def do_prediction(self, intbl, selections, gene_names,
filteropt=1, filterval=1, spec_ecutoff=0.4, nonspec_ecutoff=0.35):
'''
intbl: preprocessed table
filteropt: 1 for highest t-val, 2 for p-val cutoff
filterval: # TFs for opt 1 and p-val cutoff for opt 2
'''
if type(intbl) is str: # got an error in the pipeline from inittbl
return {'current': 1, 'total': 1, 'error': intbl}
# intbl: #rowidx,seq,val,diff,t,pbmname,escore_seq
start_time = time.time()
#while not inittask.ready():
# time.sleep(1)
#intbl = inittask.get()
predfiles = [app.config['PREDDIR'] + "/" + s for s in selections] # os.listdir(preddir)
preds = [l for l in utils.chunkify(predfiles,app.config['PCOUNT']) if len(l) != 0] # chunks the predfiles for each process
# collect the short2long_map -- shared, so only one i/o
emap = pd.read_csv("%s/index_short_to_long.csv" % (app.config["ESCORE_DIR"]), header=0, index_col=0, sep=',', dtype='Int32') # pd.DataFrame
emap = np.array(emap[emap.columns[0]]) - 1 #emap[emap.columns[0]].to_numpy() - 1
# ---- MULTIPROCESSING PART ----
pool = mp.Pool(processes=app.config['PCOUNT'])
# need to use manager here
shared_ready_sum = mp.Manager().Value('i', 0)
predict_partial = ft.partial(predict, **{'dataset':intbl, 'ready_count':shared_ready_sum, 'emap':emap,
'filteropt':filteropt, 'filterval':filterval, 'spec_ecutoff':spec_ecutoff, 'nonspec_ecutoff':nonspec_ecutoff})
async_pools = [pool.apply_async(predict_partial, (preds[i], )) for i in range(0,len(preds))]
# run the job, update progress bar
total = len(predfiles)
while not all([p.ready() for p in async_pools]):
time.sleep(2) # super important to avoid checking every loop
self.update_state(state='PROGRESS',
meta={'current': shared_ready_sum.value, 'total': total, 'status': 'Processing input data...'})
res = [p.get() for p in async_pools]
self.update_state(state='PROGRESS',
meta={'current': shared_ready_sum.value, 'total': total, 'status': 'post-processing'})
print("Terminate all children process..")
pool.terminate() # terminate to kill all child processes !!! Like.. super important,
# to avoid memory leak, seriously...
datavalues = postprocess(res,predfiles,gene_names,filteropt,filterval)
''' SET the values in redis '''
#print("marktesting",colnames,datavalues)
savetomongo(self.request.id, datavalues.to_dict('records') ,app.config['USER_DATA_EXPIRY'])
# significance_score can be z-score or p-value depending on the out_type
#db.expire("%s:vals:*" % self.request.id, app.config['USER_DATA_EXPIRY'])
return {'current': shared_ready_sum.value, 'total': len(predfiles), 'status': 'Task completed!',
'result': 'done', 'taskid': self.request.id,
'time':(time.time()-start_time)} # -- somehow cannot do jsonify(postproc)
def __init__(self, depth, threading):
# Logger already setup by config, just get an instance
logobj = logging.getLogger('eventgen')
from eventgenconfig import EventgenAdapter
adapter = EventgenAdapter(logobj, {
'module': 'Queue',
'sample': 'null'
})
self.logger = adapter
# logger.info("Creating Queue of depth %d, threading %s" % (depth, threading))
if threading == 'thread':
self.q = PQueue.Queue(depth)
else:
self.q = multiprocessing.Manager().Queue(depth)
self.depth = depth
def __init__(self, blocking=True, db_path=None, ncpu=1):
"""
Init function
Parameter
---------
blocking: bool
determines whether join() blocks or not
db_path: str
the string to a LevelDB for command persistence
"""
self.__blocking = blocking
self.__broker_queue = mp.Queue()
self.__job_queue = mp.JoinableQueue()
self.__pending_dict = mp.Manager().dict()
self.__results_queue = mp.Queue()
self.__results_queue_worker = mp.Queue()
if db_path is None:
tmp_db = NamedTemporaryFile(delete=False,
dir=os.getcwd(),
suffix=".db")
tmp_db.close()
self.__is_temp_db = True
self.__db_path = tmp_db.name
