1#![deny(non_upper_case_globals)]
22#![deny(non_camel_case_types)]
23#![deny(non_snake_case)]
24#![deny(unused_mut)]
25#![deny(dead_code)]
26#![deny(unused_imports)]
27#![deny(missing_docs)]
28#![cfg_attr(all(not(test), not(feature = "std")), no_std)]
29
30#[cfg(any(test, feature = "std"))]
31pub extern crate core;
32
33extern crate bitcoin_hashes;
34extern crate rand_core;
35
36#[cfg(feature = "std")]
37extern crate unicode_normalization;
38
39#[cfg(feature = "rand")]
40extern crate rand;
41#[cfg(feature = "serde")]
42pub extern crate serde;
43
44use core::{fmt, str};
45
46#[cfg(feature = "std")]
47use std::borrow::Cow;
48#[cfg(feature = "std")]
49use std::error;
50
51use bitcoin_hashes::{sha256, Hash};
52
53#[cfg(feature = "std")]
54use unicode_normalization::UnicodeNormalization;
55
56#[macro_use]
57mod internal_macros;
58mod language;
59mod pbkdf2;
60
61pub use language::Language;
62
63#[allow(unused)]
65const MIN_NB_WORDS: usize = 12;
66
67const MAX_NB_WORDS: usize = 24;
69
70const EOF: u16 = u16::max_value();
72
73#[derive(Debug, Clone, PartialEq, Eq, Copy)]
76pub struct AmbiguousLanguages([bool; language::MAX_NB_LANGUAGES]);
77
78impl AmbiguousLanguages {
79 pub fn as_bools(&self) -> &[bool; language::MAX_NB_LANGUAGES] {
82 &self.0
83 }
84
85 pub fn iter(&self) -> impl Iterator<Item = Language> + '_ {
87 Language::all().iter().enumerate().filter(move |(i, _)| self.0[*i]).map(|(_, l)| *l)
88 }
89
90 #[cfg(feature = "std")]
92 pub fn to_vec(&self) -> Vec<Language> {
93 self.iter().collect()
94 }
95}
96
97#[derive(Debug, Clone, PartialEq, Eq, Copy)]
99pub enum Error {
100 BadWordCount(usize),
102 UnknownWord(usize),
106 BadEntropyBitCount(usize),
108 InvalidChecksum,
110 AmbiguousLanguages(AmbiguousLanguages),
114}
115
116impl fmt::Display for Error {
117 fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
118 match *self {
119 Error::BadWordCount(c) => {
120 write!(f, "mnemonic has a word count that is not a multiple of 6: {}", c,)
121 }
122 Error::UnknownWord(i) => write!(f, "mnemonic contains an unknown word (word {})", i,),
123 Error::BadEntropyBitCount(c) => write!(
124 f,
125 "entropy was not between 128-256 bits or not a multiple of 32 bits: {} bits",
126 c,
127 ),
128 Error::InvalidChecksum => write!(f, "the mnemonic has an invalid checksum"),
129 Error::AmbiguousLanguages(a) => {
130 write!(f, "ambiguous word list: ")?;
131 for (i, lang) in a.iter().enumerate() {
132 if i == 0 {
133 write!(f, "{}", lang)?;
134 } else {
135 write!(f, ", {}", lang)?;
136 }
137 }
138 Ok(())
139 }
140 }
141 }
142}
143
144#[cfg(feature = "std")]
145impl error::Error for Error {}
146
147#[derive(Clone, Debug, Hash, PartialEq, Eq, PartialOrd, Ord)]
155pub struct Mnemonic {
156 lang: Language,
158 words: [u16; MAX_NB_WORDS],
161}
162
163serde_string_impl!(Mnemonic, "a BIP-39 Mnemonic Code");
164
165impl Mnemonic {
166 #[inline]
170 #[cfg(feature = "std")]
171 fn normalize_utf8_cow<'a>(cow: &mut Cow<'a, str>) {
172 let is_nfkd = unicode_normalization::is_nfkd_quick(cow.as_ref().chars());
173 if is_nfkd != unicode_normalization::IsNormalized::Yes {
174 *cow = Cow::Owned(cow.as_ref().nfkd().to_string());
175 }
176 }
177
178 pub fn from_entropy_in(language: Language, entropy: &[u8]) -> Result<Mnemonic, Error> {
181 const MAX_ENTROPY_BITS: usize = 256;
182 const MIN_ENTROPY_BITS: usize = 128;
183 const MAX_CHECKSUM_BITS: usize = 8;
184
185 let nb_bytes = entropy.len();
186 let nb_bits = nb_bytes * 8;
187
188 if nb_bits % 32 != 0 {
189 return Err(Error::BadEntropyBitCount(nb_bits));
190 }
191 if nb_bits < MIN_ENTROPY_BITS || nb_bits > MAX_ENTROPY_BITS {
192 return Err(Error::BadEntropyBitCount(nb_bits));
193 }
194
195 let check = sha256::Hash::hash(&entropy);
196 let mut bits = [false; MAX_ENTROPY_BITS + MAX_CHECKSUM_BITS];
197 for i in 0..nb_bytes {
198 for j in 0..8 {
199 bits[i * 8 + j] = (entropy[i] & (1 << (7 - j))) > 0;
200 }
201 }
202 for i in 0..nb_bytes / 4 {
203 bits[8 * nb_bytes + i] = (check[i / 8] & (1 << (7 - (i % 8)))) > 0;
204 }
205
206 let mut words = [EOF; MAX_NB_WORDS];
207 let nb_words = nb_bytes * 3 / 4;
208 for i in 0..nb_words {
209 let mut idx = 0;
210 for j in 0..11 {
211 if bits[i * 11 + j] {
212 idx += 1 << (10 - j);
213 }
214 }
215 words[i] = idx;
216 }
217
