[fdt] Add ability to parse a MAC address from a flattened device tree
[ipxe.git] / src / crypto / entropy.c
1 /*
2 * Copyright (C) 2012 Michael Brown <mbrown@fensystems.co.uk>.
3 *
4 * This program is free software; you can redistribute it and/or
5 * modify it under the terms of the GNU General Public License as
6 * published by the Free Software Foundation; either version 2 of the
7 * License, or any later version.
8 *
9 * This program is distributed in the hope that it will be useful, but
10 * WITHOUT ANY WARRANTY; without even the implied warranty of
11 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
12 * General Public License for more details.
13 *
14 * You should have received a copy of the GNU General Public License
15 * along with this program; if not, write to the Free Software
16 * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA
17 * 02110-1301, USA.
18 *
19 * You can also choose to distribute this program under the terms of
20 * the Unmodified Binary Distribution Licence (as given in the file
21 * COPYING.UBDL), provided that you have satisfied its requirements.
22 */
23
24 FILE_LICENCE ( GPL2_OR_LATER_OR_UBDL );
25
26 /** @file
27 *
28 * Entropy source
29 *
30 * This algorithm is designed to comply with ANS X9.82 Part 4 (April
31 * 2011 Draft) Section 13.3. This standard is unfortunately not
32 * freely available.
33 */
34
35 #include <stdint.h>
36 #include <assert.h>
37 #include <string.h>
38 #include <errno.h>
39 #include <ipxe/crypto.h>
40 #include <ipxe/hash_df.h>
41 #include <ipxe/entropy.h>
42
43 /* Disambiguate the various error causes */
44 #define EPIPE_REPETITION_COUNT_TEST \
45 __einfo_error ( EINFO_EPIPE_REPETITION_COUNT_TEST )
46 #define EINFO_EPIPE_REPETITION_COUNT_TEST \
47 __einfo_uniqify ( EINFO_EPIPE, 0x01, "Repetition count test failed" )
48 #define EPIPE_ADAPTIVE_PROPORTION_TEST \
49 __einfo_error ( EINFO_EPIPE_ADAPTIVE_PROPORTION_TEST )
50 #define EINFO_EPIPE_ADAPTIVE_PROPORTION_TEST \
51 __einfo_uniqify ( EINFO_EPIPE, 0x02, "Adaptive proportion test failed" )
52
53 /**
54 * Calculate cutoff value for the repetition count test
55 *
56 * @ret cutoff Cutoff value
57 *
58 * This is the cutoff value for the Repetition Count Test defined in
59 * ANS X9.82 Part 2 (October 2011 Draft) Section 8.5.2.1.2.
60 */
61 static inline __attribute__ (( always_inline )) unsigned int
62 repetition_count_cutoff ( void ) {
63 double max_repetitions;
64 unsigned int cutoff;
65
66 /* The cutoff formula for the repetition test is:
67 *
68 * C = ( 1 + ( -log2(W) / H_min ) )
69 *
70 * where W is set at 2^(-30) (in ANS X9.82 Part 2 (October
71 * 2011 Draft) Section 8.5.2.1.3.1).
72 */
73 max_repetitions = ( 1 + ( MIN_ENTROPY ( 30 ) /
74 min_entropy_per_sample() ) );
75
76 /* Round up to a whole number of repetitions. We don't have
77 * the ceil() function available, so do the rounding by hand.
78 */
79 cutoff = max_repetitions;
80 if ( cutoff < max_repetitions )
81 cutoff++;
82 linker_assert ( ( cutoff >= max_repetitions ), rounding_error );
83
84 /* Floating-point operations are not allowed in iPXE since we
85 * never set up a suitable environment. Abort the build
86 * unless the calculated number of repetitions is a
87 * compile-time constant.
88 */
89 linker_assert ( __builtin_constant_p ( cutoff ),
90 repetition_count_cutoff_not_constant );
91
92 return cutoff;
93 }
94
95 /**
96 * Perform repetition count test
97 *
98 * @v sample Noise sample
99 * @ret rc Return status code
100 *
101 * This is the Repetition Count Test defined in ANS X9.82 Part 2
102 * (October 2011 Draft) Section 8.5.2.1.2.
103 */
104 static int repetition_count_test ( noise_sample_t sample ) {
105 static noise_sample_t most_recent_sample;
106 static unsigned int repetition_count = 0;
107
108 /* A = the most recently seen sample value
109 * B = the number of times that value A has been seen in a row
110 * C = the cutoff value above which the repetition test should fail
111 */
112
113 /* 1. For each new sample processed:
114 *
115 * (Note that the test for "repetition_count > 0" ensures that
116 * the initial value of most_recent_sample is treated as being
117 * undefined.)