else:
self.__is_temp_db = False
self.__db_path = db_path
self.__broker = _Broker(self.__broker_queue,
self.__job_queue,
self.__results_queue,
self.__results_queue_worker,
self.__pending_dict,
db_path=self.__db_path)
self.__broker.daemon = False
self.__broker.start()
self.__worker = []
for i in range(ncpu):
p = _Worker(self.__broker_queue, self.__job_queue,
self.__results_queue_worker)
p.daemon = False
self.__worker.append(p)
p.start()
def __init__(self,
targets,
ports=range(65536),
threads=100,
timeout=3,
proxy_ip=["127.0.0.1", "127.0.0.1"],
proxy_port=[80, 80]):
self._targets_ = targets
self._ports_ = ports
self._threads_ = threads
self._timeout_ = timeout
self._proxy_ip_ = proxy_ip
self._proxy_port_ = proxy_port
self._worker_pool_ = []
self._worker_count_ = cpu_count()
self._job_len_ = len(targets)
self._scanners_ = [
Scan(self._targets_[i], self._ports_, self._threads_,
self._timeout_, self._proxy_ip_, self._proxy_port_)
for i in range(self._job_len_)
]
self._scan_secure_ = [
Scan(self._targets_[i], self._ports_, self._threads_,
self._timeout_, self._proxy_ip_[0], self._proxy_port_[0])
for i in range(self._job_len_)
]
self._scan_unsecure_ = [
Scan(self._targets_[i], self._ports_, self._threads_,
self._timeout_, self._proxy_ip_[1], self._proxy_port_[1])
for i in range(self._job_len_)
]
self._manager_ = billiard.Manager()
self._log_ = self._manager_.dict()
self._proxy_log_ = self._manager_.dict()
self._total_runtime_ = 0
from pygtftk.utils import GTFtkError
from pygtftk.utils import add_prefix_to_file
from pygtftk.utils import close_properly
from pygtftk.utils import flatten_list
from pygtftk.utils import intervals
from pygtftk.utils import make_tmp_file
from pygtftk.utils import message
# -------------------------------------------------------------------------
# TMP_FILE_POOL_MANAGER stores temporary file name
# make_tmp_file_pool is function that add temporary files to TMP_FILE_POOL_MANAGER
# TMP_FILE_POOL_MANAGER will be updated by workers (in contrast to a global
# variable)
# -------------------------------------------------------------------------
TMP_FILE_POOL_MANAGER = multiprocessing.Manager().list()
def make_tmp_file_pool(prefix='tmp',
suffix='',
store=True,
dir=None):
"""
This
:Example:
>>> from pygtftk.utils import make_tmp_file_pool
>>> tmp_file = make_tmp_file_pool()
>>> assert os.path.exists(tmp_file.name)
>>> tmp_file = make_tmp_file_pool(prefix="pref")
def do_prediction(self,
intbl,
selections,
gene_names,
filteropt=1,
filterval=1,
spec_ecutoff=0.4,
nonspec_ecutoff=0.35):
'''
intbl: preprocessed table
filteropt: 1 for highest t-val, 2 for p-val cutoff
filterval: # TFs for opt 1 and p-val cutoff for opt 2
'''
if type(intbl) is str: # got an error in the pipeline from inittbl
return {'current': 1, 'total': 1, 'error': intbl}
# intbl: #rowidx,seq,val,diff,t,pbmname,escore_seq
start_time = time.time()
#while not inittask.ready():
# time.sleep(1)
#intbl = inittask.get()
# move the comment here for testing
pool = mp.Pool(processes=app.config['PCOUNT'])
predfiles = [app.config['PREDDIR'] + "/" + s
for s in selections] # os.listdir(preddir)
preds = utils.chunkify(
predfiles,
app.config['PCOUNT']) # chunks the predfiles for each process
# need to use manager here
shared_ready_sum = mp.Manager().Value('i', 0)
async_pools = [
pool.apply_async(predict,
(preds[i], intbl, shared_ready_sum, filteropt,
filterval, spec_ecutoff, nonspec_ecutoff))
for i in range(0, len(preds))
]
# run the job, update progress bar
total = len(predfiles)
while not all([p.ready() for p in async_pools]):
time.sleep(2) # super important to avoid checking every loop
self.update_state(state='PROGRESS',
meta={
'current': shared_ready_sum.value,
'total': total,
'status': 'Processing input data...'
