How to run driller

[ash09]

Hello, Could someone explain me how to run Driller? When I execute the run.py script, Driller listens for crashes but the fuzzer doesn't seem to start fuzzing. Thank you in advance.

$ python2 ~/software/driller/run.py bin/
INFO    | 2017-04-05 13:29:15,025 | driller | 1 binaries found
INFO    | 2017-04-05 13:29:15,025 | driller | 1 binaries found
INFO    | 2017-04-05 13:29:15,025 | driller | going to work on 1
INFO    | 2017-04-05 13:29:15,074 | driller | listening for crashes..

[ekilmer]

I would check the logs that Driller produces in fuzzer-err.log and driller-err.log. Chances are that AFL needs some extra environment options set. You can also check AFL's logs in your FUZZER_WORK_DIR

[gottlieb]

Further on this topic, it seems like run.py runs AFL as a fuzzer, and test_driller.py runs ANGR as a symbolic analysis tool, but none of the supplied scripts do both? Or am I missing something?

Can you provide any guidance about how the fuzzer and ANGR would be integrated?

[salls]

None of the scripts do both. The way we ran Driller was with the "Drilling" jobs on one machine and the AFL jobs on another. I think we used redis.

It is not hard to write a script that runs both on the same machine. Simply check for if AFL no longer has pending fav's then start a driller job with any inputs that have not been passed to Driller.

[ekilmer]

If you can get Redis and Celery running on the same machine, then you can execute

./run.py <bin_dir>

in one terminal and

./node.py

in another terminal. You'll be dividing your machine's resources between fuzzing and symbolic execution, though.

My config.py also looks something like this:

### Redis Options
REDIS_HOST = 'localhost'
REDIS_PORT = 6379
REDIS_DB = 1

### Celery Options
BROKER_URL = 'pyamqp://myuser:mypasswd@localhost:5672/myvhost'

CELERY_ROUTES = {'driller.tasks.fuzz': {'queue': 'fuzzer'}, 'driller.tasks.drill': {'queue': 'driller'}}

### Environment Options

# directory contain driller-qemu versions, relative to the directoy node.py is invoked in
QEMU_DIR = None

# directory containing the binaries, used by the driller node to find binaries
BINARY_DIR = '/drill-bins'

# directory containing the pcap corpus
PCAP_DIR = '/pcaps'

### Driller options
# how long to drill before giving up in seconds
DRILL_TIMEOUT = 60 * 60 * 2

# 16 GB
MEM_LIMIT = 16*1024*1024*1024

# where to write a debug file that contains useful debugging information like
# AFL's fuzzing bitmap, input used, binary path, time started.
# Uses following naming convention:
#   <binary_basename>_<input_str_md5>.py
DEBUG_DIR = '/drill-logs'

### Fuzzer options

# how often to check for crashes in seconds
CRASH_CHECK_INTERVAL = 60

# how long to fuzz before giving up in seconds
FUZZ_TIMEOUT = 60 * 60 * 24 * 5

# how long before we kill a dictionary creation process
DICTIONARY_TIMEOUT = 60 * 60

# how many fuzzers should be spun up when a fuzzing job is received
FUZZER_INSTANCES = 4

# where the fuzzer should place it's results on the filesystem
FUZZER_WORK_DIR = '/media/fuzz-ramdisk'

I'm using RabbitMQ with Celery, and I don't believe DRILL_TIMEOUT or FUZZ_TIMEOUT works with run.py or node.py (although I haven't tested it extensively). I would also look at https://github.com/mechaphish/worker and https://github.com/mechaphish/meister if you really want to get into it.

When restarting the jobs, I kill everything with pkill python; pkill celery; pkill afl-fuzz. Use that at your own risk if you have multiple python processes running that aren't related to angr.

I also clear the Celery queues with

rabbitmqadmin -u myuser -p mypasswd -V myvhost purge queue name=driller

and

rabbitmqadmin -u myuser -p mypasswd -V myvhost purge queue name=fuzzer

You can view the number of jobs in each queue with

rabbitmqadmin -u myuser -p mypasswd -V myvhost list queues vhost name node messages message_stats.publish_details.rate

[zardus]

I just uploaded the following script: https://github.com/shellphish/fuzzer/blob/master/shellphuzz

It facilitates drilling on a single machine, and is definitely easier than the whole redis/celery or kubernetes setup.