# afl-utils [![pipeline status](https://gitlab.com/rc0r/afl-utils/badges/master/pipeline.svg)](https://gitlab.com/rc0r/afl-utils/commits/master)[![coverage report](https://gitlab.com/rc0r/afl-utils/badges/master/coverage.svg)](https://gitlab.com/rc0r/afl-utils/commits/master)

afl-utils is a collection of utilities to assist fuzzing with
[american-fuzzy-lop (afl)](http://lcamtuf.coredump.cx/afl/).
afl-utils includes tools for:

* automated crash sample collection, verification, reduction and analysis (`afl-collect`, `afl-vcrash`)
* easy management of parallel (multi-core) fuzzing jobs (`afl-multicore`, `afl-multikill`)
* corpus optimization (`afl-minimize`)
* fuzzer stats supervision (`afl-stats`)
* fuzzer queue synchronisation (`afl-sync`)
* autonomous utility execution (`afl-cron`)

Various [screenshots](#screenshots) of the tools in action can be found at the end of this file.

**For installation instructions see [docs/INSTALL.md](https://gitlab.com/rc0r/afl-utils/blob/master/docs/INSTALL.md).**


## afl-collect

`afl-collect` basically copies all crash sample files from an afl synchronisation directory
(used by multiple afl instances when run in parallel) into a single location providing
easy access for further crash analysis. Beyond that `afl-collect` has some more advanced
features like invalid crash sample removing (see `afl-vcrash`) as well as generating and
executing `gdb` scripts that make use of [Exploitable](https://github.com/jfoote/exploitable).
The purpose of these scripts is to automate crash sample classification (see screenshot below)
and reduction.  
Version 1.01a introduced crash sample de-duplication using backtrace hashes calculated by
exploitable. To use this feature invoke `afl-collect` with `-e <gdb_script>` switch for
automatic gdb+exploitable script generation and execution. For each backtrace hash only a
single crash sample file will be kept.  
`afl-collect` is quite slow when operating on large sample sets and using gdb+exploitable
script execution, so be patient!  
When invoked with `-d <database>`, sample information will be stored in the `database`. This
will only be done when the gdb-script execution step is selected (`-e`). If `database` is an
existing database containing sample info, `afl-collect` will skip all samples that already
have a database entry during sample processing. This will work also when `-e` is not requested.
This makes subsequent `afl-collect` runs more efficient, since only unseen samples are
processed (and added to the database).  

Usage examples:

Simply collect all crashes from `./afl_sync_dir` into a collection directory removing
non-crashing samples:

    $ afl-collect -r ./afl_sync_dir ./collection_dir -- /path/to/target --target-opts

Collect crashes, execute `exploitable` on them and remove uninteresting crashes. Info
for all processed samples will be stored in an SQLite DB. The `gdb` script used to run
`exploitable` on all samples will be saved in `gdb_script`. We're using eight threads
here:

    $ afl-collect -d crashes.db -e gdb_script -r -rr ./afl_sync_dir ./collection_dir \
            -j 8 -- /path/to/target --target-opts

During sample verification (enabled using `-r`) `afl-collect` uses a default time of
10 seconds to allow the target process to finish processing a single sample. This ensures
that `afl-collect` continues to run even if you happen to encounter some DoS condition
in the target. If you want to tweak this value use `-r` in conjunction with
`-rt <timeout>` to specify the timeout in seconds.

## afl-cron

The purpose of `afl-cron` is to run different `afl-utils` tasks periodically. Example
use cases include grabbing `afl-stats` or syncing fuzzing queues using `afl-sync`
repeatedly. `afl-cron` is not limited to run top-level tools from the `afl-utils`
collection. For a much finer granularity you may specify an arbitrary function from
any `afl-utils` module to be executed once the timer runs out.