218 Ok(Mnemonic {
219 lang: language,
220 words: words,
221 })
222 }
223
224 pub fn from_entropy(entropy: &[u8]) -> Result<Mnemonic, Error> {
227 Mnemonic::from_entropy_in(Language::English, entropy)
228 }
229
230 pub fn generate_in_with<R>(
246 rng: &mut R,
247 language: Language,
248 word_count: usize,
249 ) -> Result<Mnemonic, Error>
250 where
251 R: rand_core::RngCore + rand_core::CryptoRng,
252 {
253 if word_count < MIN_NB_WORDS || word_count % 6 != 0 || word_count > MAX_NB_WORDS {
254 return Err(Error::BadWordCount(word_count));
255 }
256
257 let entropy_bytes = (word_count / 3) * 4;
258 let mut entropy = [0u8; (MAX_NB_WORDS / 3) * 4];
259 rand_core::RngCore::fill_bytes(rng, &mut entropy[0..entropy_bytes]);
260 Mnemonic::from_entropy_in(language, &entropy[0..entropy_bytes])
261 }
262
263 #[cfg(feature = "rand")]
276 pub fn generate_in(language: Language, word_count: usize) -> Result<Mnemonic, Error> {
277 Mnemonic::generate_in_with(&mut rand::thread_rng(), language, word_count)
278 }
279
280 #[cfg(feature = "rand")]
293 pub fn generate(word_count: usize) -> Result<Mnemonic, Error> {
294 Mnemonic::generate_in(Language::English, word_count)
295 }
296
297 pub fn language(&self) -> Language {
299 self.lang
300 }
301
302 pub fn word_iter(&self) -> impl Iterator<Item = &'static str> + Clone + '_ {
304 let list = self.lang.word_list();
305 self.words.iter().take_while(|w| **w != EOF).map(move |w| list[*w as usize])
306 }
307
308 fn language_of_iter<'a, W: Iterator<Item = &'a str>>(words: W) -> Result<Language, Error> {
311 let mut words = words.peekable();
312 let langs = Language::all();
313 {
314 let first_word = words.peek().ok_or(Error::BadWordCount(0))?;
316 if first_word.len() == 0 {
317 return Err(Error::BadWordCount(0));
318 }
319
320 for language in langs.iter().filter(|l| l.unique_words()) {
323 if language.find_word(first_word).is_some() {
324 return Ok(*language);
325 }
326 }
327 }
328
329 let mut possible = [false; language::MAX_NB_LANGUAGES];
333 for (i, lang) in langs.iter().enumerate() {
334 possible[i] = !lang.unique_words();
337 }
338 for (idx, word) in words.enumerate() {
339 for (i, lang) in langs.iter().enumerate() {
341 possible[i] &= lang.find_word(word).is_some();
342 }
343
344 let mut iter = possible.iter().zip(langs.iter()).filter(|(p, _)| **p).map(|(_, l)| l);
346
347 match iter.next() {
348 None => return Err(Error::UnknownWord(idx)),
350 Some(remaining) => {
352 if iter.next().is_none() {
353 return Ok(*remaining);
355 }
356 }
357 }
358 }
359
360 return Err(Error::AmbiguousLanguages(AmbiguousLanguages(possible)));
361 }
362
363 pub fn language_of<S: AsRef<str>>(mnemonic: S) -> Result<Language, Error> {
374 Mnemonic::language_of_iter(mnemonic.as_ref().split_whitespace())
375 }
376
377 pub fn parse_in_normalized(language: Language, s: &str) -> Result<Mnemonic, Error> {
379 let nb_words = s.split_whitespace().count();
380 if nb_words < MIN_NB_WORDS || nb_words % 6 != 0 || nb_words > MAX_NB_WORDS {
381 return Err(Error::BadWordCount(nb_words));
382 }
383
384 let mut words = [EOF; MAX_NB_WORDS];
386
387 let mut bits = [false; MAX_NB_WORDS * 11];
390
391 for (i, word) in s.split_whitespace().enumerate() {
392 let idx = language.find_word(word).ok_or(Error::UnknownWord(i))?;
393
394 words[i] = idx;
395
396 for j in 0..11 {
397 bits[i * 11 + j] = idx >> (10 - j) & 1 == 1;
398 }
399 }
400
401 let mut entropy = [0u8; MAX_NB_WORDS / 3 * 4];
404 let nb_bytes_entropy = nb_words / 3 * 4;
405 for i in 0..nb_bytes_entropy {
406 for j in 0..8 {
407 if bits[i * 8 + j] {
408 entropy[i] += 1 << (7 - j);
409 }
410 }
411 }
412 let check = sha256::Hash::hash(&entropy[0..nb_bytes_entropy]);
413 for i in 0..nb_bytes_entropy / 4 {
414 if bits[8 * nb_bytes_entropy + i] != ((check[i / 8] & (1 << (7 - (i % 8)))) > 0) {
415 return Err(Error::InvalidChecksum);
416 }
417 }
418
419 Ok(Mnemonic {
420 lang: language,
421 words: words,
422 })
423 }
424
425 pub fn parse_normalized(s: &str) -> Result<Mnemonic, Error> {
427 let lang = Mnemonic::language_of(s)?;
428 Mnemonic::parse_in_normalized(lang, s)
429 }
430
431 #[cfg(feature = "std")]
433 pub fn parse_in<'a, S: Into<Cow<'a, str>>>(
434 language: Language,
435 s: S,
436 ) -> Result<Mnemonic, Error> {
437 let mut cow = s.into();
