| /* |
| * Copyright (C) 2012 Michael Brown <mbrown@fensystems.co.uk>. |
| * |
| * This program is free software; you can redistribute it and/or |
| * modify it under the terms of the GNU General Public License as |
| * published by the Free Software Foundation; either version 2 of the |
| * License, or any later version. |
| * |
| * This program is distributed in the hope that it will be useful, but |
| * WITHOUT ANY WARRANTY; without even the implied warranty of |
| * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU |
| * General Public License for more details. |
| * |
| * You should have received a copy of the GNU General Public License |
| * along with this program; if not, write to the Free Software |
| * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA |
| * 02110-1301, USA. |
| * |
| * You can also choose to distribute this program under the terms of |
| * the Unmodified Binary Distribution Licence (as given in the file |
| * COPYING.UBDL), provided that you have satisfied its requirements. |
| */ |
| |
| FILE_LICENCE ( GPL2_OR_LATER_OR_UBDL ); |
| |
| /** @file |
| * |
| * Entropy source |
| * |
| * This algorithm is designed to comply with ANS X9.82 Part 4 (April |
| * 2011 Draft) Section 13.3. This standard is unfortunately not |
| * freely available. |
| */ |
| |
| #include <stdint.h> |
| #include <assert.h> |
| #include <string.h> |
| #include <errno.h> |
| #include <ipxe/crypto.h> |
| #include <ipxe/hash_df.h> |
| #include <ipxe/entropy.h> |
| |
| /* Disambiguate the various error causes */ |
| #define EPIPE_REPETITION_COUNT_TEST \ |
| __einfo_error ( EINFO_EPIPE_REPETITION_COUNT_TEST ) |
| #define EINFO_EPIPE_REPETITION_COUNT_TEST \ |
| __einfo_uniqify ( EINFO_EPIPE, 0x01, "Repetition count test failed" ) |
| #define EPIPE_ADAPTIVE_PROPORTION_TEST \ |
| __einfo_error ( EINFO_EPIPE_ADAPTIVE_PROPORTION_TEST ) |
| #define EINFO_EPIPE_ADAPTIVE_PROPORTION_TEST \ |
| __einfo_uniqify ( EINFO_EPIPE, 0x02, "Adaptive proportion test failed" ) |
| |
| /** |
| * Calculate cutoff value for the repetition count test |
| * |
| * @ret cutoff Cutoff value |
| * |
| * This is the cutoff value for the Repetition Count Test defined in |
| * ANS X9.82 Part 2 (October 2011 Draft) Section 8.5.2.1.2. |
| */ |
| static inline __attribute__ (( always_inline )) unsigned int |
| repetition_count_cutoff ( void ) { |
| double max_repetitions; |
| unsigned int cutoff; |
| |
| /* The cutoff formula for the repetition test is: |
| * |
| * C = ( 1 + ( -log2(W) / H_min ) ) |
| * |
| * where W is set at 2^(-30) (in ANS X9.82 Part 2 (October |
| * 2011 Draft) Section 8.5.2.1.3.1). |
| */ |
| max_repetitions = ( 1 + ( MIN_ENTROPY ( 30 ) / |
| min_entropy_per_sample() ) ); |
| |
| /* Round up to a whole number of repetitions. We don't have |
| * the ceil() function available, so do the rounding by hand. |
| */ |
| cutoff = max_repetitions; |
| if ( cutoff < max_repetitions ) |
| cutoff++; |
| linker_assert ( ( cutoff >= max_repetitions ), rounding_error ); |
| |
| /* Floating-point operations are not allowed in iPXE since we |
| * never set up a suitable environment. Abort the build |
| * unless the calculated number of repetitions is a |
| * compile-time constant. |
| */ |
| linker_assert ( __builtin_constant_p ( cutoff ), |
| repetition_count_cutoff_not_constant ); |
| |
| return cutoff; |
| } |
| |
| /** |
| * Perform repetition count test |
| * |
| * @v sample Noise sample |
| * @ret rc Return status code |
| * |
| * This is the Repetition Count Test defined in ANS X9.82 Part 2 |
| * (October 2011 Draft) Section 8.5.2.1.2. |
| */ |
| static int repetition_count_test ( noise_sample_t sample ) { |
| static noise_sample_t most_recent_sample; |
| static unsigned int repetition_count = 0; |
| |
| /* A = the most recently seen sample value |
