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

  • 3598

    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 3501-3550 of 3598 ranked incidents

Largest Web3 incidents by USD amount lost
Rank Project Amount Lost Date Chain Technique Attack Guide Source
3501 LamboPUMP — binance Honeypot — View →
3502 CURLYPUFF — binance Honeypot — View →
3503 SonicSwap — binance Honeypot — View →
3504 NFT Farm — binance Honeypot — View →
3505 E=MCv2 — binance Honeypot — View →
3506 Symbol — binance Honeypot — View →
3507 Milkyway — binance Honeypot — View →
3508 RFI Protocol — binance Honeypot — View →
3509 Beagle — binance Honeypot — View →
3510 ONYX — binance Honeypot — View →
3511 Unstoppable — binance Honeypot — View →
3512 ShareDeFi Protocol — binance Honeypot — —
3513 Shyft Network — ethereum Honeypot — View →
3514 Dafi Protocol — ethereum Honeypot — View →
3515 Lepricon — ethereum Honeypot — View →
3516 MHP88 — binance Honeypot — View →
3517 PancakeSwap / Cream Finance — bsc, ethereum DNS Hijack — —
3518 Cream Finance — - Other — View →
3519 Crocoswap finance — binance Other — View →
3520 SUPPLYSWAP — binance Honeypot — View →
3521 PegasusCoin — binance Honeypot — View →
3522 BSCView — binance Honeypot — View →
3523 Chef Swap — binance Other — View →
3524 OgreSwap — binance Other — View →
3525 ApeShiba — binance Honeypot — View →
3526 Zombie Swap — binance Honeypot — View →
3527 PabloEscobarFi — binance Other — View →
3528 BenzSwap — binance Honeypot — View →
3529 Chad Token — binance Honeypot — —
3530 VikingSwap — binance Abandoned — View →
3531 AK47 — binance Honeypot — View →
3532 Alchemist — binance Honeypot — View →
3533 Kylin Network — ethereum Honeypot — View →
3534 Slime.Finance — binance Honeypot — View →
3535 PepeSocks — binance Honeypot — View →
3536 OxSocks — binance Honeypot — View →
3537 RobotSwap — binance Honeypot — View →
3538 WizzardSwap — binance Honeypot — View →
3539 Berry Swap — binance Honeypot — View →
3540 DoggySwap — binance Honeypot — View →
3541 SteadyGainz — binance Honeypot — View →
3542 Bee-Swap.org — binance Honeypot — View →
3543 SilentSwap.Finance — binance Honeypot — View →
3544 ZELDASWAP — binance Honeypot — View →
3545 Raydium Protocol — binance Honeypot — View →
3546 CaliSwap — binance Honeypot — View →
3547 PROJECTX — binance Honeypot — View →
3548 BubbleSwap — binance Honeypot — View →
3549 JumanjiSwap — binance Honeypot — View →
3550 SexySwap — 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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