438 Mnemonic::normalize_utf8_cow(&mut cow);
439 Ok(Mnemonic::parse_in_normalized(language, cow.as_ref())?)
440 }
441
442 #[cfg(feature = "std")]
444 pub fn parse<'a, S: Into<Cow<'a, str>>>(s: S) -> Result<Mnemonic, Error> {
445 let mut cow = s.into();
446 Mnemonic::normalize_utf8_cow(&mut cow);
447
448 let language = if Language::all().len() == 1 {
449 Language::all()[0]
450 } else {
451 Mnemonic::language_of(cow.as_ref())?
452 };
453
454 Ok(Mnemonic::parse_in_normalized(language, cow.as_ref())?)
455 }
456
457 pub fn word_count(&self) -> usize {
459 self.words.iter().take_while(|w| **w != EOF).count()
460 }
461
462 pub fn to_seed_normalized(&self, normalized_passphrase: &str) -> [u8; 64] {
464 const PBKDF2_ROUNDS: usize = 2048;
465 const PBKDF2_BYTES: usize = 64;
466
467 let mut seed = [0u8; PBKDF2_BYTES];
468 pbkdf2::pbkdf2(
469 self.word_iter(),
470 normalized_passphrase.as_bytes(),
471 PBKDF2_ROUNDS,
472 &mut seed,
473 );
474 seed
475 }
476
477 #[cfg(feature = "std")]
479 pub fn to_seed<'a, P: Into<Cow<'a, str>>>(&self, passphrase: P) -> [u8; 64] {
480 let normalized_passphrase = {
481 let mut cow = passphrase.into();
482 Mnemonic::normalize_utf8_cow(&mut cow);
483 cow
484 };
485 self.to_seed_normalized(normalized_passphrase.as_ref())
486 }
487
488 pub fn to_entropy_array(&self) -> ([u8; 33], usize) {
492 let language = Mnemonic::language_of_iter(self.word_iter()).unwrap();
496
497 let mut entropy = [0; 33];
499 let mut cursor = 0;
500 let mut offset = 0;
501 let mut remainder = 0;
502
503 let nb_words = self.word_count();
504 for word in self.word_iter() {
505 let idx = language.find_word(word).expect("invalid mnemonic");
506
507 remainder |= ((idx as u32) << (32 - 11)) >> offset;
508 offset += 11;
509
510 while offset >= 8 {
511 entropy[cursor] = (remainder >> 24) as u8;
512 cursor += 1;
513 remainder <<= 8;
514 offset -= 8;
515 }
516 }
517
518 if offset != 0 {
519 entropy[cursor] = (remainder >> 24) as u8;
520 }
521
522 let entropy_bytes = (nb_words / 3) * 4;
523 (entropy, entropy_bytes)
524 }
525
526 #[cfg(feature = "std")]
528 pub fn to_entropy(&self) -> Vec<u8> {
529 let (arr, len) = self.to_entropy_array();
530 arr[0..len].to_vec()
531 }
532}
533
534impl fmt::Display for Mnemonic {
535 fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
536 for (i, word) in self.word_iter().enumerate() {
537 if i > 0 {
538 f.write_str(" ")?;
539 }
540 f.write_str(word)?;
541 }
542 Ok(())
543 }
544}
545
546impl str::FromStr for Mnemonic {
547 type Err = Error;
548
549 fn from_str(s: &str) -> Result<Mnemonic, Error> {
550 #[cfg(feature = "std")]
551 {
552 Mnemonic::parse(s)
553 }
554 #[cfg(not(feature = "std"))]
555 {
556 Mnemonic::parse_normalized(s)
557 }
558 }
559}
560
561#[cfg(test)]
562mod tests {
563 use super::*;
564
565 use bitcoin_hashes::hex::FromHex;
566
567 #[cfg(feature = "rand")]
568 #[test]
569 fn test_language_of() {
570 for lang in Language::all() {
571 let m = Mnemonic::generate_in(*lang, 24).unwrap();
572 assert_eq!(*lang, Mnemonic::language_of_iter(m.word_iter()).unwrap());
573 assert_eq!(
574 *lang,
575 Mnemonic::language_of_iter(m.to_string().split_whitespace()).unwrap()
576 );
577 assert_eq!(*lang, Mnemonic::language_of(m.to_string()).unwrap());
578 assert_eq!(*lang, Mnemonic::language_of(&m.to_string()).unwrap());
579 }
580 }
581
582 #[cfg(feature = "std")]
583 #[test]
584 fn test_ambiguous_languages() {
585 let mut present = [false; language::MAX_NB_LANGUAGES];
586 let mut present_vec = Vec::new();
587 let mut alternate = true;
588 for i in 0..Language::all().len() {
589 present[i] = alternate;
590 if alternate {
591 present_vec.push(Language::all()[i]);
592 }
593 alternate = !alternate;
594 }
595 let amb = AmbiguousLanguages(present);
596 assert_eq!(amb.to_vec(), present_vec);
597 assert_eq!(amb.iter().collect::<Vec<_>>(), present_vec);
598 }
599
