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[ on-chain  ·  solana + evm ]

Rug Pull Risk Check

Review the liquidity lock status, holder concentration, and contract permissions before committing to a position.

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
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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

Contracts exhibiting the honeypot pattern often incorporate a require() statement within their transfer function that reverts transactions originating from addresses not included on a designated whitelist. Mechanically, this design allows buy transactions to succeed while any attempt to sell tokens by non-whitelisted holders fails, effectively trapping funds within user wallets. This structural condition can be detected through a careful inspection of the contract’s transfer logic without the need to execute any trades on-chain. From the perspective of price charts, the token may appear to behave normally since buy orders clear and tokens accumulate in holders’ wallets, while sell orders never finalize. This creates a one-sided trade flow that can be exploited by the contract owner, restricting exit liquidity selectively and causing a fundamental asymmetry in how holders can interact with their assets.

The honeypot pattern becomes particularly risk-relevant when the whitelist is controlled and modifiable by the contract owner after deployment. This dynamic control enables the owner to selectively block sells from any holder at will, turning the contract into what is sometimes described as a soft honeypot. In such cases, buyers may enter with no indication of exit restrictions and only discover the inability to liquidate their holdings upon attempting to sell. The absence of transparency around the whitelist’s mutability significantly heightens exit risk because it introduces uncertainty about whether or when the owner might restrict transfers. Conversely, the honeypot pattern can be benign or even protective if the whitelist is immutable or employed for legitimate regulatory compliance reasons, such as restricting transfers to approved jurisdictions or known participants. In these scenarios, the whitelist functions more as a gating mechanism consistent with legal or operational constraints rather than a trap. The key distinction lies in the owner’s ability to alter the whitelist post-launch; immutable or time-locked whitelists materially reduce exit risk, while dynamic control preserves the potential for malicious exit blocking.

Additional contract features may exacerbate or mitigate risk when evaluated alongside the honeypot pattern. Adjustable sell tax parameters controlled by the owner, for instance, can be raised after launch to penalize or effectively block sells without triggering explicit transaction reverts. This creates a stealthy exit barrier by imposing prohibitive fees rather than outright failures. Similarly, the presence of active mint or freeze authorities on the token contract adds layers of control that can amplify exit risk if these privileges are retained without clear operational justification. Mint authority allows the owner to inflate the token supply arbitrarily, diluting holders, while freeze authority can prevent any token movement, effectively locking assets. Moreover, proxy upgradeability without the safeguard of multisignature or timelock protections increases the risk profile because the contract logic can be swapped post-deployment to introduce or remove exit restrictions abruptly. Conversely, transparent whitelist policies, renounced minting rights, a lack of owner-controlled sell tax parameters, and non-upgradeable contracts with immutable logic serve to mitigate such concerns by limiting owner control over critical token functions.

When the honeypot pattern is combined with other common contract conditions, such as an active blacklist function, pause capability, or upgradeable proxy mechanisms, the range of possible outcomes broadens significantly. These layered permissions can enable stealthy exit traps wherein holders find themselves unable to sell, transfer, or otherwise move tokens without prior warning. For example, the owner can pause all transfers temporarily or blacklist individual wallets, compounding exit risk by restricting movement beyond just sell attempts. This combination of controls can lead to forced freezes or sudden contract logic changes that undermine holder confidence and liquidity. However, it is important to acknowledge that these patterns can also exist in projects with legitimate operational reasons. Pause functions may be employed to respond rapidly to security incidents, while blacklists can enforce regulatory compliance or prevent fraudulent activity. Therefore, the mere presence of these patterns does not confirm malicious intent but rather establishes the structural capability for rug pull scenarios and exit manipulation.

Holder concentration within token ownership also interacts with these structural risk patterns in meaningful ways. When a single wallet or a small group of wallets controls an outsized percentage of circulating supply—above 40% in some cases—the potential for exit manipulation increases. Highly concentrated ownership paired with dynamic whitelist or sell tax control allows a small group of insiders to exert disproportionate influence over liquidity and price dynamics, including the ability to initiate sudden sell-offs or block exits for other holders selectively. Conversely, a wide and distributed holder base with transparent and immutable contract permissions typically reduces the risk of such manipulations, as the coordination required to enforce exit restrictions becomes more complex and less feasible.

Liquidity pool (LP) lock status further informs the risk assessment. Pools with shallow depths—under $50,000 in some contexts—relative to market cap or trading volume are more susceptible to price manipulation and sudden liquidity withdrawal, especially if the LP tokens are not time-locked or are controlled by a single entity. When combined with dynamic contract permissions, these conditions create a precarious environment where an owner might simultaneously restrict sells through contract logic and remove liquidity via LP tokens, constituting classic rug pull mechanics. However, the presence of locked LP tokens or multisignature governance over liquidity reduces this risk by limiting unilateral control.

Taken together, these patterns—honeypot mechanics, adjustable sell taxes, mint and freeze authorities, upgradeable proxies, holder concentration, and LP lock status—form a complex risk matrix that can sometimes reveal structural vulnerabilities prone to exit traps or rug pulls. Each pattern alone does not necessarily confirm malicious intent or guarantee a rug pull, but the combination of multiple factors, especially when opaque or owner-controlled, significantly raises the likelihood of adverse outcomes for token holders. A deep and nuanced analysis of contract code, permissions, and on-chain data is essential to discern between benign operational features and potential exit liquidity traps embedded within token contracts.

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 →