Running `afl-cron` with the following configuration will execute `afl-stats.main()`
every 60 minutes in quiet mode using the provided sample config:

```json
{
    "interval": 60,
    "jobs": [
        {
            "name": "afl-stats",
            "description": "Job description here",
            "module": "afl_utils.afl_stats",
            "function": "main",
            "params": "--quiet -c config/afl-stats.conf.sample"
        }
    ]
}
```

You may have multiple job definitions in your configuration. Once the interval timer is up,
all jobs are executed sequentially.


## afl-minimize

Helps to create a minimized corpus from samples of a parallel fuzzing job. It
basically works as follows:

1. Collect all queue samples from an afl synchronisation directory in `collection_dir`.
2. Run `afl-cmin` on the collected corpus, save minimized corpus in `collection_dir.cmin`.
3. Run `afl-tmin` on the remaining samples to reduce them in size. Save results in
   `collection_dir.tmin` if step two was omitted or `collection_dir.cmin.tmin` otherwise.
4. Perform a "dry-run" for each sample and move crashes/timeouts out of the corpus. This
   step will be useful prior to starting a new or resuming a parallel fuzzing job on a
   corpus containing intermittent crashes. Crashes will be moved to a `.crashes` directory,
   if one of steps 1, 2 or 3 were performed. If only "dry-run" is requested, crashing
   samples will be moved from the `queue` to the `crashes` dirs within an afl sync dir.
   For timeouts the behavior is similar: When operating on a collection directory timeouts
   will be moved to a `.hangs` directory. When operating on the original afl synchronisation
   directory timeouts will go into `hangs` dir within the corresponding afl fuzzer dir.  
   
As already indicated, all these steps are optional, making the tool quite flexible. E.g.
running only step four can be handy before resuming a parallel fuzzing session. In order
to skip step one, simply provide a directory containing fuzzing samples. Then `afl-minimize`
will not collect any samples, instead `afl-cmin` and/or `afl-tmin` are run on the samples
in the provided directory.  

When operating on corpora with many samples use `--tmin` with caution. Running thousands
of files through `afl-tmin` can take very long. So make sure the results are as expected
and worth the effort. You don't want to waste days of CPU time just to reduce your corpus
size by a few bytes, don't you?!

Performing the "dry-run" step after running `afl-cmin` might seem pointless, but my
experience showed that sometimes crashes remain in the minimized corpus. So this is just
an additional step to get rid of them. But don't expect "dry-run" to always clear your
corpus from crashes with a 100% success rate!

Brandon Perry described a common fuzzing workflow in his
[blog post](http://foxglovesecurity.com/2016/03/15/fuzzing-workflows-a-fuzz-job-from-start-to-finish/).
It incorporates corpus pruning and reseeding `afl-fuzz` with optimized corpora. The
collection and minimization steps taken in `afl-minimize` automate the pruning process
of the presented workflow. To feed the minimized, pruned corpus back into the different
instances of `afl-fuzz` you may use the `--reseed` option that comes with `afl-minimize`.  
This effectively moves the original `queue` directories of all fuzzing instances
out of the way (to `queue.YYYY-MM-DD-HH:MM:SS`). Next, the optimized corpus is copied
into the `queue` dirs of your fuzzing instances.  
After reseeding, all fuzzing instances may be resumed on the same, optimized corpus.
So with `afl-utils` the pruning/reseeding process is just a matter of `afl-multicore`ing,
`afl-multikill`ing and `afl-minimize`ing.