600 #[cfg(feature = "rand")]
601 #[test]
602 fn test_generate() {
603 let _ = Mnemonic::generate(24).unwrap();
604 let _ = Mnemonic::generate_in(Language::English, 24).unwrap();
605 let _ = Mnemonic::generate_in_with(&mut rand::thread_rng(), Language::English, 24).unwrap();
606 }
607
608 #[test]
609 fn test_vectors_english() {
610 let test_vectors = [
613 (
614 "00000000000000000000000000000000",
615 "abandon abandon abandon abandon abandon abandon abandon abandon abandon abandon abandon about",
616 "c55257c360c07c72029aebc1b53c05ed0362ada38ead3e3e9efa3708e53495531f09a6987599d18264c1e1c92f2cf141630c7a3c4ab7c81b2f001698e7463b04",
617 ),
618 (
619 "7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f",
620 "legal winner thank year wave sausage worth useful legal winner thank yellow",
621 "2e8905819b8723fe2c1d161860e5ee1830318dbf49a83bd451cfb8440c28bd6fa457fe1296106559a3c80937a1c1069be3a3a5bd381ee6260e8d9739fce1f607",
622 ),
623 (
624 "80808080808080808080808080808080",
625 "letter advice cage absurd amount doctor acoustic avoid letter advice cage above",
626 "d71de856f81a8acc65e6fc851a38d4d7ec216fd0796d0a6827a3ad6ed5511a30fa280f12eb2e47ed2ac03b5c462a0358d18d69fe4f985ec81778c1b370b652a8",
627 ),
628 (
629 "ffffffffffffffffffffffffffffffff",
630 "zoo zoo zoo zoo zoo zoo zoo zoo zoo zoo zoo wrong",
631 "ac27495480225222079d7be181583751e86f571027b0497b5b5d11218e0a8a13332572917f0f8e5a589620c6f15b11c61dee327651a14c34e18231052e48c069",
632 ),
633 (
634 "000000000000000000000000000000000000000000000000",
635 "abandon abandon abandon abandon abandon abandon abandon abandon abandon abandon abandon abandon abandon abandon abandon abandon abandon agent",
636 "035895f2f481b1b0f01fcf8c289c794660b289981a78f8106447707fdd9666ca06da5a9a565181599b79f53b844d8a71dd9f439c52a3d7b3e8a79c906ac845fa",
637 ),
638 (
639 "7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f",
640 "legal winner thank year wave sausage worth useful legal winner thank year wave sausage worth useful legal will",
641 "f2b94508732bcbacbcc020faefecfc89feafa6649a5491b8c952cede496c214a0c7b3c392d168748f2d4a612bada0753b52a1c7ac53c1e93abd5c6320b9e95dd",
642 ),
643 (
644 "808080808080808080808080808080808080808080808080",
645 "letter advice cage absurd amount doctor acoustic avoid letter advice cage absurd amount doctor acoustic avoid letter always",
646 "107d7c02a5aa6f38c58083ff74f04c607c2d2c0ecc55501dadd72d025b751bc27fe913ffb796f841c49b1d33b610cf0e91d3aa239027f5e99fe4ce9e5088cd65",
647 ),
648 (
649 "ffffffffffffffffffffffffffffffffffffffffffffffff",
650 "zoo zoo zoo zoo zoo zoo zoo zoo zoo zoo zoo zoo zoo zoo zoo zoo zoo when",
651 "0cd6e5d827bb62eb8fc1e262254223817fd068a74b5b449cc2f667c3f1f985a76379b43348d952e2265b4cd129090758b3e3c2c49103b5051aac2eaeb890a528",
652 ),
653 (
654 "0000000000000000000000000000000000000000000000000000000000000000",
655 "abandon abandon abandon abandon abandon abandon abandon abandon abandon abandon abandon abandon abandon abandon abandon abandon abandon abandon abandon abandon abandon abandon abandon art",
656 "bda85446c68413707090a52022edd26a1c9462295029f2e60cd7c4f2bbd3097170af7a4d73245cafa9c3cca8d561a7c3de6f5d4a10be8ed2a5e608d68f92fcc8",
657 ),
658 (
659 "7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f",
660 "legal winner thank year wave sausage worth useful legal winner thank year wave sausage worth useful legal winner thank year wave sausage worth title",
661 "bc09fca1804f7e69da93c2f2028eb238c227f2e9dda30cd63699232578480a4021b146ad717fbb7e451ce9eb835f43620bf5c514db0f8add49f5d121449d3e87",
662 ),
663 (
664 "8080808080808080808080808080808080808080808080808080808080808080",
665 "letter advice cage absurd amount doctor acoustic avoid letter advice cage absurd amount doctor acoustic avoid letter advice cage absurd amount doctor acoustic bless",