| * B = the number of times that value A has been seen in a row |
| * C = the cutoff value above which the repetition test should fail |
| */ |
| |
| /* 1. For each new sample processed: |
| * |
| * (Note that the test for "repetition_count > 0" ensures that |
| * the initial value of most_recent_sample is treated as being |
| * undefined.) |
| */ |
| if ( ( sample == most_recent_sample ) && ( repetition_count > 0 ) ) { |
| |
| /* a) If the new sample = A, then B is incremented by one. */ |
| repetition_count++; |
| |
| /* i. If B >= C, then an error condition is raised |
| * due to a failure of the test |
| */ |
| if ( repetition_count >= repetition_count_cutoff() ) |
| return -EPIPE_REPETITION_COUNT_TEST; |
| |
| } else { |
| |
| /* b) Else: |
| * i. A = new sample |
| */ |
| most_recent_sample = sample; |
| |
| /* ii. B = 1 */ |
| repetition_count = 1; |
| } |
| |
| return 0; |
| } |
| |
| /** |
| * Window size for the adaptive proportion test |
| * |
| * ANS X9.82 Part 2 (October 2011 Draft) Section 8.5.2.1.3.1.1 allows |
| * five possible window sizes: 16, 64, 256, 4096 and 65536. |
| * |
| * We expect to generate relatively few (<256) entropy samples during |
| * a typical iPXE run; the use of a large window size would mean that |
| * the test would never complete a single cycle. We use a window size |
| * of 64, which is the smallest window size that permits values of |
| * H_min down to one bit per sample. |
| */ |
| #define ADAPTIVE_PROPORTION_WINDOW_SIZE 64 |
| |
| /** |
| * Combine adaptive proportion test window size and min-entropy |
| * |
| * @v n N (window size) |
| * @v h H (min-entropy) |
| * @ret n_h (N,H) combined value |
| */ |
| #define APC_N_H( n, h ) ( ( (n) << 8 ) | (h) ) |
| |
| /** |
| * Define a row of the adaptive proportion cutoff table |
| * |
| * @v h H (min-entropy) |
| * @v c16 Cutoff for N=16 |
| * @v c64 Cutoff for N=64 |
| * @v c256 Cutoff for N=256 |
| * @v c4096 Cutoff for N=4096 |
| * @v c65536 Cutoff for N=65536 |
| */ |
| #define APC_TABLE_ROW( h, c16, c64, c256, c4096, c65536) \ |
| case APC_N_H ( 16, h ) : return c16; \ |
| case APC_N_H ( 64, h ) : return c64; \ |
| case APC_N_H ( 256, h ) : return c256; \ |
| case APC_N_H ( 4096, h ) : return c4096; \ |
| case APC_N_H ( 65536, h ) : return c65536; |
| |
| /** Value used to represent "N/A" in adaptive proportion cutoff table */ |
| #define APC_NA 0 |
| |
| /** |
| * Look up value in adaptive proportion test cutoff table |
| * |
| * @v n N (window size) |
| * @v h H (min-entropy) |
| * @ret cutoff Cutoff |
| * |
| * This is the table of cutoff values defined in ANS X9.82 Part 2 |
| * (October 2011 Draft) Section 8.5.2.1.3.1.2. |
| */ |
| static inline __attribute__ (( always_inline )) unsigned int |
| adaptive_proportion_cutoff_lookup ( unsigned int n, unsigned int h ) { |
| switch ( APC_N_H ( n, h ) ) { |
| APC_TABLE_ROW ( 1, APC_NA, 51, 168, 2240, 33537 ); |
| APC_TABLE_ROW ( 2, APC_NA, 35, 100, 1193, 17053 ); |
| APC_TABLE_ROW ( 3, 10, 24, 61, 643, 8705 ); |
| APC_TABLE_ROW ( 4, 8, 16, 38, 354, 4473 ); |
| APC_TABLE_ROW ( 5, 6, 12, 25, 200, 2321 ); |
| APC_TABLE_ROW ( 6, 5, 9, 17, 117, 1220 ); |
| APC_TABLE_ROW ( 7, 4, 7, 15, 71, 653 ); |
| APC_TABLE_ROW ( 8, 4, 5, 9, 45, 358 ); |
| APC_TABLE_ROW ( 9, 3, 4, 7, 30, 202 ); |
| APC_TABLE_ROW ( 10, 3, 4, 5, 21, 118 ); |
| APC_TABLE_ROW ( 11, 2, 3, 4, 15, 71 ); |
| APC_TABLE_ROW ( 12, 2, 3, 4, 11, 45 ); |
| APC_TABLE_ROW ( 13, 2, 2, 3, 9, 30 ); |
| APC_TABLE_ROW ( 14, 2, 2, 3, 7, 21 ); |
| APC_TABLE_ROW ( 15, 1, 2, 2, 6, 15 ); |
| APC_TABLE_ROW ( 16, 1, 2, 2, 5, 11 ); |
| APC_TABLE_ROW ( 17, 1, 1, 2, 4, 9 ); |
| APC_TABLE_ROW ( 18, 1, 1, 2, 4, 7 ); |
| APC_TABLE_ROW ( 19, 1, 1, 1, 3, 6 ); |
| APC_TABLE_ROW ( 20, 1, 1, 1, 3, 5 ); |
| default: |
| return APC_NA; |
