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 3351-3400 of 3597 ranked incidents

Largest Web3 incidents by USD amount lost
Rank Project Amount Lost Date Chain Technique Attack Guide Source
3351 Totoro — binance Honeypot — View →
3352 HiBNB — binance Honeypot — View →
3353 CUATROtoken — binance Honeypot — View →
3354 Xcademy Token — ethereum Honeypot — View →
3355 y.at — ethereum Honeypot — View →
3356 SafeCatch — binance Honeypot — View →
3357 SafeStarship — binance Honeypot — View →
3358 rock solid Vaults — binance Honeypot — View →
3359 ElonFrog — binance Honeypot — View →
3360 SafeAurora — binance Honeypot — View →
3361 Kattana Trade — ethereum Honeypot — View →
3362 epns.io — ethereum Honeypot — View →
3363 Lazy.com — ethereum Honeypot — View →
3364 TubbyCoin — ethereum Honeypot — View →
3365 RAZE Network — ethereum Honeypot — View →
3366 CoreSwap.finance — ethereum Honeypot — View →
3367 GoalTimeN Finance — ethereum Honeypot — View →
3368 SafeNaruto Token — binance Honeypot — View →
3369 Cook Token — ethereum Honeypot — View →
3370 MoonX2 — binance Honeypot — View →
3371 KingSwap — binance Honeypot — View →
3372 Fei Tribe — ethereum Honeypot — View →
3373 HOPE — ethereum Honeypot — View →
3374 Instantly — binance Honeypot — View →
3375 TOKO TOKEN — binance Honeypot — View →
3376 nebula — binance Honeypot — View →
3377 Ultrasafe — binance Honeypot — View →
3378 Halleys Comet — binance Honeypot — View →
3379 Unmarshal.io — ethereum Honeypot — View →
3380 Ramifi.org — ethereum Honeypot — View →
3381 Forcedao.com — ethereum Honeypot — View →
3382 FORCE — ethereum Honeypot — View →
3383 gorillapump.net — binance Honeypot — View →
3384 ElonHODL Token — binance Honeypot — View →
3385 SafeForever — binance Honeypot — View →
3386 SafeRedux — binance Honeypot — View →
3387 Coinlix — binance Honeypot — View →
3388 safe-x.space — ethereum Honeypot — View →
3389 KINGLER — binance Honeypot — View →
3390 ZirgonYield — binance Honeypot — View →
3391 WhiteX Finance — binance Honeypot — View →
3392 COPE — ethereum Honeypot — View →
3393 NEOBUX — binance Honeypot — View →
3394 MoonFEG Token — binance Honeypot — View →
3395 KURMA — binance Honeypot — View →
3396 GamyFi — ethereum Honeypot — View →
3397 ElonSafu — binance Honeypot — View →
3398 Luxury Finance — binance Honeypot — View →
3399 saferipple — binance Honeypot — View →
3400 VanillaUnicorn — 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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