Usage examples:

Minimize the entire corpus of all fuzzers in `./afl_sync_dir` using `afl-cmin` and
`afl-cmin` utilizing eight threads:

    $ afl-minimize -c new_corpus --cmin --cmin-mem-limit=500 --tmin --tmin-mem-limit=500 \
                -j 8 ./afl_sync_dir -- /path/to/target --target-opts

Minimize the entire corpus using `afl-cmin` and reseed the fuzzers:

    $ afl-minimize -c new_corpus --cmin --cmin-mem-limit=500 --reseed ./afl_sync_dir \
                -- /path/to/target --target-opts


## afl-multicore

`afl-multicore` starts several parallel fuzzing jobs in the background using `nohup` (Note:
So afl's fancy interface is gone). Fuzzer outputs (`stdout` and `stderr`) will be redirected
to `/dev/null`. Use `--verbose` to turn output redirection off. This is particularly useful
when debugging `afl-fuzz` invocations. The auto-generated file `nohup.out` might also contain
some useful info.  
Another way to debug `afl-fuzz` invocations is test mode. Just start `afl-multicore` and
provide the `--test` flag to perform a test run. `afl-multicore` will start a single fuzzing
instance in interactive mode using a test output directory `<out-dir>_test`. The `interactive`
setting in your config file will be ignored.  
**Note:** After running a test you will have to clean up the test output directory
`<out-dir>_test` yourself!  
**Note:** For interactive *test runs* `screen` is not required!

If you want to check the fuzzers' progress see `fuzzer_stats` in the respective fuzzer
directory in the synchronisation dir (`sync_dir/SESSION###/fuzzer_stats`)! Another way to monitor
fuzzing progress is to use `afl-stats`. You may also want to check out `afl-stats` database dumping
feature. An `afl-multicore` session can (and should!) easily be aborted with the help of
`afl-multikill` (see below).

If you prefer to work with afl's UI instead of background processes and stat files, screen
mode is for you. "Interactive" screen mode can be enabled using the `interactive` setting
in the config file (see below). In order to use it, start `afl-multicore` from **inside** a
`screen` session. A new screen window is created for every afl instance. Though screen mode is
not supported by `afl-multikill`.  
**Attention:** When using screen mode be sure to set necessary environment variables in your
`afl-multicore` configuration! Alternatively run
`screen -X setenv <var_name> <var_value>` from inside `screen` before running `afl-multicore`.
Both ways the environment is inherited by all subsequently created screen windows.

Usage examples:

    $ afl-multicore -c target-multicore.conf start 16
    $ afl-multicore -c target-multicore.conf add 4
    $ afl-multicore -c target-multicore.conf resume 20

In case you want to resume just a few fuzzers you may use selective resume. Let's say
you've had 20 afl instances running, killed all but the first one (the master instance) and now
you want to resume all slave instances without interrupting master:

    $ afl-multicore -c target-multicore.conf resume number_of_jobs_to_resume,job_offset
    $ afl-multicore -c target-multicore.conf resume 19,1

This `afl-multicore` invocation will resume 19 instances starting at offset 1. Of course other
ranges are possible too. However, when using an offset greater than `master_instances` (description
below) only slave instances will be resumed!

Target settings and afl options are configured in a JSON configuration file.
The most simple configuration may look something like:

```json
{
    "input": "./in",
    "output": "./out",
    "target": "~/bin/target",
    "cmdline": "--target-opt"
}
```

Of course a lot more settings can be configured, some of these settings are:

* afl options: timeout, memory limit, dictionary, CPU affinity, ...
* job options: session name, interactive mode
* environment variables for interactive screen mode

For a complete list of options see `afl-multicore.conf.sample`. Their descriptions
are documented in section `Configuration Settings` below.

To start four fuzzing instances simply do:

    $ afl-multicore -c target.conf start 4

Now, if you want to add two more instances because `afl-gotcpu` states you've
got some spare CPU cycles available, use the `add` command:

    $ afl-multicore -c target.conf add 2

Interrupted fuzzing jobs can be resumed the same way using the `resume` command.  
**Note:** It is possible to *tell* `afl-multicore` to resume more jobs for a
specific target than were previously started. Obviously `afl-multicore` can
resume just as many afl instances as it finds output directories for! Use the
`add` command to start additional afl instances!