666 "c0c519bd0e91a2ed54357d9d1ebef6f5af218a153624cf4f2da911a0ed8f7a09e2ef61af0aca007096df430022f7a2b6fb91661a9589097069720d015e4e982f",
667 ),
668 (
669 "ffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff",
670 "zoo zoo zoo zoo zoo zoo zoo zoo zoo zoo zoo zoo zoo zoo zoo zoo zoo zoo zoo zoo zoo zoo zoo vote",
671 "dd48c104698c30cfe2b6142103248622fb7bb0ff692eebb00089b32d22484e1613912f0a5b694407be899ffd31ed3992c456cdf60f5d4564b8ba3f05a69890ad",
672 ),
673 (
674 "9e885d952ad362caeb4efe34a8e91bd2",
675 "ozone drill grab fiber curtain grace pudding thank cruise elder eight picnic",
676 "274ddc525802f7c828d8ef7ddbcdc5304e87ac3535913611fbbfa986d0c9e5476c91689f9c8a54fd55bd38606aa6a8595ad213d4c9c9f9aca3fb217069a41028",
677 ),
678 (
679 "6610b25967cdcca9d59875f5cb50b0ea75433311869e930b",
680 "gravity machine north sort system female filter attitude volume fold club stay feature office ecology stable narrow fog",
681 "628c3827a8823298ee685db84f55caa34b5cc195a778e52d45f59bcf75aba68e4d7590e101dc414bc1bbd5737666fbbef35d1f1903953b66624f910feef245ac",
682 ),
683 (
684 "68a79eaca2324873eacc50cb9c6eca8cc68ea5d936f98787c60c7ebc74e6ce7c",
685 "hamster diagram private dutch cause delay private meat slide toddler razor book happy fancy gospel tennis maple dilemma loan word shrug inflict delay length",
686 "64c87cde7e12ecf6704ab95bb1408bef047c22db4cc7491c4271d170a1b213d20b385bc1588d9c7b38f1b39d415665b8a9030c9ec653d75e65f847d8fc1fc440",
687 ),
688 (
689 "c0ba5a8e914111210f2bd131f3d5e08d",
690 "scheme spot photo card baby mountain device kick cradle pact join borrow",
691 "ea725895aaae8d4c1cf682c1bfd2d358d52ed9f0f0591131b559e2724bb234fca05aa9c02c57407e04ee9dc3b454aa63fbff483a8b11de949624b9f1831a9612",
692 ),
693 (
694 "6d9be1ee6ebd27a258115aad99b7317b9c8d28b6d76431c3",
695 "horn tenant knee talent sponsor spell gate clip pulse soap slush warm silver nephew swap uncle crack brave",
696 "fd579828af3da1d32544ce4db5c73d53fc8acc4ddb1e3b251a31179cdb71e853c56d2fcb11aed39898ce6c34b10b5382772db8796e52837b54468aeb312cfc3d",
697 ),
698 (
699 "9f6a2878b2520799a44ef18bc7df394e7061a224d2c33cd015b157d746869863",
700 "panda eyebrow bullet gorilla call smoke muffin taste mesh discover soft ostrich alcohol speed nation flash devote level hobby quick inner drive ghost inside",
701 "72be8e052fc4919d2adf28d5306b5474b0069df35b02303de8c1729c9538dbb6fc2d731d5f832193cd9fb6aeecbc469594a70e3dd50811b5067f3b88b28c3e8d",
702 ),
703 (
704 "23db8160a31d3e0dca3688ed941adbf3",
705 "cat swing flag economy stadium alone churn speed unique patch report train",
706 "deb5f45449e615feff5640f2e49f933ff51895de3b4381832b3139941c57b59205a42480c52175b6efcffaa58a2503887c1e8b363a707256bdd2b587b46541f5",
707 ),
708 (
709 "8197a4a47f0425faeaa69deebc05ca29c0a5b5cc76ceacc0",
710 "light rule cinnamon wrap drastic word pride squirrel upgrade then income fatal apart sustain crack supply proud access",
711 "4cbdff1ca2db800fd61cae72a57475fdc6bab03e441fd63f96dabd1f183ef5b782925f00105f318309a7e9c3ea6967c7801e46c8a58082674c860a37b93eda02",
712 ),
713 (
714 "066dca1a2bb7e8a1db2832148ce9933eea0f3ac9548d793112d9a95c9407efad",
715 "all hour make first leader extend hole alien behind guard gospel lava path output census museum junior mass reopen famous sing advance salt reform",
716 "26e975ec644423f4a4c4f4215ef09b4bd7ef924e85d1d17c4cf3f136c2863cf6df0a475045652c57eb5fb41513ca2a2d67722b77e954b4b3fc11f7590449191d",
717 ),
718 (
719 "f30f8c1da665478f49b001d94c5fc452",
720 "vessel ladder alter error federal sibling chat ability sun glass valve picture",
721 "2aaa9242daafcee6aa9d7269f17d4efe271e1b9a529178d7dc139cd18747090bf9d60295d0ce74309a78852a9caadf0af48aae1c6253839624076224374bc63f",
722 ),
723 (
724 "c10ec20dc3cd9f652c7fac2f1230f7a3c828389a14392f05",
725 "scissors invite lock maple supreme raw rapid void congress muscle digital elegant little brisk hair mango congress clump",
