside a phishing wallet detector, the combined effect can be to create traps that prevent holders from selling or transferring their tokens. This layering of control mechanisms can be particularly dangerous in environments with low liquidity pool depths, where rapid liquidity removal can lead to cascading price crashes.

Conversely, in ecosystems with robust governance structures—where blacklist management is decentralized, transparent, and separated from other contract controls—the incorporation of a phishing wallet detector may serve as a net positive security feature. By proactively blocking interactions with known malicious wallets, the detector can reduce the likelihood of token theft or fraud, enhancing holder confidence. In such cases, the detector does not necessarily increase exit risk but contributes to a safer trading environment. However, the actual impact depends heavily on the interplay between the detector’s governance, the contract’s other control features, and the broader tokenomics and liquidity context.

In sum, phishing wallet detectors embody a nuanced structural pattern whose risk implications hinge on governance transparency, control centralization, and interaction with other contract features. While they can serve as valuable security tools, their presence alone neither guarantees protection nor confirms malicious intent. Instead, a thorough analytical approach must consider the mutable nature of the blacklist, the presence of multisig or timelock governance, the contract’s other control points, and the overall liquidity profile to assess the genuine risk landscape surrounding these mechanisms.

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 →