`afl-fuzz` can be run using its `-f <file>` argument to specify the location of
the generated sample. When using multiple `afl-fuzz` instances a single file
obviously can't do the trick, because multiple fuzzers running in parallel would
need separate files to store their data. For that reason `afl-multicore` extends
the provided filename with the instance number similar to the session naming
scheme: `cur_input` would be extended into `cur_input_000`, `cur_input_001` and
so on. In order to use these files just use `%%` in the target command line
specification within the config file. `afl-multicore` will then do all the magic
and use the correct files for the different instances of `afl-fuzz`.

Example config:

```json
{
    "target": "/your/app/here",
    "cmdline": "--some-target-opts --input-file %%",
      "#": "^- translates to:",
      "#": "--some-target-opts --input-file /path/to/cur_input_000",
      "#": "--some-target-opts --input-file /path/to/cur_input_001",
      "#": "...",
    "file": "/path/to/cur_input"
}
```

Real life fuzzing experience showed that starting or resuming many afl-fuzz
instances at once can be problematic. Especially during initialization these
fuzzers may heavily interfere with each other causing intermittent afl-fuzz
aborts. In case you are facing such a scenario you might want to give the delayed
startup feature (`-s <delay>` option) a try! Chose the startup delay with caution
depending on your corpus size. For small corpora a few seconds should work well,
for corpora containing tens or hundreds of thousands of files much greater delays
(minutes, hours or even days) are needed to have an effect.  
If you have no clue what to chose or you're simply lazy, try `auto`. This will
estimate a delay based on the chosen afl timeout and the number of samples in the
input dir (for initial start ups) or in the queue dirs of the individual fuzzers
(for resumes).

    $ afl-multicore -c target.conf -s 120 resume 64
    $ afl-multicore -c target.conf -s auto resume 64


### Configuration settings

As already noted there are only four settings that are required in every config
file. These are `afl-fuzz` directory specifications `input` and `output`, the
path to the target binary `target` and target command line arguments `cmdline`:

If you want to run `afl-multicore` on different `afl-fuzz` binaries you may
specify the fuzzer explicitly:

```json
"fuzzer": "afl-fuzz-fast"
```

Make sure the provided fuzzer binary is in your path! The default is to use `afl-fuzz`.   

afl-fuzz directory specifications:

```json
"input": "./in",
"output": "./out"
```

Target binary and command line settings:

```json
"target": "/usr/bin/target",
"cmdline": "-a -b -c -d"
```

Location read by the fuzzed program. Valid options are:

  * a file name
  * `@@` (see afl-fuzz manual)

```json
"file": "@@"
```

Timeout in ms for each fuzzing run:

```json
"timeout": "200+"
```

Memory limit in MB for target processes. To avoid hiccups make sure to provide
the desired memory limit value as a string!

```json
"mem_limit": "150"
```

Use afl QEMU mode?

```json
"qemu": true
```

Use `afl_margs` to provide additional cmdline arguments for afl. These
arguments will directly be passed to afl! This way you may provide new,
hacked or experimental cmdline args to `afl-fuzz`.

```json
"afl_margs": "-T banner"
```

Skip afl deterministic steps:

```json
"dirty": true
```

Fuzz without instrumentation:

```json
"dumb": true
```

Specify a fuzzing dictionary:

```json
"dict": "dict/target.dict"
```

Provide a name for the fuzzing session. Master outputs
will be written to `output/SESSION000`!

```json
"session": "SESSION"
```

The optional `master_instances` configuration option controls how many master instances should be started:

* `master_instances = 1` or omitted: run in default single-master mode
* `master_instances <= 0`: run in slave-only mode
* `master_instances > 1`: run in experimental multi-master mode

```json
"master_instances": 1
```

Interactive screen mode. Starts every afl instance in a separate
screen window. Run `afl-multicore` from inside screen!

```json
"interactive": true
```

Environment variables `afl-multicore` will set when using interactive screen mode.

```json
"environment": [
    "AFL_PERSISTENT=1",
    "LD_PRELOAD=desock.so"
]
```

## afl-multikill

Aborts all `afl-fuzz` instances belonging to an active non-interactive `afl-multicore`
session. `afl-multicore` sessions that were started in `screen` mode can not be aborted!