726 "7b4a10be9d98e6cba265566db7f136718e1398c71cb581e1b2f464cac1ceedf4f3e274dc270003c670ad8d02c4558b2f8e39edea2775c9e232c7cb798b069e88",
727 ),
728 (
729 "f585c11aec520db57dd353c69554b21a89b20fb0650966fa0a9d6f74fd989d8f",
730 "void come effort suffer camp survey warrior heavy shoot primary clutch crush open amazing screen patrol group space point ten exist slush involve unfold",
731 "01f5bced59dec48e362f2c45b5de68b9fd6c92c6634f44d6d40aab69056506f0e35524a518034ddc1192e1dacd32c1ed3eaa3c3b131c88ed8e7e54c49a5d0998",
732 )
733 ];
734
735 for vector in &test_vectors {
736 let entropy = Vec::<u8>::from_hex(&vector.0).unwrap();
737 let mnemonic_str = vector.1;
738 let seed = Vec::<u8>::from_hex(&vector.2).unwrap();
739
740 let mnemonic = Mnemonic::from_entropy(&entropy).unwrap();
741
742 assert_eq!(
743 mnemonic,
744 Mnemonic::parse_in_normalized(Language::English, mnemonic_str).unwrap(),
745 "failed vector: {}",
746 mnemonic_str
747 );
748 assert_eq!(
749 mnemonic,
750 Mnemonic::parse_normalized(mnemonic_str).unwrap(),
751 "failed vector: {}",
752 mnemonic_str
753 );
754 assert_eq!(
755 &seed[..],
756 &mnemonic.to_seed_normalized("TREZOR")[..],
757 "failed vector: {}",
758 mnemonic_str
759 );
760
761 #[cfg(features = "std")]
762 {
763 assert_eq!(&mnemonic.to_string(), mnemonic_str, "failed vector: {}", mnemonic_str);
764 assert_eq!(
765 mnemonic,
766 Mnemonic::parse_in(Language::English, mnemonic_str).unwrap(),
767 "failed vector: {}",
768 mnemonic_str
769 );
770 assert_eq!(
771 mnemonic,
772 Mnemonic::parse(mnemonic_str).unwrap(),
773 "failed vector: {}",
774 mnemonic_str
775 );
776 assert_eq!(
777 &seed[..],
778 &mnemonic.to_seed("TREZOR")[..],
779 "failed vector: {}",
780 mnemonic_str
781 );
782 assert_eq!(&entropy, &mnemonic.to_entropy(), "failed vector: {}", mnemonic_str);
783 assert_eq!(
784 &entropy,
785 &mnemonic.to_entropy_array().0[0..entropy.len()],
786 "failed vector: {}",
787 mnemonic_str
788 );
789 }
790 }
791 }
792
793 #[test]
794 fn test_invalid_engish() {
795 assert_eq!(
799 Mnemonic::parse_normalized(
800 "getter advice cage absurd amount doctor acoustic avoid letter advice cage above",
801 ),
802 Err(Error::UnknownWord(0))
803 );
804
805 assert_eq!(
806 Mnemonic::parse_normalized(
807 "letter advice cagex absurd amount doctor acoustic avoid letter advice cage above",
808 ),
809 Err(Error::UnknownWord(2))
810 );
811
812 assert_eq!(
813 Mnemonic::parse_normalized(
814 "advice cage absurd amount doctor acoustic avoid letter advice cage above",
815 ),
816 Err(Error::BadWordCount(11))
817 );
818
819 assert_eq!(
820 Mnemonic::parse_normalized(
821 "primary advice cage absurd amount doctor acoustic avoid letter advice cage above",
822 ),
823 Err(Error::InvalidChecksum)
824 );
825 }
826
827 #[test]
828 fn test_invalid_entropy() {
829 assert_eq!(Mnemonic::from_entropy(&vec![b'x'; 17]), Err(Error::BadEntropyBitCount(136)));
831
832 assert_eq!(Mnemonic::from_entropy(&vec![b'x'; 4]), Err(Error::BadEntropyBitCount(32)));
834
835 assert_eq!(Mnemonic::from_entropy(&vec![b'x'; 36]), Err(Error::BadEntropyBitCount(288)));
837 }
838
839 #[cfg(all(feature = "japanese", feature = "std"))]
840 #[test]
841 fn test_vectors_japanese() {
842 let vectors = [
850 (
851 "00000000000000000000000000000000",
852 "あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あおぞら",
853 "㍍ガバヴァぱばぐゞちぢ十人十色",
854 "a262d6fb6122ecf45be09c50492b31f92e9beb7d9a845987a02cefda57a15f9c467a17872029a9e92299b5cbdf306e3a0ee620245cbd508959b6cb7ca637bd55",
855 ),
856 (
857 "7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f",
858 "そつう れきだい ほんやく わかす りくつ ばいか ろせん やちん そつう れきだい ほんやく わかめ",
859 "㍍ガバヴァぱばぐゞちぢ十人十色",
860 "aee025cbe6ca256862f889e48110a6a382365142f7d16f2b9545285b3af64e542143a577e9c144e101a6bdca18f8d97ec3366ebf5b088b1c1af9bc31346e60d9",
861 ),
862 (
863 "80808080808080808080808080808080",
864 "そとづら あまど おおう あこがれる いくぶん けいけん あたえる いよく そとづら あまど おおう あかちゃん",
