|  | /* | 
|  | * 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; | 
|  | } |