Usage example:

    $ afl-multikill -S target_session


## afl-stats

Prints fuzzing statistics similar to `afl-whatsup -s` and optionally posts (tweets) them
to Twitter. This is especially useful when fuzzing on multiple machines. Regularly ssh-ing
into all of your boxes to check `fuzzer_stats` quickly becomes a PITA...  
Additionally `afl-stats` may dump the current contents of `fuzzer_stats` into a database.
So upon later inspection you have historical stats information in one place for analysis.
For twitter setup instructions, please see
[docs/INSTALL.md](https://gitlab.com/rc0r/afl-utils/blob/master/docs/INSTALL.md)!
Screenshots of sample tweets can be found in the final section of this document.

Usage example:

    $ afl-stats -c target-stats.conf -d stats.db -t


## afl-sync

Using `afl-sync` you may distribute fuzzing corpora of multiple `afl-fuzz` instances
across node boundaries. It allows to backup, restore or synchronise `afl-fuzz` instance
directories to, from or with a remote destination. Under the hood `afl-sync` uses
`rsync` with enabled compression and tries to avoid unnecessary data transfers. During
a push operation `afl-sync` takes an `afl-fuzz` synchronisation directory and transfers
all contained fuzzer directories to a remote location appending the `.sync` extension.
When pulling `afl-sync` downloads all fuzzer directories from the remote location to
the synchronisation dir. Fuzzer instances already located in the local sync dir that
previously were used for pushing will not be downloaded! In order to download these
fuzzer directories provide a clean sync dir.
The synchronisation operation simply issues a pull followed by push command.
Specific fuzzing jobs may be selected from a sync dir by providing their respective
session name (`-S session`). See `afl-multicore` for more info about session naming.

Usage examples:

    $ afl-sync push ./afl_sync_dir rc0r@remote.fuzzer_instance_repo.com:/repo/target/
    $ afl-sync pull ./afl_sync_dir rc0r@remote.fuzzer_instance_repo.com:/repo/target/
    $ afl-sync sync ./afl_sync_dir rc0r@remote.fuzzer_instance_repo.com:/repo/target/


## afl-vcrash

`afl-vcrash` verifies that afl-fuzz crash samples really lead to crashes in the target
binary and optionally removes these samples automatically.  
Note: `afl-vcrash` functionality is incorporated into `afl-collect`. If `afl-collect` is
invoked with switch `-r`, it runs `afl-vcrash -qr` to quietly remove invalid samples from
the collected files.  
To enable parallel crash sample verification provide `-j` followed by the desired number
of threads `afl-vcrash` will utilize. Depending on the target process you're fuzzing,
running multiple threads in parallel can significantly improve verification speeds.

Usage example:

    $ afl-vcrash -r -j 8 ./dir_with_crashes -- /path/to/target --target-opt


## Screenshots

### afl-collect

Sample output:

![afl-collect_sample](https://gitlab.com/rc0r/afl-utils/raw/master/.scrots/afl_collect_sample.png)

### afl-sync

![afl-sync_diagram](https://gitlab.com/rc0r/afl-utils/raw/master/.scrots/afl-sync-diagram.png)

### afl-multicore

Sample output (normal mode):

![afl-multicore_sample](https://gitlab.com/rc0r/afl-utils/raw/master/.scrots/afl_multicore_sample.png)

### afl-stats

![afl-stats_sample](https://gitlab.com/rc0r/afl-utils/raw/master/.scrots/afl_stats_sample.png)

![afl-stats_tweet](https://gitlab.com/rc0r/afl-utils/raw/master/.scrots/afl_stats_tweet.png)