865 "㍍ガバヴァぱばぐゞちぢ十人十色",
866 "e51736736ebdf77eda23fa17e31475fa1d9509c78f1deb6b4aacfbd760a7e2ad769c714352c95143b5c1241985bcb407df36d64e75dd5a2b78ca5d2ba82a3544",
867 ),
868 (
869 "ffffffffffffffffffffffffffffffff",
870 "われる われる われる われる われる われる われる われる われる われる われる ろんぶん",
871 "㍍ガバヴァぱばぐゞちぢ十人十色",
872 "4cd2ef49b479af5e1efbbd1e0bdc117f6a29b1010211df4f78e2ed40082865793e57949236c43b9fe591ec70e5bb4298b8b71dc4b267bb96ed4ed282c8f7761c",
873 ),
874 (
875 "000000000000000000000000000000000000000000000000",
876 "あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あらいぐま",
877 "㍍ガバヴァぱばぐゞちぢ十人十色",
878 "d99e8f1ce2d4288d30b9c815ae981edd923c01aa4ffdc5dee1ab5fe0d4a3e13966023324d119105aff266dac32e5cd11431eeca23bbd7202ff423f30d6776d69",
879 ),
880 (
881 "7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f",
882 "そつう れきだい ほんやく わかす りくつ ばいか ろせん やちん そつう れきだい ほんやく わかす りくつ ばいか ろせん やちん そつう れいぎ",
883 "㍍ガバヴァぱばぐゞちぢ十人十色",
884 "eaaf171efa5de4838c758a93d6c86d2677d4ccda4a064a7136344e975f91fe61340ec8a615464b461d67baaf12b62ab5e742f944c7bd4ab6c341fbafba435716",
885 ),
886 (
887 "808080808080808080808080808080808080808080808080",
888 "そとづら あまど おおう あこがれる いくぶん けいけん あたえる いよく そとづら あまど おおう あこがれる いくぶん けいけん あたえる いよく そとづら いきなり",
889 "㍍ガバヴァぱばぐゞちぢ十人十色",
890 "aec0f8d3167a10683374c222e6e632f2940c0826587ea0a73ac5d0493b6a632590179a6538287641a9fc9df8e6f24e01bf1be548e1f74fd7407ccd72ecebe425",
891 ),
892 (
893 "ffffffffffffffffffffffffffffffffffffffffffffffff",
894 "われる われる われる われる われる われる われる われる われる われる われる われる われる われる われる われる われる りんご",
895 "㍍ガバヴァぱばぐゞちぢ十人十色",
896 "f0f738128a65b8d1854d68de50ed97ac1831fc3a978c569e415bbcb431a6a671d4377e3b56abd518daa861676c4da75a19ccb41e00c37d086941e471a4374b95",
897 ),
898 (
899 "0000000000000000000000000000000000000000000000000000000000000000",
900 "あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん あいこくしん いってい",
901 "㍍ガバヴァぱばぐゞちぢ十人十色",
902 "23f500eec4a563bf90cfda87b3e590b211b959985c555d17e88f46f7183590cd5793458b094a4dccc8f05807ec7bd2d19ce269e20568936a751f6f1ec7c14ddd",
903 ),
904 (
905 "7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f7f",
906 "そつう れきだい ほんやく わかす りくつ ばいか ろせん やちん そつう れきだい ほんやく わかす りくつ ばいか ろせん やちん そつう れきだい ほんやく わかす りくつ ばいか ろせん まんきつ",
907 "㍍ガバヴァぱばぐゞちぢ十人十色",
908 "cd354a40aa2e241e8f306b3b752781b70dfd1c69190e510bc1297a9c5738e833bcdc179e81707d57263fb7564466f73d30bf979725ff783fb3eb4baa86560b05",
909 ),
910 (
911 "8080808080808080808080808080808080808080808080808080808080808080",
912 "そとづら あまど おおう あこがれる いくぶん けいけん あたえる いよく そとづら あまど おおう あこがれる いくぶん けいけん あたえる いよく そとづら あまど おおう あこがれる いくぶん けいけん あたえる うめる",
913 "㍍ガバヴァぱばぐゞちぢ十人十色",
914 "6b7cd1b2cdfeeef8615077cadd6a0625f417f287652991c80206dbd82db17bf317d5c50a80bd9edd836b39daa1b6973359944c46d3fcc0129198dc7dc5cd0e68",
915 ),
916 (
917 "ffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff",
918 "われる われる われる われる われる われる われる われる われる われる われる われる われる われる われる われる われる われる われる われる われる われる われる らいう",
919 "㍍ガバヴァぱばぐゞちぢ十人十色",
920 "a44ba7054ac2f9226929d56505a51e13acdaa8a9097923ca07ea465c4c7e294c038f3f4e7e4b373726ba0057191aced6e48ac8d183f3a11569c426f0de414623",
921 ),
922 (
923 "77c2b00716cec7213839159e404db50d",
924 "せまい うちがわ あずき かろう めずらしい だんち ますく おさめる ていぼう あたる すあな えしゃく",
925 "㍍ガバヴァぱばぐゞちぢ十人十色",
926 "344cef9efc37d0cb36d89def03d09144dd51167923487eec42c487f7428908546fa31a3c26b7391a2b3afe7db81b9f8c5007336b58e269ea0bd10749a87e0193",
927 ),
928 (
929 "b63a9c59a6e641f288ebc103017f1da9f8290b3da6bdef7b",
930 "ぬすむ ふっかつ うどん こうりつ しつじ りょうり おたがい せもたれ あつめる いちりゅう はんしゃ ごますり そんけい たいちょう らしんばん ぶんせき やすみ ほいく",
931 "㍍ガバヴァぱばぐゞちぢ十人十色",
932 "b14e7d35904cb8569af0d6a016cee7066335a21c1c67891b01b83033cadb3e8a034a726e3909139ecd8b2eb9e9b05245684558f329b38480e262c1d6bc20ecc4",
933 ),
934 (
935 "3e141609b97933b66a060dcddc71fad1d91677db872031e85f4c015c5e7e8982",
936 "くのう てぬぐい そんかい すろっと ちきゅう ほあん とさか はくしゅ ひびく みえる そざい てんすう たんぴん くしょう すいようび みけん きさらぎ げざん ふくざつ あつかう はやい くろう おやゆび こすう",
