Rug pulls dey lead crypto scam (54%): AI phishing dey fuel new threats
On-chain security firm Web3 Antivirus talk say rug pulls dey make over 54% of newly detected crypto scams. For one breakdown for X on June 9, honeypots dey second (~22%), then fake tokens (~12%) and scam airdrops (just under ~12%).
Rug pulls dey work because contracts first dey look normal, prices and activity dey rise. The risk show when hidden permissions make creators fit block sales, comot liquidity, or lock funds—then chart suddenly collapse after the pump. Web3 Antivirus still flag say AI-driven delivery dey make phishing emails, fake support chats, and scam social posts harder to spot. Email na the most common channel (53%), then SMS (10%), social (9%), and online ads (8%).
Total detections for Scam Pulse include 425,000+ rug pulls, 172,000 honeypots, and 94,000+ scam airdrops. From 100M+ contracts analyzed, near 4M get flagged as scams (3.1M for the last 30 days). Impersonation dey rise too, with Ethereum leading fake token detections, followed by Tether and USDC.
Examples dem mention include fake Uniswap site wey drain at least $400,000 and warnings about fake XRP giveaways. For traders, rug pulls remain the main threat, dey increase short-term volatility round new listings and dey strengthen the case for stricter contract and off-chain verification.
Bearish
Di dat show say rug pulls na di main scam waka (54%+), an e point out mechanics we fit trap liquidity an block exit wit hidden contract permissions. Dis dey usually raise how people dey see counterparty risk, we fit reduce speculative appetite an make people dey more careful—specially wɛn new token dem dey launch.
Short term, traders fit see more volatility during “pump” phases as bots an attackers go front‑run di attention, den when dem remove liquidity e go trigger sharp downside moves. Di fake Uniswap drain an fake XRP giveaway risks dem talk about resemble past waves weh phishing an impersonation incidents cause sudden fall in sentiment an quicker risk‑off positioning.
Long term, repeated contract‑level threats plus AI‑enhanced phishing fit make exchanges an wallets tighten verification (contract allowlists, phishing detection, user education). Dis fit bad for demand of unvetted tokens, but e fit eventually improve market hygiene. Net impact na bearish: higher scam frequency dey reduce trust an participation until mitigations catch up.