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[ on-chain  ·  solana + evm ]

Scam Token Check

Verify the contract structure, on-chain trading history, and developer wallet activity before buying in.

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
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⚡ Results in Seconds
🔍 Honeypot detection
💧 LP lock status
👥 Holder concentration
⚡ Solana + EVM
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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

Exit scam detection in token contracts fundamentally revolves around identifying structural conditions that restrict, manipulate, or control exit liquidity. At its core, the issue is whether token holders can realistically liquidate their assets without encountering artificial or technical barriers imposed by the contract code. One of the most pervasive patterns involves transfer restrictions embedded directly within the token’s transfer function, often implemented through require() statements that revert sell transactions unless the sender’s address is explicitly whitelisted. This design creates a scenario where buyers can acquire tokens on the open market but are unable to sell unless granted permission, effectively creating a “soft honeypot” where exits are selectively enabled or disabled by contract owners or privileged parties.

Such whitelist-only exit mechanisms impose a stark asymmetry in token movement permissions. They give disproportionate control to a small set of addresses, often under owner discretion, while leaving the broader holder base exposed to illiquidity risks and potential capital lockup. This asymmetry is concerning because it can be used to engineer exit scams by allowing early insiders or privileged holders to sell freely while preventing others from doing so. However, it is important to note that the mere presence of transfer restrictions does not necessarily confirm malicious intent. In some cases, these mechanisms are implemented for legitimate compliance reasons, staged liquidity releases, or to support phased token sale strategies that are disclosed transparently.

Beyond transfer restrictions, other contract features that factor into exit scam detection include active mint authorities, freeze functions, and blacklist capabilities. Contracts with active mint authority can increase token supply arbitrarily, which can dilute existing holders and artificially depress prices if misused. Freeze functions allow the contract owner or designated parties to pause transfers globally or freeze specific wallets, effectively halting exit opportunities for affected holders. Blacklist functions operate similarly by selectively blocking certain addresses from selling. The combination of these mechanisms creates a multi-faceted toolkit for controlling liquidity and exit paths. Yet, the presence of these tools alone does not inherently indicate nefarious behavior. Instead, the risk profile escalates significantly when these permissions remain owner-modifiable post-launch and lack transparent operational justification.

A critical factor in assessing exit scam risk is the governance model surrounding these control permissions. If the contract owner retains the ability to arbitrarily modify whitelists, blacklists, or freeze states without restrictions, it preserves a latent capability to block exits selectively at will. This mutable control is a classic enabler of soft honeypots and exit scams, as it leaves holders vulnerable to sudden and unexplained illiquidity. Conversely, if these permissions are renounced or locked—meaning the owner relinquishes the ability to alter crucial parameters—or if the whitelist or blacklist usage is governed by explicit, time-locked, or multisig-controlled governance frameworks, the risk diminishes. Such frameworks introduce transparency and accountability that can mitigate the potential for abuse.

Another layer of analysis involves upgradeable proxy patterns embedded in the token’s smart contract architecture. Upgradeability allows the contract logic to be changed post-deployment, which can be a double-edged sword. Without proper safeguards such as timelocks or multisig controls, upgradeability can enable sudden and opaque changes to exit permissions, effectively changing the rules around token transfers after investors have committed capital. This can facilitate exit scams by introducing new restrictions or revoking previously granted exit rights. Monitoring whether a token contract uses upgradeable proxies and evaluating the governance controls around upgrades is therefore a critical part of exit scam detection.

Historical on-chain activity provides supplementary insight. If blacklist or freeze functions have been actively used to restrict transfers, it signals a willingness to curtail liquidity and can indicate a higher risk of malicious exit manipulation. Conversely, if such functions exist but remain dormant, or if the contract’s governance is transparent and time-locked, it suggests a more benign use case or cautious operational approach. Market context also interacts with these structural patterns to influence risk. Thin liquidity pools—especially those significantly smaller than the token’s market cap—amplify vulnerability to price manipulation and forced illiquidity. In such conditions, even moderate exit restrictions can trap capital and create downward price pressure. In contrast, deep and active pools with robust trading volumes can provide some buffer against immediate exit risks, though they do not eliminate underlying governance concerns.

When restrictive exit patterns coincide with other common tokenomic features—such as cliff unlocks of large token allocations released into thin liquidity pools—the outcome can resemble protracted price decline rather than sudden crashes. The inability of holders to sell freely causes selling pressure to accumulate off-chain, often resulting in gradual price erosion over time. Furthermore, the owner’s ability to mint additional tokens or freeze specific wallets can exacerbate downward spirals by diluting supply or selectively locking capital. Yet, it must be emphasized that these dynamics do not automatically confirm an exit scam. In some scenarios, they reflect complex tokenomics designed for staged releases, liquidity management, or compliance with regulatory frameworks. The key differentiator remains transparency around permissions, governance controls, and operational intent.

In summary, exit scam detection is a nuanced exercise that requires dissecting contract code to identify structural exit restrictions, analyzing governance frameworks controlling those restrictions, and contextualizing these elements within market liquidity and tokenomics. Transfer restrictions such as whitelist-only exits, combined with active mint, freeze, and blacklist functions, create a potent toolkit for controlling liquidity and exit paths. However, these patterns alone do not confirm malicious intent. Instead, the risk intensifies when these permissions remain mutable, opaque, and ungoverned post-launch, especially in conjunction with upgradeable proxies lacking safeguards. Evaluating on-chain usage of restrictive functions and market liquidity dynamics provides additional clarity. Ultimately, exit scam detection hinges on discerning whether these structural patterns serve transparent operational purposes or mask latent exit traps that can be exploited by controlling parties.

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

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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 →