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

Jump to full leaderboard
  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 3301-3350 of 3597 ranked incidents

Largest Web3 incidents by USD amount lost
Rank Project Amount Lost Date Chain Technique Attack Guide Source
3301 Supernova — binance Honeypot — View →
3302 Alpha Andromedae — binance Honeypot — View →
3303 Dark.Build — binance Honeypot — View →
3304 Genix.finance — binance Honeypot — View →
3305 MoonPlan — binance Honeypot — View →
3306 AVG1000X — binance Honeypot — View →
3307 APEMARS Token — binance Honeypot — View →
3308 Voltage — binance Honeypot — View →
3309 Setting Sun — binance Honeypot — View →
3310 FairPluto — binance Honeypot — View →
3311 Quagmire — binance Honeypot — View →
3312 JUSTMOON — binance Honeypot — View →
3313 Safe Planet 9 — binance Honeypot — View →
3314 BaTorrent — binance Honeypot — View →
3315 Safe Jail — binance Honeypot — View →
3316 FairVenus — binance Honeypot — View →
3317 Hurricane — binance Honeypot — View →
3318 Avengers NFT — ethereum Honeypot — View →
3319 Safe Fortune — binance Honeypot — View →
3320 Shining Star — binance Honeypot — View →
3321 Duke Nukem — binance Honeypot — View →
3322 Fair Prison — binance Honeypot — View →
3323 rewardiqa — binance Honeypot — View →
3324 Aragorn — binance Honeypot — View →
3325 SafeWorld — binance Honeypot — View →
3326 SafeCompound — binance Honeypot — View →
3327 SafeWaifu — binance Honeypot — View →
3328 Cassiopeia — binance Honeypot — View →
3329 StrongCroac — binance Honeypot — View →
3330 FairRocket — binance Honeypot — View →
3331 Turtle In Space — binance Honeypot — View →
3332 FairSatoshi — binance Honeypot — View →
3333 Milky Way — binance Honeypot — View →
3334 SafeBinance — binance Honeypot — View →
3335 ElonProtocol — binance Honeypot — View →
3336 Constellation — binance Honeypot — View →
3337 SUNLIGHT PROTOCOL — binance Honeypot — View →
3338 Neutron Network — binance Honeypot — View →
3339 TigerSwap — ethereum Honeypot — View →
3340 Interstellar — binance Honeypot — View →
3341 SafeAtmosphere — binance Honeypot — View →
3342 Pulse — binance Honeypot — View →
3343 Findora — ethereum Honeypot — View →
3344 PotionBrew.net — binance Honeypot — View →
3345 Helios Project — binance Honeypot — View →
3346 Gains Associates — ethereum Honeypot — View →
3347 Orion — binance Honeypot — View →
3348 Palm.io — ethereum Honeypot — View →
3349 EXODUS — binance Honeypot — View →
3350 Bombic Finance — 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.

Learn to Prevent High-Impact Smart Contract Hacks

$91B+ lost to preventable vulnerabilities. Master real exploit patterns and defense techniques with hands-on Web3 security training.

Start Free Trial → View Full Course