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-=========================================================
-Unicorn-based binary-only instrumentation for afl-fuzz
-=========================================================
-
-1) Introduction
----------------
-
-The code in ./unicorn_mode allows you to build a standalone feature that
-leverages the Unicorn Engine and allows callers to obtain instrumentation 
-output for black-box, closed-source binary code snippets. This mechanism 
-can be then used by afl-fuzz to stress-test targets that couldn't be built 
-with afl-gcc or used in QEMU mode, or with other extensions such as 
-TriforceAFL.
-
-There is a significant performance penalty compared to native AFL,
-but at least we're able to use AFL on these binaries, right?
-
-The idea and much of the implementation comes from Nathan Voss <njvoss299@gmail.com>.
-
-2) How to use
--------------
-
-Requirements: you need an installed python2 environment.
-
-*** Building AFL's Unicorn Mode ***
-
-First, make afl as usual.
-Once that completes successfully you need to build and add in the Unicorn Mode 
-features:
-
-  $ cd unicorn_mode
-  $ ./build_unicorn_support.sh
-
-NOTE: This script downloads a recent Unicorn Engine commit that has been tested 
-and is stable-ish from the Unicorn github page. If you are offline, you'll need 
-to hack up this script a little bit and supply your own copy of Unicorn's latest 
-stable release. It's not very hard, just check out the beginning of the 
-build_unicorn_support.sh script and adjust as necessary.
-
-Building Unicorn will take a little bit (~5-10 minutes). Once it completes 
-it automatically compiles a sample application and verify that it works.
-
-*** Fuzzing with Unicorn Mode ***
-
-To really use unicorn-mode effectively you need to prepare the following:
-
-	* Relevant binary code to be fuzzed
-	* Knowledge of the memory map and good starting state
-	* Folder containing sample inputs to start fuzzing with
-		- Same ideas as any other AFL inputs
-		- Quality/speed of results will depend greatly on quality of starting 
-		  samples
-		- See AFL's guidance on how to create a sample corpus
-	* Unicorn-based test harness which:
-		- Adds memory map regions
-		- Loads binary code into memory		
-		- Emulates at least one instruction*
-			- Yeah, this is lame. See 'Gotchas' section below for more info		
-		- Loads and verifies data to fuzz from a command-line specified file
-			- AFL will provide mutated inputs by changing the file passed to 
-			  the test harness
-			- Presumably the data to be fuzzed is at a fixed buffer address
-			- If input constraints (size, invalid bytes, etc.) are known they 
-			  should be checked after the file is loaded. If a constraint 
-			  fails, just exit the test harness. AFL will treat the input as 
-			  'uninteresting' and move on.
-		- Sets up registers and memory state for beginning of test
-		- Emulates the interested code from beginning to end
-		- If a crash is detected, the test harness must 'crash' by 
-		  throwing a signal (SIGSEGV, SIGKILL, SIGABORT, etc.)
-
-Once you have all those things ready to go you just need to run afl-fuzz in
-'unicorn-mode' by passing in the '-U' flag:
-
-	$ afl-fuzz -U -m none -i /path/to/inputs -o /path/to/results -- ./test_harness @@
-
-The normal afl-fuzz command line format applies to everything here. Refer to
-AFL's main documentation for more info about how to use afl-fuzz effectively.
-
-For a much clearer vision of what all of this looks like, please refer to the
-sample provided in the 'unicorn_mode/samples' directory. There is also a blog
-post that goes over the basics at:
-
-https://medium.com/@njvoss299/afl-unicorn-fuzzing-arbitrary-binary-code-563ca28936bf
-
-The 'helper_scripts' directory also contains several helper scripts that allow you 
-to dump context from a running process, load it, and hook heap allocations. For details
-on how to use this check out the follow-up blog post to the one linked above.
-
-A example use of AFL-Unicorn mode is discussed in the Paper Unicorefuzz:
-https://www.usenix.org/conference/woot19/presentation/maier
-
-3) Gotchas, feedback, bugs
---------------------------
-
-To make sure that AFL's fork server starts up correctly the Unicorn test 
-harness script must emulate at least one instruction before loading the
-data that will be fuzzed from the input file. It doesn't matter what the
-instruction is, nor if it is valid. This is an artifact of how the fork-server
-is started and could likely be fixed with some clever re-arranging of the
-patches applied to Unicorn.
-
-Running the build script builds Unicorn and its python bindings and installs 
-them on your system. This installation will supersede any existing Unicorn
-installation with the patched afl-unicorn version.
-
-Refer to the unicorn_mode/samples/arm_example/arm_tester.c for an example
-of how to do this properly! If you don't get this right, AFL will not 
-load any mutated inputs and your fuzzing will be useless!