})
res = [p.get() for p in async_pools]
self.update_state(state='PROGRESS',
meta={
'current': shared_ready_sum.value,
'total': total,
'status': 'post-processing'
})
print("Terminate all children process..")
pool.terminate(
) # terminate to kill all child processes !!! Like.. super important,
# to avoid memory leak, seriously...
colnames, datavalues = postprocess(res, gene_names, filteropt, filterval)
''' SET the values in redis '''
#print("marktesting",colnames,datavalues)
savetoredis(self.request.id, colnames, datavalues,
app.config['USER_DATA_EXPIRY'])
# significance_score can be z-score or p-value depending on the out_type
#db.expire("%s:vals:*" % self.request.id, app.config['USER_DATA_EXPIRY'])
return {
'current': shared_ready_sum.value,
'total': len(predfiles),
'status': 'Task completed!',
'result': 'done',
'taskid': self.request.id,
'time': (time.time() - start_time)
} # -- somehow cannot do jsonify(postproc)
def main(domain, threads, savefile, ports, silent, verbose, enable_bruteforce,
engines):
bruteforce_list = set()
search_list = set()
if is_windows:
subdomains_queue = list()
else:
subdomains_queue = billiard.Manager().list()
# Check Bruteforce Status
if enable_bruteforce or enable_bruteforce is None:
enable_bruteforce = True
# Validate domain
domain_check = re.compile(
"^(http|https)?[a-zA-Z0-9]+([\-\.]{1}[a-zA-Z0-9]+)*\.[a-zA-Z]{2,}$")
if not domain_check.match(domain):
if not silent:
print(R + "Error: Please enter a valid domain" + W)
return []
if not domain.startswith('http://') or not domain.startswith('https://'):
domain = 'http://' + domain
parsed_domain = urlparse.urlparse(domain)
if not silent:
print(B +
"[-] Enumerating subdomains now for %s" % parsed_domain.netloc +
W)
if verbose and not silent:
print(
Y +
"[-] verbosity is enabled, will show the subdomains results in realtime"
+ W)
supported_engines = {
'baidu': BaiduEnum,
'yahoo': YahooEnum,
'google': GoogleEnum,
'bing': BingEnum,
'ask': AskEnum,
'netcraft': NetcraftEnum,
'dnsdumpster': DNSdumpster,
'virustotal': Virustotal,
'threatcrowd': ThreatCrowd,
'ssl': CrtSearch,
'passivedns': PassiveDNS
}
chosenEnums = []
if engines is None:
chosenEnums = [
BaiduEnum, YahooEnum, GoogleEnum, BingEnum, AskEnum, NetcraftEnum,
DNSdumpster, Virustotal, ThreatCrowd, CrtSearch, PassiveDNS
]
else:
engines = engines.split(',')
for engine in engines:
if engine.lower() in supported_engines:
chosenEnums.append(supported_engines[engine.lower()])
# Start the engines enumeration
enums = [
enum(domain, [], q=subdomains_queue, silent=silent, verbose=verbose)
for enum in chosenEnums
]
for enum in enums:
enum.start()
for enum in enums:
enum.join()
subdomains = set(subdomains_queue)
for subdomain in subdomains:
search_list.add(subdomain)
if enable_bruteforce:
if not silent:
print(G + "[-] Starting bruteforce module now using subbrute.." +
W)
record_type = False
path_to_file = os.path.dirname(os.path.realpath(__file__))
subs = os.path.join(path_to_file, 'subbrute', 'names.txt')
resolvers = os.path.join(path_to_file, 'subbrute', 'resolvers.txt')
process_count = threads
output = False
json_output = False
bruteforce_list = subbrute.print_target(parsed_domain.netloc,
record_type, subs, resolvers,
process_count, output,
json_output, search_list,
verbose)
subdomains = search_list.union(bruteforce_list)
if subdomains:
subdomains = sorted(subdomains, key=subdomain_sorting_key)
if savefile:
write_file(savefile, subdomains)
if not silent:
print(Y +
"[-] Total Unique Subdomains Found: %s" % len(subdomains) +
W)
if ports:
if not silent:
print(G +
"[-] Start port scan now for the following ports: %s%s" %
(Y, ports) + W)
ports = ports.split(',')
pscan = portscan(subdomains, ports)
pscan.run()
elif not silent:
for subdomain in subdomains:
print(G + subdomain + W)
return subdomains