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#include "ndpi_api.h"
#include "fuzz_common_code.h"
#include <stdint.h>
#include <stdio.h>
#include "fuzzer/FuzzedDataProvider.h"
extern "C" int LLVMFuzzerTestOneInput(const uint8_t *data, size_t size) {
FuzzedDataProvider fuzzed_data(data, size);
u_int16_t i, num_values, num_learning_values, max_series_len;
struct ndpi_hw_struct hw;
struct ndpi_rsi_struct rsi;
struct ndpi_analyze_struct *a;
int rc_hw, rc_rsi;
u_int16_t num_periods;
u_int8_t additive_seeasonal;
double alpha, beta, gamma, forecast, confidence_band;
float significance;
u_int32_t *values;
bool *outliers;
/* Use the same (integral) dataset to peform: RSI, Data analysis, HW and outliers */
/* Just to have some data */
if(fuzzed_data.remaining_bytes() < 1024)
return -1;
/* To allow memory allocation failures */
fuzz_set_alloc_callbacks_and_seed(size);
/* Data set */
num_values = fuzzed_data.ConsumeIntegral<u_int8_t>();
values = (u_int32_t *)ndpi_malloc(sizeof(u_int32_t) * num_values);
outliers = (bool *)ndpi_malloc(sizeof(bool) * num_values);
if (!values || !outliers) {
ndpi_free(values);
ndpi_free(outliers);
return -1;
}
for (i = 0; i < num_values; i++)
values[i] = fuzzed_data.ConsumeIntegral<u_int32_t>();
/* Init HW */
num_periods = fuzzed_data.ConsumeIntegral<u_int8_t>();
additive_seeasonal = fuzzed_data.ConsumeBool();
alpha = fuzzed_data.ConsumeFloatingPointInRange<double>(0, 1);
beta = fuzzed_data.ConsumeFloatingPointInRange<double>(0, 1);
gamma = fuzzed_data.ConsumeFloatingPointInRange<double>(0, 1);
significance = fuzzed_data.ConsumeFloatingPointInRange<float>(0, 1.1);
rc_hw = ndpi_hw_init(&hw, num_periods, additive_seeasonal,
alpha, beta, gamma, significance);
/* Init RSI */
num_learning_values = fuzzed_data.ConsumeIntegral<u_int8_t>();
rc_rsi = ndpi_alloc_rsi(&rsi, num_learning_values);
/* Init Data Analysis */
max_series_len = fuzzed_data.ConsumeIntegral<u_int16_t>();
a = ndpi_alloc_data_analysis(max_series_len);
/* Calculate! */
for (i = 0; i < num_values; i++) {
if (rc_hw == 0)
ndpi_hw_add_value(&hw, values[i], &forecast, &confidence_band);
if (rc_rsi == 0)
ndpi_rsi_add_value(&rsi, values[i]);
ndpi_data_add_value(a, values[i]);
}
ndpi_find_outliers(values, outliers, num_values);
/* Data analysis stuff */
ndpi_data_average(a);
ndpi_data_mean(a);
ndpi_data_variance(a);
ndpi_data_stddev(a);
ndpi_data_min(a);
ndpi_data_max(a);
ndpi_data_window_average(a);
ndpi_data_window_variance(a);
ndpi_data_window_stddev(a);
ndpi_data_entropy(a);
ndpi_reset_data_analysis(a);
ndpi_data_last(a);
/* Data ratio */
if (num_values > 1)
ndpi_data_ratio2str(ndpi_data_ratio(values[0], values[1]));
/* Done. Free */
if (rc_hw == 0)
ndpi_hw_free(&hw);
if (rc_rsi == 0)
ndpi_free_rsi(&rsi);
ndpi_free_data_analysis(a, 1);
ndpi_free(values);
ndpi_free(outliers);
return 0;
}
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