Web3 Hacks & DeFi Exploit Intelligence

Security trends
  • $91B+Lost
  • 3597Incidents
  • 141Chains
  • 19Classes
# Project Date Amount Lost Chain Technique Links
1771 MetaMoonMars $866 — Other
1772 MonoX $31.4M ethereum, polygon Swap Function Exploit / Swap Logic Flaw
1773 Coinsuper — — Other
1774 Lever $653K bsc Borrow Logic Flaw
1775 Visor Finance $976K ethereum Flash Loan Attack / Spot Price Manipulation
1776 Sloth Inu $8K — Rugpull
1777 ElectronDAO $729K — Rugpull
1778 SnowdogDAO $30.0M avalanche Rugpull / Drained Contracts / Liquidity Rug
1779 SkyDog — binance Honeypot
1780 dYdX $211K — Other
1781 Ploutoz Finance $372K bsc Flash Loan Attack / Spot Price Manipulation
1782 Unlock Protocol $416K — Access Control
1783 Formation.Fi $100K — Other
1784 Zenon Network $1.2M — Other
1785 UFCT $1.3M — Rugpull
1786 Phantom Galaxies $1.1M ethereum Malware
1787 Meta Pets $709K — Rugpull
1788 ShibaElonMars — binance Honeypot
1789 Nerve Finance $586K bsc Swap Logic Flaw
1790 Blizzard $1.1M — Other
1791 ChainSwap $4.4M bsc, ethereum Exploit Weak Authentication Check / Caller Impersonation
1792 bZx $47.6M bsc, polygon Access Control / Private Key Compromised (Phishing) / Phishing
1793 Vesper Finance $3.4M ethereum Oracle Manipulation / Spot Price Manipulation
1794 Squid Game $5.7M bsc Rugpull / Drained Liquidity Pool / Liquidity Rug
1795 Boy X Highspeed $139M bsc Suspected administrative-key leakage
1796 AutoShark $580K bsc Reward Logic Flaw
1797 AutoSharkFinance $2.0M — Other
1798 AnubisDAO $60.0M ethereum Drained Contracts / Rugpull / Admin Drain
1799 Cream Finance $130M ethereum Flash Loan Attack / Flashloan Price Oracle Attack / Spot Price Manipulation
1800 Alpha Finance Lab $171K ethereum Spot Price Manipulation

Data sourced from DefiLlama & SunWeb3Sec/DeFiHackLabs . Thank you for keeping Web3 security data open.

Understanding Smart Contract Vulnerabilities

Explore the technical causes behind reentrancy, flash loan attacks, and oracle manipulation in our attack guides.

Learn how these hacks actually worked

Study the exploit patterns behind the incidents in this database, then practice finding them before attackers do.