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+# Best practices
+
+## Contents
+
+### Targets
+
+  * [Fuzzing a binary-only target](#fuzzing-a-binary-only-target)
+  * [Fuzzing a GUI program](#fuzzing-a-gui-program)
+  * [Fuzzing a network service](#fuzzing-a-network-service)
+
+### Improvements
+
+  * [Improving speed](#improving-speed)
+  * [Improving stability](#improving-stability)
+
+## Targets
+
+### Fuzzing a binary-only target
+
+For a comprehensive guide, see [binaryonly_fuzzing.md](binaryonly_fuzzing.md).
+
+### Fuzzing a GUI program
+
+If the GUI program can read the fuzz data from a file (via the command line, a fixed location or via an environment variable) without needing any user interaction, then it would be suitable for fuzzing.
+
+Otherwise, it is not possible without modifying the source code - which is a very good idea anyway as the GUI functionality is a huge CPU/time overhead for the fuzzing.
+
+So create a new `main()` that just reads the test case and calls the functionality for processing the input that the GUI program is using.
+
+### Fuzzing a network service
+
+Fuzzing a network service does not work "out of the box".
+
+Using a network channel is inadequate for several reasons:
+- it has a slow-down of x10-20 on the fuzzing speed
+- it does not scale to fuzzing multiple instances easily,
+- instead of one initial data packet often a back-and-forth interplay of packets is needed for stateful protocols (which is totally unsupported by most coverage aware fuzzers).
+
+The established method to fuzz network services is to modify the source code
+to read from a file or stdin (fd 0) (or even faster via shared memory, combine
+this with persistent mode [instrumentation/README.persistent_mode.md](../instrumentation/README.persistent_mode.md)
+and you have a performance gain of x10 instead of a performance loss of over
+x10 - that is a x100 difference!).
+
+If modifying the source is not an option (e.g. because you only have a binary
+and perform binary fuzzing) you can also use a shared library with AFL_PRELOAD
+to emulate the network. This is also much faster than the real network would be.
+See [utils/socket_fuzzing/](../utils/socket_fuzzing/).
+
+There is an outdated AFL++ branch that implements networking if you are
+desperate though: [https://github.com/AFLplusplus/AFLplusplus/tree/networking](https://github.com/AFLplusplus/AFLplusplus/tree/networking) - 
+however a better option is AFLnet ([https://github.com/aflnet/aflnet](https://github.com/aflnet/aflnet))
+which allows you to define network state with different type of data packets.
+
+## Improvements
+
+### Improving speed
+
+1. Use [llvm_mode](../instrumentation/README.llvm.md): afl-clang-lto (llvm >= 11) or afl-clang-fast (llvm >= 9 recommended).
+2. Use [persistent mode](../instrumentation/README.persistent_mode.md) (x2-x20 speed increase).
+3. Use the [AFL++ snapshot module](https://github.com/AFLplusplus/AFL-Snapshot-LKM) (x2 speed increase).
+4. If you do not use shmem persistent mode, use `AFL_TMPDIR` to put the input file directory on a tempfs location, see [docs/env_variables.md](docs/env_variables.md).
+5. Improve Linux kernel performance: modify `/etc/default/grub`, set `GRUB_CMDLINE_LINUX_DEFAULT="ibpb=off ibrs=off kpti=off l1tf=off mds=off mitigations=off no_stf_barrier noibpb noibrs nopcid nopti nospec_store_bypass_disable nospectre_v1 nospectre_v2 pcid=off pti=off spec_store_bypass_disable=off spectre_v2=off stf_barrier=off"`; then `update-grub` and `reboot` (warning: makes the system less secure).
+6. Running on an `ext2` filesystem with `noatime` mount option will be a bit faster than on any other journaling filesystem.
+7. Use your cores! [README.md:3.b) Using multiple cores/threads](../README.md#b-using-multiple-coresthreads).
+
+### Improving stability
+
+For fuzzing a 100% stable target that covers all edges is the best case.
+A 90% stable target that covers all edges is however better than a 100% stable target that ignores 10% of the edges.
+
+With instability, you basically have a partial coverage loss on an edge, with ignored functions you have a full loss on that edges.
+
+There are functions that are unstable, but also provide value to coverage, e.g., init functions that use fuzz data as input.
+If however a function that has nothing to do with the input data is the source of instability, e.g., checking jitter, or is a hash map function etc., then it should not be instrumented.
+
+To be able to exclude these functions (based on AFL++'s measured stability), the following process will allow to identify functions with variable edges.
+
+Four steps are required to do this and it also requires quite some knowledge of coding and/or disassembly and is effectively possible only with `afl-clang-fast` `PCGUARD` and `afl-clang-lto` `LTO` instrumentation.
+
+  1. Instrument to be able to find the responsible function(s):
+
+     a) For LTO instrumented binaries, this can be documented during compile time, just set `export AFL_LLVM_DOCUMENT_IDS=/path/to/a/file`.
+        This file will have one assigned edge ID and the corresponding function per line.
+
+     b) For PCGUARD instrumented binaries, it is much more difficult. Here you can either modify the `__sanitizer_cov_trace_pc_guard` function in `instrumentation/afl-llvm-rt.o.c` to write a backtrace to a file if the ID in `__afl_area_ptr[*guard]` is one of the unstable edge IDs.
+        (Example code is already there).
+        Then recompile and reinstall `llvm_mode` and rebuild your target.
+        Run the recompiled target with `afl-fuzz` for a while and then check the file that you wrote with the backtrace information.
+        Alternatively, you can use `gdb` to hook `__sanitizer_cov_trace_pc_guard_init` on start, check to which memory address the edge ID value is written, and set a write breakpoint to that address (`watch 0x.....`).
+
+     c) In other instrumentation types, this is not possible.
+        So just recompile with the two mentioned above.
+        This is just for identifying the functions that have unstable edges.
+
+  2. Identify which edge ID numbers are unstable.
+
+     Run the target with `export AFL_DEBUG=1` for a few minutes then terminate.
+     The out/fuzzer_stats file will then show the edge IDs that were identified
+     as unstable in the `var_bytes` entry. You can match these numbers
+     directly to the data you created in the first step.
+     Now you know which functions are responsible for the instability
+
+  3. Create a text file with the filenames/functions
+
+     Identify which source code files contain the functions that you need to remove from instrumentation, or just specify the functions you want to skip for instrumentation.
+     Note that optimization might inline functions!
+
+     Follow this document on how to do this: [instrumentation/README.instrument_list.md](../instrumentation/README.instrument_list.md).
+     If `PCGUARD` is used, then you need to follow this guide (needs llvm 12+!):
+     [http://clang.llvm.org/docs/SanitizerCoverage.html#partially-disabling-instrumentation](http://clang.llvm.org/docs/SanitizerCoverage.html#partially-disabling-instrumentation)
+
+     Only exclude those functions from instrumentation that provide no value for coverage - that is if it does not process any fuzz data directly or indirectly (e.g. hash maps, thread management etc.).
+     If however a function directly or indirectly handles fuzz data, then you should not put the function in a deny instrumentation list and rather live with the instability it comes with.
+
+  4. Recompile the target
+
+     Recompile, fuzz it, be happy :)
+
+     This link explains this process for [Fuzzbench](https://github.com/google/fuzzbench/issues/677).
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