def get(self):
parser = reqparse.RequestParser()
parser.add_argument('q')
args = parser.parse_args()
if not args.q:
return {'data': '0'}
if self.is_whitelisted(args.q):
p = 0
else:
itype = resolve_itype(args.q)
if not itype:
api.abort(422)
return
if itype == 'fqdn':
p = predict_domain(args.q)
elif itype == 'url':
p = predict_url(args.q)
else:
p = 0
p = str(round((p[0][0] * 100), 2))
return {'data': str(p)}
def predict_urls(indicators):
urls = _filter_indicators(indicators, 'url')
if len(urls) == 0:
return indicators
predictions = predict_url([u[0] for u in urls])
return _normalize_predictions(indicators, urls, predictions)
def predict_urls(self, indicators):
indicators = list(indicators)
urls = [(i.indicator, idx) for idx, i in enumerate(indicators)
if i.itype == 'url']
predict = predict_url([u[0] for u in urls])
for idx, u in enumerate(urls):
indicators[u[1]].probability = round((predict[idx][0] * 100), 2)
return indicators
def _predict_indicators(itype, indicators):
_load()
indicators = _to_list(indicators)
urls = [(i.indicator, idx) for idx, i in enumerate(indicators)
if i.itype == itype]
if itype == 'url':
predict = predict_url([u[0] for u in urls])
else:
predict = predict_fqdn([u[0] for u in urls])
for idx, u in enumerate(urls):
indicators[u[1]].probability = float(predict[idx][0])
return indicators