| } |
| } |
| |
| /** |
| * Calculate cutoff value for the adaptive proportion test |
| * |
| * @ret cutoff Cutoff value |
| * |
| * This is the cutoff value for the Adaptive Proportion Test defined |
| * in ANS X9.82 Part 2 (October 2011 Draft) Section 8.5.2.1.3.1.2. |
| */ |
| static inline __attribute__ (( always_inline )) unsigned int |
| adaptive_proportion_cutoff ( void ) { |
| unsigned int h; |
| unsigned int n; |
| unsigned int cutoff; |
| |
| /* Look up cutoff value in cutoff table */ |
| n = ADAPTIVE_PROPORTION_WINDOW_SIZE; |
| h = ( min_entropy_per_sample() / MIN_ENTROPY_SCALE ); |
| cutoff = adaptive_proportion_cutoff_lookup ( n, h ); |
| |
| /* Fail unless cutoff value is a build-time constant */ |
| linker_assert ( __builtin_constant_p ( cutoff ), |
| adaptive_proportion_cutoff_not_constant ); |
| |
| /* Fail if cutoff value is N/A */ |
| linker_assert ( ( cutoff != APC_NA ), |
| adaptive_proportion_cutoff_not_applicable ); |
| |
| return cutoff; |
| } |
| |
| /** |
| * Perform adaptive proportion test |
| * |
| * @v sample Noise sample |
| * @ret rc Return status code |
| * |
| * This is the Adaptive Proportion Test for the Most Common Value |
| * defined in ANS X9.82 Part 2 (October 2011 Draft) Section 8.5.2.1.3. |
| */ |
| static int adaptive_proportion_test ( noise_sample_t sample ) { |
| static noise_sample_t current_counted_sample; |
| static unsigned int sample_count = ADAPTIVE_PROPORTION_WINDOW_SIZE; |
| static unsigned int repetition_count; |
| |
| /* A = the sample value currently being counted |
| * B = the number of samples examined in this run of the test so far |
| * N = the total number of samples that must be observed in |
| * one run of the test, also known as the "window size" of |
| * the test |
| * B = the current number of times that S (sic) has been seen |
| * in the W (sic) samples examined so far |
| * C = the cutoff value above which the repetition test should fail |
| * W = the probability of a false positive: 2^-30 |
| */ |
| |
| /* 1. The entropy source draws the current sample from the |
| * noise source. |
| * |
| * (Nothing to do; we already have the current sample.) |
| */ |
| |
| /* 2. If S = N, then a new run of the test begins: */ |
| if ( sample_count == ADAPTIVE_PROPORTION_WINDOW_SIZE ) { |
| |
| /* a. A = the current sample */ |
| current_counted_sample = sample; |
| |
| /* b. S = 0 */ |
| sample_count = 0; |
| |
| /* c. B = 0 */ |
| repetition_count = 0; |
| |
| } else { |
| |
| /* Else: (the test is already running) |
| * a. S = S + 1 |
| */ |
| sample_count++; |
| |
| /* b. If A = the current sample, then: */ |
| if ( sample == current_counted_sample ) { |
| |
| /* i. B = B + 1 */ |
| repetition_count++; |
| |
| /* ii. If S (sic) > C then raise an error |
| * condition, because the test has |
| * detected a failure |
| */ |
| if ( repetition_count > adaptive_proportion_cutoff() ) |
| return -EPIPE_ADAPTIVE_PROPORTION_TEST; |
| |
| } |
| } |
| |
| return 0; |
| } |
| |
| /** |
| * Get entropy sample |
| * |
| * @ret entropy Entropy sample |
| * @ret rc Return status code |
| * |
| * This is the GetEntropy function defined in ANS X9.82 Part 2 |
| * (October 2011 Draft) Section 6.5.1. |
| */ |
| static int get_entropy ( entropy_sample_t *entropy ) { |
| static int rc = 0; |
| noise_sample_t noise; |
| |
| /* Any failure is permanent */ |
| if ( rc != 0 ) |
| return rc; |
| |
| /* Get noise sample */ |
| if ( ( rc = get_noise ( &noise ) ) != 0 ) |
| return rc; |
| |
| /* Perform Repetition Count Test and Adaptive Proportion Test |
| * as mandated by ANS X9.82 Part 2 (October 2011 Draft) |
| * Section 8.5.2.1.1. |
| */ |
| if ( ( rc = repetition_count_test ( noise ) ) != 0 ) |
| return rc; |
| if ( ( rc = adaptive_proportion_test ( noise ) ) != 0 ) |
| return rc; |
| |
