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The COCOON to USD chart shows how the price changes over time.Get this data with DYOR TON API
Cocoon Price Converter
USD
COCOON
1.05K
Cocoon Markets
Cocoon Locks
Unlocked 100%
Locked 0%
324,716
0
All-time locked
324,716
Locked now
0
Total Holders
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# | Address | Balance (COCOON) | Value (USD) | Percentage |
|---|---|---|---|---|
Token check
- Risks
- 2
- Cautions
- 1
- Fine
- 5
- No data
- 0
- Trust Score15 of 100: low.Risk
- ContractA modified contract DYOR hasn't verified: its code may limit selling or take fees.Risk
- DYOR verificationNot verified. Most tokens aren't: a reason to look closer, not proof of anything.Caution
- Look-alike
- Holder concentration
5 fine
Signals come from DYOR's data at fixed thresholds and can miss what a contract hides. They are not financial advice: do your own research.
About Cocoon
- Cocoon (COCOON) is a jetton, a token on the TON blockchain, and its contract address is EQBiyZMUXvdnRYFUk3_R5uPdsR2ROI9mes_1S-jL1tIQDhDK, ending in DhDK. A name or ticker alone does not identify a jetton on TON, so the address is the way to tell which Cocoon you are dealing with. Before a swap or transfer, compare the full address character by character with the one shown in your wallet or in the DEX pool. Matching only the last four characters is not enough.
- In the project's own description, Cocoon is a memecoin that grew out of Pavel Durov's AI vision. The project says it is backed by a community that believes in TON and supports Pavel Durov in the fight for freedom and decentralization. It also notes that the token was deployed from sTONks. By the project's account, then, COCOON is a community memecoin with an AI theme in its origin story.
- DYOR.io lists Cocoon as a jetton on TON and shows its on-chain data, but it does not vouch for the project, and Cocoon does not carry the Verified Token badge. The descriptions of Cocoon here are the project's own account. To help readers weigh the token, DYOR.io gives it a Trust Score: its rating of a token from 0 to 100, calculated from more than 100 on-chain and off-chain parameters with machine learning.
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