/*
* 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;
}