118 */
119 if ( ( sample == most_recent_sample ) && ( repetition_count > 0 ) ) {
120
121 /* a) If the new sample = A, then B is incremented by one. */
122 repetition_count++;
123
124 /* i. If B >= C, then an error condition is raised
125 * due to a failure of the test
126 */
127 if ( repetition_count >= repetition_count_cutoff() )
128 return -EPIPE_REPETITION_COUNT_TEST;
129
130 } else {
131
132 /* b) Else:
133 * i. A = new sample
134 */
135 most_recent_sample = sample;
136
137 /* ii. B = 1 */
138 repetition_count = 1;
139 }
140
141 return 0;
142 }
143
144 /**
145 * Window size for the adaptive proportion test
146 *
147 * ANS X9.82 Part 2 (October 2011 Draft) Section 8.5.2.1.3.1.1 allows
148 * five possible window sizes: 16, 64, 256, 4096 and 65536.
149 *
150 * We expect to generate relatively few (<256) entropy samples during
151 * a typical iPXE run; the use of a large window size would mean that
152 * the test would never complete a single cycle. We use a window size
153 * of 64, which is the smallest window size that permits values of
154 * H_min down to one bit per sample.
155 */
156 #define ADAPTIVE_PROPORTION_WINDOW_SIZE 64
157
158 /**
159 * Combine adaptive proportion test window size and min-entropy
160 *
161 * @v n N (window size)
162 * @v h H (min-entropy)
163 * @ret n_h (N,H) combined value
164 */
165 #define APC_N_H( n, h ) ( ( (n) << 8 ) | (h) )
166
167 /**
168 * Define a row of the adaptive proportion cutoff table
169 *
170 * @v h H (min-entropy)
171 * @v c16 Cutoff for N=16
172 * @v c64 Cutoff for N=64
173 * @v c256 Cutoff for N=256
174 * @v c4096 Cutoff for N=4096
175 * @v c65536 Cutoff for N=65536
176 */
177 #define APC_TABLE_ROW( h, c16, c64, c256, c4096, c65536) \
178 case APC_N_H ( 16, h ) : return c16; \
179 case APC_N_H ( 64, h ) : return c64; \
180 case APC_N_H ( 256, h ) : return c256; \
181 case APC_N_H ( 4096, h ) : return c4096; \
182 case APC_N_H ( 65536, h ) : return c65536;
183
184 /** Value used to represent "N/A" in adaptive proportion cutoff table */
185 #define APC_NA 0
186
187 /**
188 * Look up value in adaptive proportion test cutoff table
189 *
190 * @v n N (window size)
191 * @v h H (min-entropy)
192 * @ret cutoff Cutoff
193 *
194 * This is the table of cutoff values defined in ANS X9.82 Part 2
195 * (October 2011 Draft) Section 8.5.2.1.3.1.2.
196 */
197 static inline __attribute__ (( always_inline )) unsigned int
198 adaptive_proportion_cutoff_lookup ( unsigned int n, unsigned int h ) {
199 switch ( APC_N_H ( n, h ) ) {
200 APC_TABLE_ROW ( 1, APC_NA, 51, 168, 2240, 33537 );
201 APC_TABLE_ROW ( 2, APC_NA, 35, 100, 1193, 17053 );
202 APC_TABLE_ROW ( 3, 10, 24, 61, 643, 8705 );
203 APC_TABLE_ROW ( 4, 8, 16, 38, 354, 4473 );
204 APC_TABLE_ROW ( 5, 6, 12, 25, 200, 2321 );
205 APC_TABLE_ROW ( 6, 5, 9, 17, 117, 1220 );
206 APC_TABLE_ROW ( 7, 4, 7, 15, 71, 653 );
207 APC_TABLE_ROW ( 8, 4, 5, 9, 45, 358 );
208 APC_TABLE_ROW ( 9, 3, 4, 7, 30, 202 );
209 APC_TABLE_ROW ( 10, 3, 4, 5, 21, 118 );
210 APC_TABLE_ROW ( 11, 2, 3, 4, 15, 71 );
211 APC_TABLE_ROW ( 12, 2, 3, 4, 11, 45 );
212 APC_TABLE_ROW ( 13, 2, 2, 3, 9, 30 );
213 APC_TABLE_ROW ( 14, 2, 2, 3, 7, 21 );
214 APC_TABLE_ROW ( 15, 1, 2, 2, 6, 15 );
215 APC_TABLE_ROW ( 16, 1, 2, 2, 5, 11 );
216 APC_TABLE_ROW ( 17, 1, 1, 2, 4, 9 );
217 APC_TABLE_ROW ( 18, 1, 1, 2, 4, 7 );
218 APC_TABLE_ROW ( 19, 1, 1, 1, 3, 6 );
219 APC_TABLE_ROW ( 20, 1, 1, 1, 3, 5 );
220 default:
221 return APC_NA;
222 }
223 }
224
225 /**
226 * Calculate cutoff value for the adaptive proportion test
227 *
228 * @ret cutoff Cutoff value
229 *
230 * This is the cutoff value for the Adaptive Proportion Test defined
231 * in ANS X9.82 Part 2 (October 2011 Draft) Section 8.5.2.1.3.1.2.