| /* We do not use any optional conditioning component */ |
| *entropy = noise; |
| |
| return 0; |
| } |
| |
| /** |
| * Calculate number of samples required for startup tests |
| * |
| * @ret num_samples Number of samples required |
| * |
| * ANS X9.82 Part 2 (October 2011 Draft) Section 8.5.2.1.5 requires |
| * that at least one full cycle of the continuous tests must be |
| * performed at start-up. |
| */ |
| static inline __attribute__ (( always_inline )) unsigned int |
| startup_test_count ( void ) { |
| unsigned int num_samples; |
| |
| /* At least max(N,C) samples shall be generated by the noise |
| * source for start-up testing. |
| */ |
| num_samples = repetition_count_cutoff(); |
| if ( num_samples < adaptive_proportion_cutoff() ) |
| num_samples = adaptive_proportion_cutoff(); |
| linker_assert ( __builtin_constant_p ( num_samples ), |
| startup_test_count_not_constant ); |
| |
| return num_samples; |
| } |
| |
| /** |
| * Create next nonce value |
| * |
| * @ret nonce Nonce |
| * |
| * This is the MakeNextNonce function defined in ANS X9.82 Part 4 |
| * (April 2011 Draft) Section 13.3.4.2. |
| */ |
| static uint32_t make_next_nonce ( void ) { |
| static uint32_t nonce; |
| |
| /* The simplest implementation of a nonce uses a large counter */ |
| nonce++; |
| |
| return nonce; |
| } |
| |
| /** |
| * Obtain entropy input temporary buffer |
| * |
| * @v num_samples Number of entropy samples |
| * @v tmp Temporary buffer |
| * @v tmp_len Length of temporary buffer |
| * @ret rc Return status code |
| * |
| * This is (part of) the implementation of the Get_entropy_input |
| * function (using an entropy source as the source of entropy input |
| * and condensing each entropy source output after each GetEntropy |
| * call) as defined in ANS X9.82 Part 4 (April 2011 Draft) Section |
| * 13.3.4.2. |
| * |
| * To minimise code size, the number of samples required is calculated |
| * at compilation time. |
| */ |
| int get_entropy_input_tmp ( unsigned int num_samples, uint8_t *tmp, |
| size_t tmp_len ) { |
| static unsigned int startup_tested = 0; |
| struct { |
| uint32_t nonce; |
| entropy_sample_t sample; |
| } __attribute__ (( packed )) data;; |
| uint8_t df_buf[tmp_len]; |
| unsigned int i; |
| int rc; |
| |
| /* Enable entropy gathering */ |
| if ( ( rc = entropy_enable() ) != 0 ) |
| return rc; |
| |
| /* Perform mandatory startup tests, if not yet performed */ |
| for ( ; startup_tested < startup_test_count() ; startup_tested++ ) { |
| if ( ( rc = get_entropy ( &data.sample ) ) != 0 ) |
| goto err_get_entropy; |
| } |
| |
| /* 3. entropy_total = 0 |
| * |
| * (Nothing to do; the number of entropy samples required has |
| * already been precalculated.) |
| */ |
| |
| /* 4. tmp = a fixed n-bit value, such as 0^n */ |
| memset ( tmp, 0, tmp_len ); |
| |
| /* 5. While ( entropy_total < min_entropy ) */ |
| while ( num_samples-- ) { |
| /* 5.1. ( status, entropy_bitstring, assessed_entropy ) |
| * = GetEntropy() |
| * 5.2. If status indicates an error, return ( status, Null ) |
| */ |
| if ( ( rc = get_entropy ( &data.sample ) ) != 0 ) |
| goto err_get_entropy; |
| |
| /* 5.3. nonce = MakeNextNonce() */ |
| data.nonce = make_next_nonce(); |
| |
| /* 5.4. tmp = tmp XOR |
| * df ( ( nonce || entropy_bitstring ), n ) |
| */ |
| hash_df ( &entropy_hash_df_algorithm, &data, sizeof ( data ), |
| df_buf, sizeof ( df_buf ) ); |
| for ( i = 0 ; i < tmp_len ; i++ ) |
| tmp[i] ^= df_buf[i]; |
| |
| /* 5.5. entropy_total = entropy_total + assessed_entropy |
| * |
| * (Nothing to do; the number of entropy samples |
| * required has already been precalculated.) |
| */ |
| } |
| |
| /* Disable entropy gathering */ |
| entropy_disable(); |
| |
| return 0; |
| |
| err_get_entropy: |
| entropy_disable(); |
| return rc; |
| } |