def test_get_entropy_zero(self):
string = "aaa"
info("Checked string - {}".format(string))
e = get_entropy(string)
info("Calculated entropy: {}".format(e))
assert_equal(e, 0,
"Check if calculated entropy is equal to predicted one")
def test_get_entropy(self):
string = "ab"
info("Checked string - {}".format(string))
e = get_entropy(string)
info("Calculated entropy: {}".format(e))
assert_true(e > 0, "Check if calculated entropy is bigger than 0")
assert_equal(e, 1,
"Check if calculated entropy is equal to predicted one")
def get_entropy_details(url_body):
try:
jsonschema.validate(url_body, details_url_schema)
except jsonschema.exceptions.ValidationError as exc:
raise BadRequest(exc.message)
calculated = entropy.get_entropy(url_body.get('url'))
response_text = {
"details": {
"entropy": round(calculated, 2)
}
}
return Response(json.dumps(
response_text,
default=_default_json_model
), 200, mimetype="application/json")
def create_baddie(domain):
_, ip_id = add_ip(domain)
_, crt_id = add_cert(domain)
good_keywords = [k['good_keyword'] for k in Goodies.get_all_goodies()]
domain_phrases = domain.split('.')
_, _, lev_matched_keyword = lev.levenstein_check(good_keywords,
domain_phrases)
min_lev_distance = 0
lev_distance = 0
if lev_matched_keyword:
for phrase in domain_phrases:
lev_distance = lev.calculate_levenstein(lev_matched_keyword,
phrase)
if 3 > min_lev_distance > lev_distance:
min_lev_distance = lev_distance
if not lev_matched_keyword:
lev_matched_keyword = ''
_, contained_matched_keyword = match_keyword(domain)
if not contained_matched_keyword:
contained_matched_keyword = ''
entropy = ent.get_entropy(domain)
return add_baddie(domain, ip_id[1], crt_id[1], lev_distance,
lev_matched_keyword, contained_matched_keyword, entropy)
def verify_entropy(URL):
if get_entropy(URL) >= Const.ENTROPY_PHISHING_MIN:
return True
else:
return False