232 */
233 static inline __attribute__ (( always_inline )) unsigned int
234 adaptive_proportion_cutoff ( void ) {
235 unsigned int h;
236 unsigned int n;
237 unsigned int cutoff;
238
239 /* Look up cutoff value in cutoff table */
240 n = ADAPTIVE_PROPORTION_WINDOW_SIZE;
241 h = ( min_entropy_per_sample() / MIN_ENTROPY_SCALE );
242 cutoff = adaptive_proportion_cutoff_lookup ( n, h );
243
244 /* Fail unless cutoff value is a build-time constant */
245 linker_assert ( __builtin_constant_p ( cutoff ),
246 adaptive_proportion_cutoff_not_constant );
247
248 /* Fail if cutoff value is N/A */
249 linker_assert ( ( cutoff != APC_NA ),
250 adaptive_proportion_cutoff_not_applicable );
251
252 return cutoff;
253 }
254
255 /**
256 * Perform adaptive proportion test
257 *
258 * @v sample Noise sample
259 * @ret rc Return status code
260 *
261 * This is the Adaptive Proportion Test for the Most Common Value
262 * defined in ANS X9.82 Part 2 (October 2011 Draft) Section 8.5.2.1.3.
263 */
264 static int adaptive_proportion_test ( noise_sample_t sample ) {
265 static noise_sample_t current_counted_sample;
266 static unsigned int sample_count = ADAPTIVE_PROPORTION_WINDOW_SIZE;
267 static unsigned int repetition_count;
268
269 /* A = the sample value currently being counted
270 * B = the number of samples examined in this run of the test so far
271 * N = the total number of samples that must be observed in
272 * one run of the test, also known as the "window size" of
273 * the test
274 * B = the current number of times that S (sic) has been seen
275 * in the W (sic) samples examined so far
276 * C = the cutoff value above which the repetition test should fail
277 * W = the probability of a false positive: 2^-30
278 */
279
280 /* 1. The entropy source draws the current sample from the
281 * noise source.
282 *
283 * (Nothing to do; we already have the current sample.)
284 */
285
286 /* 2. If S = N, then a new run of the test begins: */
287 if ( sample_count == ADAPTIVE_PROPORTION_WINDOW_SIZE ) {
288
289 /* a. A = the current sample */
290 current_counted_sample = sample;
291
292 /* b. S = 0 */
293 sample_count = 0;
294
295 /* c. B = 0 */
296 repetition_count = 0;
297
298 } else {
299
300 /* Else: (the test is already running)
301 * a. S = S + 1
302 */
303 sample_count++;
304
305 /* b. If A = the current sample, then: */
306 if ( sample == current_counted_sample ) {
307
308 /* i. B = B + 1 */
309 repetition_count++;
310
311 /* ii. If S (sic) > C then raise an error
312 * condition, because the test has
313 * detected a failure
314 */
315 if ( repetition_count > adaptive_proportion_cutoff() )
316 return -EPIPE_ADAPTIVE_PROPORTION_TEST;
317
318 }
319 }
320
321 return 0;
322 }
323
324 /**
325 * Get entropy sample
326 *
327 * @ret entropy Entropy sample
328 * @ret rc Return status code
329 *
330 * This is the GetEntropy function defined in ANS X9.82 Part 2
331 * (October 2011 Draft) Section 6.5.1.
332 */
333 static int get_entropy ( entropy_sample_t *entropy ) {
334 static int rc = 0;
335 noise_sample_t noise;
336
337 /* Any failure is permanent */
338 if ( rc != 0 )
339 return rc;
340
341 /* Get noise sample */
342 if ( ( rc = get_noise ( &noise ) ) != 0 )
343 return rc;
344
345 /* Perform Repetition Count Test and Adaptive Proportion Test
346 * as mandated by ANS X9.82 Part 2 (October 2011 Draft)
347 * Section 8.5.2.1.1.
