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 3401-3450 of 3598 ranked incidents

Largest Web3 incidents by USD amount lost
Rank Project Amount Lost Date Chain Technique Attack Guide Source
3401 VanillaUnicorn — binance Honeypot — View →
3402 ElonGain 1000X — binance Honeypot — View →
3403 StringFinance.io — binance Honeypot — View →
3404 EXPER — binance Honeypot — View →
3405 HAHAHA GO SAFE TOKENS — binance Honeypot — View →
3406 SafeCeti — binance Honeypot — View →
3407 SmartRush — binance Honeypot — View →
3408 POOL SIDE DAO — binance Honeypot — View →
3409 SPEEDDAO — binance Honeypot — View →
3410 UBERMOON — binance Honeypot — View →
3411 MoonWalkers — binance Honeypot — View →
3412 MoonBois — binance Honeypot — View →
3413 yTrio — binance Honeypot — View →
3414 SAFEWAVE — binance Honeypot — View →
3415 Rocket Farm — binance Honeypot — View →
3416 SilentFarm — binance Honeypot — View →
3417 Casper Network — ethereum Honeypot — View →
3418 CrossASR — binance Honeypot — View →
3419 CoilSwap — binance Honeypot — View →
3420 ELONCAKE — binance Honeypot — View →
3421 SafeSuperHeavy — binance Honeypot — View →
3422 Rage.Fan — ethereum Honeypot — View →
3423 SAFEMYANMAR — binance Honeypot — View →
3424 Polkalokr — ethereum Honeypot — View →
3425 Fei protocol — ethereum Honeypot — View →
3426 SHOPEEPAY — binance Honeypot — View →
3427 REAPit — binance Honeypot — View →
3428 TAKE OF ELON — binance Honeypot — View →
3429 Zona Indonesia — binance Honeypot — View →
3430 StudToken — binance Honeypot — View →
3431 KINGOFREFLECT — binance Honeypot — View →
3432 ElonTrade 100x — binance Honeypot — View →
3433 LIGHT LUNAR PROTOCOL — binance Honeypot — View →
3434 MoonExpress — binance Honeypot — View →
3435 SafeFLM — binance Honeypot — View →
3436 SpeedMOON — binance Honeypot — View →
3437 ELONFLY — binance Honeypot — View →
3438 One SG — binance Honeypot — View →
3439 SolaceToken — binance Honeypot — View →
3440 SafeTeslaCoil — binance Honeypot — View →
3441 QuickMOON — binance Honeypot — View →
3442 ElonFunds — binance Honeypot — View →
3443 SlothFinance — binance Honeypot — View →
3444 Nuclear Product — binance Honeypot — View →
3445 Tribe — ethereum Honeypot — View →
3446 DINAR PROTOCOL — binance Honeypot — View →
3447 ELONMARS — binance Honeypot — View →
3448 SafePlay Token — binance Honeypot — View →
3449 Solstarter — ethereum Honeypot — View →
3450 SafeQuasiStar — 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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