937 "㍍ガバヴァぱばぐゞちぢ十人十色",
938 "32e78dce2aff5db25aa7a4a32b493b5d10b4089923f3320c8b287a77e512455443298351beb3f7eb2390c4662a2e566eec5217e1a37467af43b46668d515e41b",
939 ),
940 (
941 "0460ef47585604c5660618db2e6a7e7f",
942 "あみもの いきおい ふいうち にげる ざんしょ じかん ついか はたん ほあん すんぽう てちがい わかめ",
943 "㍍ガバヴァぱばぐゞちぢ十人十色",
944 "0acf902cd391e30f3f5cb0605d72a4c849342f62bd6a360298c7013d714d7e58ddf9c7fdf141d0949f17a2c9c37ced1d8cb2edabab97c4199b142c829850154b",
945 ),
946 (
947 "72f60ebac5dd8add8d2a25a797102c3ce21bc029c200076f",
948 "すろっと にくしみ なやむ たとえる へいこう すくう きない けってい とくべつ ねっしん いたみ せんせい おくりがな まかい とくい けあな いきおい そそぐ",
949 "㍍ガバヴァぱばぐゞちぢ十人十色",
950 "9869e220bec09b6f0c0011f46e1f9032b269f096344028f5006a6e69ea5b0b8afabbb6944a23e11ebd021f182dd056d96e4e3657df241ca40babda532d364f73",
951 ),
952 (
953 "2c85efc7f24ee4573d2b81a6ec66cee209b2dcbd09d8eddc51e0215b0b68e416",
954 "かほご きうい ゆたか みすえる もらう がっこう よそう ずっと ときどき したうけ にんか はっこう つみき すうじつ よけい くげん もくてき まわり せめる げざい にげる にんたい たんそく ほそく",
955 "㍍ガバヴァぱばぐゞちぢ十人十色",
956 "713b7e70c9fbc18c831bfd1f03302422822c3727a93a5efb9659bec6ad8d6f2c1b5c8ed8b0b77775feaf606e9d1cc0a84ac416a85514ad59f5541ff5e0382481",
957 ),
958 (
959 "eaebabb2383351fd31d703840b32e9e2",
960 "めいえん さのう めだつ すてる きぬごし ろんぱ はんこ まける たいおう さかいし ねんいり はぶらし",
961 "㍍ガバヴァぱばぐゞちぢ十人十色",
962 "06e1d5289a97bcc95cb4a6360719131a786aba057d8efd603a547bd254261c2a97fcd3e8a4e766d5416437e956b388336d36c7ad2dba4ee6796f0249b10ee961",
963 ),
964 (
965 "7ac45cfe7722ee6c7ba84fbc2d5bd61b45cb2fe5eb65aa78",
966 "せんぱい おしえる ぐんかん もらう きあい きぼう やおや いせえび のいず じゅしん よゆう きみつ さといも ちんもく ちわわ しんせいじ とめる はちみつ",
967 "㍍ガバヴァぱばぐゞちぢ十人十色",
968 "1fef28785d08cbf41d7a20a3a6891043395779ed74503a5652760ee8c24dfe60972105ee71d5168071a35ab7b5bd2f8831f75488078a90f0926c8e9171b2bc4a",
969 ),
970 (
971 "4fa1a8bc3e6d80ee1316050e862c1812031493212b7ec3f3bb1b08f168cabeef",
972 "こころ いどう きあつ そうがんきょう へいあん せつりつ ごうせい はいち いびき きこく あんい おちつく きこえる けんとう たいこ すすめる はっけん ていど はんおん いんさつ うなぎ しねま れいぼう みつかる",
973 "㍍ガバヴァぱばぐゞちぢ十人十色",
974 "43de99b502e152d4c198542624511db3007c8f8f126a30818e856b2d8a20400d29e7a7e3fdd21f909e23be5e3c8d9aee3a739b0b65041ff0b8637276703f65c2",
975 ),
976 (
977 "18ab19a9f54a9274f03e5209a2ac8a91",
978 "うりきれ さいせい じゆう むろん とどける ぐうたら はいれつ ひけつ いずれ うちあわせ おさめる おたく",
979 "㍍ガバヴァぱばぐゞちぢ十人十色",
980 "3d711f075ee44d8b535bb4561ad76d7d5350ea0b1f5d2eac054e869ff7963cdce9581097a477d697a2a9433a0c6884bea10a2193647677977c9820dd0921cbde",
981 ),
982 (
983 "18a2e1d81b8ecfb2a333adcb0c17a5b9eb76cc5d05db91a4",
984 "うりきれ うねる せっさたくま きもち めんきょ へいたく たまご ぜっく びじゅつかん さんそ むせる せいじ ねくたい しはらい せおう ねんど たんまつ がいけん",
985 "㍍ガバヴァぱばぐゞちぢ十人十色",
986 "753ec9e333e616e9471482b4b70a18d413241f1e335c65cd7996f32b66cf95546612c51dcf12ead6f805f9ee3d965846b894ae99b24204954be80810d292fcdd",
987 ),
988 (
989 "15da872c95a13dd738fbf50e427583ad61f18fd99f628c417a61cf8343c90419",
990 "うちゅう ふそく ひしょ がちょう うけもつ めいそう みかん そざい いばる うけとる さんま さこつ おうさま ぱんつ しひょう めした たはつ いちぶ つうじょう てさぎょう きつね みすえる いりぐち かめれおん",
991 "㍍ガバヴァぱばぐゞちぢ十人十色",
992 "346b7321d8c04f6f37b49fdf062a2fddc8e1bf8f1d33171b65074531ec546d1d3469974beccb1a09263440fc92e1042580a557fdce314e27ee4eabb25fa5e5fe",
993 )
994 ];
995
996 for vector in &vectors {
997 let entropy = Vec::<u8>::from_hex(&vector.0).unwrap();
998 let mnemonic_str = vector.1;
999 let passphrase = vector.2;
1000 let seed = Vec::<u8>::from_hex(&vector.3).unwrap();
1001
1002 let mnemonic = Mnemonic::from_entropy_in(Language::Japanese, &entropy).unwrap();
1003
1004 assert_eq!(seed, &mnemonic.to_seed(passphrase)[..], "failed vector: {}", mnemonic_str);
1005 let rt = Mnemonic::parse_in(Language::Japanese, mnemonic.to_string())
1006 .expect(&format!("vector: {}", mnemonic_str));
1007 assert_eq!(seed, &rt.to_seed(passphrase)[..]);
1008
1009 let mnemonic = Mnemonic::parse_in(Language::Japanese, mnemonic_str)
1010 .expect(&format!("vector: {}", mnemonic_str));
1011 assert_eq!(seed, &mnemonic.to_seed(passphrase)[..], "failed vector: {}", mnemonic_str);
1012 }
1013 }
1014}