348 */
349 if ( ( rc = repetition_count_test ( noise ) ) != 0 )
350 return rc;
351 if ( ( rc = adaptive_proportion_test ( noise ) ) != 0 )
352 return rc;
353
354 /* We do not use any optional conditioning component */
355 *entropy = noise;
356
357 return 0;
358 }
359
360 /**
361 * Calculate number of samples required for startup tests
362 *
363 * @ret num_samples Number of samples required
364 *
365 * ANS X9.82 Part 2 (October 2011 Draft) Section 8.5.2.1.5 requires
366 * that at least one full cycle of the continuous tests must be
367 * performed at start-up.
368 */
369 static inline __attribute__ (( always_inline )) unsigned int
370 startup_test_count ( void ) {
371 unsigned int num_samples;
372
373 /* At least max(N,C) samples shall be generated by the noise
374 * source for start-up testing.
375 */
376 num_samples = repetition_count_cutoff();
377 if ( num_samples < adaptive_proportion_cutoff() )
378 num_samples = adaptive_proportion_cutoff();
379 linker_assert ( __builtin_constant_p ( num_samples ),
380 startup_test_count_not_constant );
381
382 return num_samples;
383 }
384
385 /**
386 * Create next nonce value
387 *
388 * @ret nonce Nonce
389 *
390 * This is the MakeNextNonce function defined in ANS X9.82 Part 4
391 * (April 2011 Draft) Section 13.3.4.2.
392 */
393 static uint32_t make_next_nonce ( void ) {
394 static uint32_t nonce;
395
396 /* The simplest implementation of a nonce uses a large counter */
397 nonce++;
398
399 return nonce;
400 }
401
402 /**
403 * Obtain entropy input temporary buffer
404 *
405 * @v num_samples Number of entropy samples
406 * @v tmp Temporary buffer
407 * @v tmp_len Length of temporary buffer
408 * @ret rc Return status code
409 *
410 * This is (part of) the implementation of the Get_entropy_input
411 * function (using an entropy source as the source of entropy input
412 * and condensing each entropy source output after each GetEntropy
413 * call) as defined in ANS X9.82 Part 4 (April 2011 Draft) Section
414 * 13.3.4.2.
415 *
416 * To minimise code size, the number of samples required is calculated
417 * at compilation time.
418 */
419 int get_entropy_input_tmp ( unsigned int num_samples, uint8_t *tmp,
420 size_t tmp_len ) {
421 static unsigned int startup_tested = 0;
422 struct {
423 uint32_t nonce;
424 entropy_sample_t sample;
425 } __attribute__ (( packed )) data;;
426 uint8_t df_buf[tmp_len];
427 unsigned int i;
428 int rc;
429
430 /* Enable entropy gathering */
431 if ( ( rc = entropy_enable() ) != 0 )
432 return rc;
433
434 /* Perform mandatory startup tests, if not yet performed */
435 for ( ; startup_tested < startup_test_count() ; startup_tested++ ) {
436 if ( ( rc = get_entropy ( &data.sample ) ) != 0 )
437 goto err_get_entropy;
438 }
439
440 /* 3. entropy_total = 0
441 *
442 * (Nothing to do; the number of entropy samples required has
443 * already been precalculated.)
444 */
445
446 /* 4. tmp = a fixed n-bit value, such as 0^n */
447 memset ( tmp, 0, tmp_len );
448
449 /* 5. While ( entropy_total < min_entropy ) */
450 while ( num_samples-- ) {
451 /* 5.1. ( status, entropy_bitstring, assessed_entropy )
452 * = GetEntropy()
453 * 5.2. If status indicates an error, return ( status, Null )
454 */
455 if ( ( rc = get_entropy ( &data.sample ) ) != 0 )
456 goto err_get_entropy;
457
458 /* 5.3. nonce = MakeNextNonce() */
459 data.nonce = make_next_nonce();
460
461 /* 5.4. tmp = tmp XOR
462 * df ( ( nonce || entropy_bitstring ), n )
463 */
464 hash_df ( &entropy_hash_df_algorithm, &data, sizeof ( data ),
465 df_buf, sizeof ( df_buf ) );
466 for ( i = 0 ; i < tmp_len ; i++ )
467 tmp[i] ^= df_buf[i];
468
469 /* 5.5. entropy_total = entropy_total + assessed_entropy
470 *
471 * (Nothing to do; the number of entropy samples
472 * required has already been precalculated.)
473 */
474 }
475
476 /* Disable entropy gathering */
477 entropy_disable();
478
479 return 0;
480
481 err_get_entropy:
482 entropy_disable();
483 return rc;
484 }