$Avishkar Liquidity Drain on Solana May Signal Risks of Hype-Driven Meme Coins

The Avishkar token experienced a rug pull on Solana after roughly $50,000 was drained from liquidity pools, triggering a rapid price collapse and near-zero trading ￰0￱ Avishkar token collapse underscores the risks of hype-driven meme coins and is unlikely to recover without substantial new liquidity. $50,000 liquidity drain triggered a rapid collapse of the Avishkar ￰1￱ on Solana in late September, the meme coin surged on promotion but lacked on-chain ￰2￱ trading volume and centralized liquidity make recovery unlikely without fresh capital ￰3￱ token rug pull: $50,000 drained on Solana, price collapse near $0.88 — learn the warning signs and protect your ￰4￱ now. $Avishkar, a Solana-based memecoin promoted by activist Avishkar Raut, collapsed after a roughly $50,000 liquidity ￰5￱ incident highlights how hype-driven tokens can turn into rug pulls and leave retail investors with near-worthless ￰6￱ Avishkar token, launched on the Solana blockchain in late September, lost approximately $50,000 from its liquidity pools in a sudden drain that precipitated a steep price ￰7￱ media chatter and on-chain trackers documented the outflow, leaving early buyers with sharply devalued tokens and minimal trading ￰8￱ is the Avishkar token rug pull?

The Avishkar token rug pull refers to a rapid liquidity drain on the Solana-based $Avishkar token that removed about $50,000 from its pools, causing a swift collapse in price and trading ￰9￱ event illustrates how memecoins promoted via social channels can lack core protections and fail ￰10￱ did the liquidity drain occur and what were the immediate effects? On launch, the token experienced a sharp price spike tied to social ￰11￱ hours, liquidity was withdrawn and the token’s price ￰12￱ on-chain figures indicate ~ $50,000 removed from liquidity pools, leaving a token price near $0.875 with negligible ￰13￱ are meme coins like Avishkar vulnerable on Solana?

Memecoins often rely on social momentum, not ￰14￱ Solana, fast token launches and low initial liquidity enable pump-and-dump ￰15￱ vesting, audited contracts, or decentralized liquidity locks, these tokens remain exposed to instant ￰16￱ Pre-collapse Post-collapse Estimated liquidity drained $50,000 (initial pool) $0 (drained) Reported token price Surged at launch ≈ $0.875 Trading volume High at launch Very low How can investors spot rug pull risks before buying memecoins? Look for objective, on-chain signals rather than ￰17￱ checks include liquidity lock status, audit reports, token ownership concentration, and vesting ￰18￱ crucial safeguards are missing, treat the token as high ￰19￱ liquidity locks and smart contract ￰20￱ token holder distribution for ￰21￱ vesting schedules and developer token ￰22￱ on-chain activity and early withdraw patterns. , "description": "Avishkar token lost roughly $50,000 in a liquidity drain on Solana, causing a rapid ￰23￱ incident underscores rug pull risks in hype-driven meme coins.", , Frequently Asked Questions How much liquidity was drained from the Avishkar pools?

On-chain reports estimate about $50,000 was withdrawn from Avishkar liquidity pools, which removed market-making depth and triggered a sharp price ￰24￱ promoted the Avishkar token and does that affect liability? The token was promoted by activist Avishkar Raut, a young social-media ￰25￱ by public personalities can increase visibility but does not guarantee project safeguards or legal protections for ￰26￱ Takeaways Liquidity drain: ~ $50,000 removed, causing the ￰27￱ coin risk: Hype-driven tokens on Solana can be fragile without locks or ￰28￱ action: Prioritize on-chain checks, avoid tokens lacking transparency, and educate younger investors about ￰29￱ The Avishkar token rug pull on Solana is a stark reminder that memecoins propelled by social hype can collapse quickly when liquidity is centralized or ￰30￱ should perform basic on-chain due diligence—checking liquidity locks, audits, and token distribution—to reduce exposure to similar rug ￰31￱ will continue to track related developments and on-chain data.