If you take one thing from this article: Your GPU and your timeline will thank you.
The keyword rockyou2024txt better has since gained traction. Security researchers, penetration testers, and red teamers aren’t asking "Is RockYou2024 good?"—they’re asking "What makes a better version?" rockyou2024txt better
| Wordlist | Size (lines) | Cracks within 1 hour (8x RTX 4090) | Coverage | |----------|--------------|--------------------------------------|-----------| | RockYou2024 (raw) | 9.4B | 12,847 | 25.7% | | RockYou2024 (deduped, freq>2) | 380M | 18,231 | 36.5% | | (base + rules + context) | 412M (guesses) | 26,794 | 53.6% | If you take one thing from this article:
| Pillar | RockYou2024 | Better Alternative | |--------|-------------|--------------------| | | 9.4B entries, 80% waste | 50–200M high-probability entries | | Real-world frequency | No frequency data | Ranked by breach occurrence | | Ruleset readiness | Plaintext only | Paired with mutation rules (Best64, OneRuleToRuleThemAll) | | Freshness | Stops at 2023 leaks | Includes 2024+ breaches (e.g., Microsoft, Snowflake) | | Targeting capability | General purpose | Industry- or country-specific variants | This instantly cuts RockYou2024 from billions to <500
| Tool | Purpose | Command Example | |------|---------|------------------| | pw-sleeper | Remove passwords with low frequency | pwsleeper rockyou2024.txt --min-freq 3 | | duplicut | Ultra-fast deduplication w/ memory limits | duplicut rockyou2024.txt -o clean.txt | | hashcat --stdout + rp | Apply rules and rank by probability | hashcat -r best64.rule rockyou_base.txt --stdout \| rp --max=50M | | pass-station | Convert to probabilistic sorted order | passstation rockyou2024.txt --sort-by pwned-count | We tested three variations against a real-world sample of 50,000 NTLM hashes from an authorized internal audit:
Keep only passwords that appear in (using a reference like haveibeenpwned v3 API or Pwned Passwords downloadable hashes). This instantly cuts RockYou2024 from billions to <500 million lines.
For advanced practitioners, the next horizon isn’t larger wordlists—it’s using (like small GPTs trained on password corpuses) to produce never-before-seen candidates that follow human biases. But that is a topic for another deep dive.