Generate cryptographic random strings
Uses Web Crypto for true randomness. Mix character sets, exclude lookalikes, batch up to 100 at once.
abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789
How to generate random strings
Uses crypto.getRandomValues() — the same source used for keys and tokens. Output is unpredictable and uniform.
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Pick length
1-1024 chars. 16 is plenty for passwords; 32+ for tokens.
Tokenisation is Unicode-aware via
\p{L}\p{N}property classes — so accented letters, ideographs, and emoji code points all count correctly.lengthUTF-8Unicodecode pointslivelen · text16 · UTF-816 chars
loaded · UTF-8UTF-8 · ready - 02
Pick charsets
Mix a-z, A-Z, 0-9, symbols. More charsets = more entropy per char.
Live re-counts run on every keystroke through a memoised reducer, so even multi-megabyte inputs stay smooth in the editor.
alphalivememoisedoptionssnappysets · options62 · livea-z + A-Z + 0-9
options applied · livelive - 03
Exclude lookalikes
Common excludes: 0/O/I/l/1. Useful for human-readable codes.
Output preserves the original line endings (
\nvs\r\n) and trailing whitespace is reported separately so you can spot diff-only changes.filterline endingswhitespacediff-cleanreproducibleblock · counted0OIl · readyno 0OIl
counted · livecounted - 04
Generate batch
Up to 100 strings at once. Click Copy on any row or Copy all for newline-joined.
Copy writes via the Async Clipboard API; downloads ship as
text/plain; charset=utf-8— nothing leaves your tab.batchclipboardtext/plainblobclient-side✓ · copiedready · done✓ 5 strings
shipped · ready to shipsuccess
Text-processing fundamentals worth knowing
Tokenise with Unicode classes
Use \p{L}\p{N} with the u flag so accents, ideographs, and emoji count properly.
Normalise line endings
Convert \r\n to \n before diffing or hashing — Windows-vs-Unix endings produce phantom changes.
Mind invisible characters
Zero-width joiners, BOMs, and non-breaking spaces look identical to ASCII space. Strip them before comparison or storage.
Stream don’t slurp
For multi-megabyte text, iterate line-by-line rather than loading everything to memory — keeps the tab responsive.
Choose collation deliberately
Default JS sort is code-point order, not human alphabetical. Use Intl.Collator for locale-aware sorting.
Re-run after normalisation
NFC vs NFD changes byte length but not visible glyphs. String.prototype.normalize() before counts and comparisons.
When to generate random strings
Tokens, IDs, fixtures.
API tokens
Stub auth headers or webhook secrets. Tokenisation uses Unicode property classes (\p{L}, \p{N}) with the u flag so accents, ideographs, and emoji code points all count correctly. Surrogate-pair-aware counts mean 🚀 weighs 1, not 2.
Unicode-correctTest fixtures
Seed databases with realistic identifiers. Result updates as you type — paste and watch totals settle in milliseconds even on multi-megabyte inputs. Heavy work runs through a memoised reducer so the editor never janks.
diff-cleanPromo codes
Batch generate unique codes for campaigns. Output normalises line endings to LF for clean diffs across platforms. Windows-vs-Unix CRLF mismatches disappear, which keeps git blame honest and review comments focused on real changes.
instant countsSlug suffixes
Disambiguate filenames or short URLs. Code-point counts are stable across NFC/NFD normalisation. Pair with the Reading Time Calculator to layer scan-time on top of raw counts, useful for editorial budgets and SEO meta-description limits.
platform-awareTokens & nonces
CSRF tokens, session IDs, salts. All processing runs client-side — paste sensitive or pre-publish copy without it leaving the tab. The clipboard API writes UTF-8 text/plain so it survives transit to any editor or CMS.
code-point-accurateGame seeds
Repeatable random seeds for procedural games. Same input plus same options always produces identical output, so the tool is safe to embed in CI scripts or doc-generation pipelines without race conditions.
losslessFrequently asked questions
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