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 2801-2850 of 3597 ranked incidents

Largest Web3 incidents by USD amount lost
Rank Project Amount Lost Date Chain Technique Attack Guide Source
2801 TeslaModelS Plaid — binance Honeypot — View →
2802 SupHerbs — binance Honeypot — View →
2803 ShinyShiba — binance Honeypot — View →
2804 BRONZE Token — binance Honeypot — View →
2805 Shuby Inu — ethereum Honeypot — View →
2806 MoonGiraffe — binance Honeypot — View →
2807 MAMASHIBA — ethereum Honeypot — View →
2808 Smells Like Updoge — ethereum Honeypot — View →
2809 Rocket Doge — binance Honeypot — View →
2810 SafeMEME — binance Honeypot — View →
2811 LION — binance Honeypot — View →
2812 ELEPHANT — binance Honeypot — View →
2813 Polkally — binance Honeypot — View →
2814 IDEA Token — binance Honeypot — View →
2815 DipBitcoin — binance Honeypot — View →
2816 $FUCKELON — binance Honeypot — View →
2817 Chubby Akita — binance Honeypot — View →
2818 GoatCoin — binance Honeypot — View →
2819 MoonFly — binance Honeypot — View →
2820 SHIBA PLATINUM — binance Honeypot — View →
2821 KreamPie — binance Honeypot — View →
2822 MoonChain — binance Honeypot — View →
2823 TIGER — binance Honeypot — View →
2824 ElonCash — binance Honeypot — View →
2825 PirateElon — binance Honeypot — View →
2826 PANKY TOKEN — binance Honeypot — View →
2827 KodaRobotDog Token — binance Honeypot — View →
2828 YieldShiba.com — binance Honeypot — View →
2829 SAFEPUP TOKEN — binance Honeypot — View →
2830 MoonAkita Inu — binance Honeypot — View →
2831 MaxGoatToken — binance Honeypot — View →
2832 LuckyDoge — binance Honeypot — View →
2833 WhereLambo — binance Honeypot — View →
2834 NEPTUNE Token — binance Honeypot — View →
2835 WOODEN Token — binance Honeypot — View →
2836 GEMROCKET — binance Honeypot — View →
2837 HuskyMoon — binance Honeypot — View →
2838 Eloge Inu — ethereum Honeypot — View →
2839 MoonDegenerates — binance Honeypot — View →
2840 ShibaBTC — binance Honeypot — View →
2841 ARGOAPP — binance Honeypot — View →
2842 KISHUSWAP — ethereum Honeypot — View →
2843 Maxxi Protocol — binance Honeypot — View →
2844 SAFEMOONSWAP — ethereum Honeypot — View →
2845 MulletCoinClub — binance Honeypot — View →
2846 JAGUAR — binance Honeypot — View →
2847 SHIBACOIN — ethereum Honeypot — View →
2848 T-Rex — binance Honeypot — View →
2849 KNIGHT TOKEN — binance Honeypot — View →
2850 AERION — binance 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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