Most Expensive Crypto Hacks Leaderboard

The biggest Web3 and DeFi exploits ranked by amount lost. Track high-impact incidents, study attack patterns, and learn how security failures scale into multi-million dollar losses.

  • $91B+

    Total Value Lost

  • 3597

    Incidents Tracked

  • 141

    Chains Affected

  • 65

    $100M+ Incidents

Top 10 Biggest Hacks

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  2. 🥈

    Mantra

    $5.50B

  4. #4

    LuBian

    $3.50B

    bitcoin

  7. #7

    Thodex

    $2.00B

  9. #9

    Finiko

    $1.50B

  10. #10

    Bybit

    $1.40B

    ethereum

Where the Largest Losses Concentrate

Top Chains by Losses

  • ethereum $9,830M
  • bitcoin $5,404M
  • bsc $3,037M
  • solana $1,697M
  • polygon $1,539M

Top Techniques by Losses

  • Other $52,517M
  • Rugpull $15,631M
  • Private Key Compromised (Brute Force) / Weak Key Generation $3,500M
  • Safe Multisig wallet Phishing Exploit / Access Control / Signer Phishing $1,635M
  • Access Control / Hot Wallet Key Compromised $1,027M

Full Leaderboard

Showing 3101-3150 of 3597 ranked incidents

Largest Web3 incidents by USD amount lost
Rank Project Amount Lost Date Chain Technique Attack Guide Source
3101 Ares Protocol — ethereum Honeypot — View →
3102 Moon Rat Token — binance Honeypot — View →
3103 BullsDrop — binance Honeypot — View →
3104 Pudgy Token — binance Honeypot — View →
3105 Floyd Crypto Mayweather — ethereum Honeypot — View →
3106 Lion King Token — ethereum Honeypot — View →
3107 SATANS PLAYHOUSE — binance Honeypot — View →
3108 SAFEGUARD — binance Honeypot — View →
3109 Big Chungus — ethereum Honeypot — View →
3110 InfinityDoge — binance Honeypot — View →
3111 Aichi Inu — binance Honeypot — View →
3112 Elon SpaceEX — ethereum Honeypot — View →
3113 Time Dilation — binance Honeypot — View →
3114 1MILNFT — ethereum Honeypot — View →
3115 German Shepherd — ethereum Honeypot — View →
3116 UnoRe — ethereum Honeypot — View →
3117 Monkey Island — ethereum Honeypot — View →
3118 Safe Sex — ethereum Honeypot — View →
3119 Atmosphere — binance Honeypot — View →
3120 Golden Retriever — ethereum Honeypot — View →
3121 SafePOODLE — binance Honeypot — View →
3122 Shibazilla — ethereum Honeypot — View →
3123 Jigstack.org — ethereum Honeypot — View →
3124 MoonDog — binance Honeypot — View →
3125 MEGAMOON — binance Honeypot — View →
3126 TokenFomo.pro — binance Honeypot — View →
3127 Private Token Offering — binance Honeypot — View →
3128 MoonSafebank — binance Honeypot — View →
3129 DogeDAO — binance Honeypot — View →
3130 moonpirate — binance Honeypot — View →
3131 Refinable — ethereum Honeypot — View →
3132 Quantum Tunneling — binance Honeypot — View →
3133 MoonWhale — binance Honeypot — View →
3134 Fish Tank — ethereum Honeypot — View →
3135 Gecko Token — ethereum Honeypot — View →
3136 Gorillaz Sunshine — ethereum Honeypot — View →
3137 Ergosphere — binance Honeypot — View →
3138 JiX Swap — ethereum Honeypot — View →
3139 Yuki Inu Token — ethereum Honeypot — View →
3140 Chicken Soup Protocol — ethereum Honeypot — View →
3141 RocketDoge — binance Honeypot — View →
3142 WARONRUGS — binance Honeypot — View →
3143 ROCKETMARS — binance Honeypot — View →
3144 SAFESHITCOIN — binance Honeypot — View →
3145 JUMPFROG — binance Honeypot — View →
3146 Kitten.finance — ethereum Honeypot — View →
3147 Digital Reserve Currency — ethereum Honeypot — View →
3148 ULTRADOGE — ethereum Honeypot — View →
3149 Quark — binance Honeypot — View →
3150 Treasure Box — ethereum Honeypot — View →

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

Understanding the Pattern Behind Billion-Dollar Losses

The most expensive crypto hacks are not random. They cluster around repeating vulnerability patterns: access-control failures, flash-loan manipulation, oracle abuse, and unsafe external calls. Studying large-loss incidents helps security researchers prioritize high-impact threat models first.

For deeper context, explore the full Web3 Hacks Dashboard and our Smart Contract Attack Library for hands-on exploit and mitigation breakdowns.

Frequently Asked Questions

How is this leaderboard ranked?

Incidents are ranked by parsed USD amount lost in descending order. Records without parseable loss values are excluded from this ranking.

Does this include every attack type?

It includes all incidents with known loss values in the database. Use the full dashboard for broader filtering and lower-severity incidents.

How can I learn to prevent these exploits?

Study attack-class pages first, then practice in guided exercises inside the Smart Contract Hacking course.

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