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#!/usr/bin/env python
# encoding: utf-8
'''
Example Python Module for AFLFuzz
@author: Christian Holler (:decoder)
@license:
This Source Code Form is subject to the terms of the Mozilla Public
License, v. 2.0. If a copy of the MPL was not distributed with this
file, You can obtain one at http://mozilla.org/MPL/2.0/.
@contact: choller@mozilla.com
'''
import random
def init(seed):
'''
Called once when AFLFuzz starts up. Used to seed our RNG.
@type seed: int
@param seed: A 32-bit random value
'''
random.seed(seed)
return 0
def fuzz(buf, add_buf):
'''
Called per fuzzing iteration.
@type buf: bytearray
@param buf: The buffer that should be mutated.
@type add_buf: bytearray
@param add_buf: A second buffer that can be used as mutation source.
@rtype: bytearray
@return: A new bytearray containing the mutated data
'''
ret = bytearray(buf)
# Do something interesting with ret
return ret
# Uncomment and implement the following methods if you want to use a custom
# trimming algorithm. See also the documentation for a better API description.
# def init_trim(buf):
# '''
# Called per trimming iteration.
#
# @type buf: bytearray
# @param buf: The buffer that should be trimmed.
#
# @rtype: int
# @return: The maximum number of trimming steps.
# '''
# global ...
#
# # Initialize global variables
#
# # Figure out how many trimming steps are possible.
# # If this is not possible for your trimming, you can
# # return 1 instead and always return 0 in post_trim
# # until you are done (then you return 1).
#
# return steps
#
# def trim():
# '''
# Called per trimming iteration.
#
# @rtype: bytearray
# @return: A new bytearray containing the trimmed data.
# '''
# global ...
#
# # Implement the actual trimming here
#
# return bytearray(...)
#
# def post_trim(success):
# '''
# Called after each trimming operation.
#
# @type success: bool
# @param success: Indicates if the last trim operation was successful.
#
# @rtype: int
# @return: The next trim index (0 to max number of steps) where max
# number of steps indicates the trimming is done.
# '''
# global ...
#
# if not success:
# # Restore last known successful input, determine next index
# else:
# # Just determine the next index, based on what was successfully
# # removed in the last step
#
# return next_index
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