def phishng_detection(urlname):
checkprediction = inputScript.main(urlname)
prediction = classifier.predict(checkprediction)
if (prediction == 1):
return("URL may be a phishing attack!")
else:
return("URL seems safe")
def make_predict():
#error checking
data = request.get_json(force=True)
#extract url from request
url_to_be_predicted = data['url']
url = str(url_to_be_predicted)
#load the pickle file
classifier = joblib.load('final_models/rf_final.pkl')
#checking and predicting
try:
checkprediction = inputScript.main(url)
prediction = int(classifier.predict(checkprediction))
print(prediction)
result = {"prediction": prediction}
except Exception as e:
#print("Error")
result = {"prediction": -9999}
#print(prediction)
#prediction = prediction + 1
return jsonify(result)
def send():
if (request.method == 'POST'):
url = request.form['url']
cp = inputScript.main(url)
pos = percentageSafety(cp)
try:
if (requests.get(url).status_code == 200):
URLStatus = 'Online'
else:
URLStatus = 'Offline'
except:
URLStatus = "Unknown"
GlobalRank, NationRank, NationName = pagerank(url)
checkprediction = np.reshape(cp, (1, -1))
prediction = classifier.predict(checkprediction)
if (prediction < -0.5):
PTResult = "Safe"
elif (prediction > 0.5):
PTResult = "Unsafe"
else:
PTResult = "Suspicious"
return render_template('result.html',
URL=url,
STATUS=URLStatus,
PHISHSTATUS=PTResult,
PercentageOfSafety=pos,
GLOBALRANK=GlobalRank,
NATIONNAME=NationName,
NATIONRANK=NationRank)
return render_template('index.html')
def start(x):
# load the pickle file
if x == '1': # Random Forest
classifier = joblib.load('rf_final.pkl')
elif x == '2': # SVM
classifier = joblib.load('svm_final.pkl')
elif x == '3': # LogisticRegression
classifier = joblib.load('logisticR_final.pkl')
else:
print("Please choose a valid option")
x = input(
"Enter the method you want to use:\n1.RandomForest\n2.Support Vector Machine\n3.Logistic Regression\n"
)
start(x)
# input url
url = input("Enter Website URL: ")
# checking and predicting
checkprediction = inputScript.main(url)
prediction = classifier.predict(checkprediction)
if prediction == 1:
print("\nPhishing Website Detected\n")
print("Can't open website")
else:
print("\nNo Phishing Website Detected\n")
print("Opening Website..........")
webbrowser.open_new(url)
y = input("Would you like to continue:\nY\nN\n")
cont(y)
def result():
urlname = request.args['name']
result = inputScript.main(urlname)
prediction = classifier.predict(result)
if (prediction == 1):
return ("Phishing URL")
else:
return ("Safe URL")
def y_predict():
'''
For rendering results on HTML GUI
'''
url = request.form['website URL']
checkprediction = inputScript.main(url)
prediction = model.predict(checkprediction)
print(prediction)
output = prediction[0]
if (output == 1):
pred = "The Website is Legitimate"
else:
pred = "This is a Phishing Website,your data may fall into high risk"
return render_template('LR.html', prediction_text='{}'.format(pred))
def processing():
text = request.form['name']
if text:
checkprediction = inputScript.main(text)
prediction = classifier.predict(checkprediction)
if prediction[0] == -1:
c = "Legit"
d = 'name'
else:
c = "Phishing"
d = 'namered'
return jsonify({d: c})
else:
return jsonify({"error": "Missing data!"})
def y_predict():
'''
For rendering results on HTML GUI
'''
url = request.form['URL']
checkprediction = inputScript.main(url)
prediction = model.predict(checkprediction)
print(prediction)
output = prediction[0]
if (output == 1):
pred = "Your are safe!! This is a Legitimate Website."
else:
pred = "You are on the wrong site. Be cautious!"
return render_template('final.html',
prediction_text='{}'.format(pred),
url=url)
def CHECK():
link = url.get('1.0', 'end-1c')
checkprediction = inputScript.main(link)
# load the pickle file
classifier = joblib.load('final_models/svm_final1.pkl')
# checking and predicting
prediction = classifier.predict(checkprediction)
print(prediction)
if prediction == 1:
yes = tk.Label(
root,
text="! Web Site Looks Phishing Site, Browse at your OWN RISK !",
background="red",
foreground="white",
font=('times', 18, 'italic'),
width=60)
yes.place(x=300, y=350)
button2 = tk.Button(root,
command=BROWSE,
foreground="white",
background="black",
font=("Times New Roman", 14, "italic"),
text="Browse Anyway",
width=14,
height=1)
button2.place(x=600, y=400)
else:
no = tk.Label(root,
text="! Site Seems Safe Site !",
background="green",
foreground="white",
font=('times', 18, ' italic '),
width=60)
no.place(x=300, y=350)
button2 = tk.Button(root,
command=BROWSE,
foreground="white",
background="black",
font=("Times New Roman", 14, "italic"),
text="Browse",
width=14,
height=1)
button2.place(x=600, y=400)
def send():
if (request.method == 'POST'):
url = request.form['url']
cp = inputScript.main(url)
pos = percentageSafety(cp)
try:
if (requests.get(url).status_code == 200):
URLStatus = 'Online'
else:
URLStatus = 'Offline'
except:
URLStatus = "Unknown"
GlobalRank, NationRank, NationName = pagerank(url)
checkprediction = np.reshape(cp, (1, -1))
prediction = classifier.predict(checkprediction)
if (prediction < 0.1):
PTResult = "Safe"
pos = (pos + 100) / 2
elif (prediction > 0.6):
PTResult = "Phishing"
try:
""" Checking if model prediction is true or not """
p = phishtank.PhishTank()
result = p.check(url)
if result.in_database:
if result.valid:
PTResult = "Phishing"
else:
PTResult = "Safe"
else:
PTResult = "Safe"
except:
PTResult = "Phishing"
else:
PTResult = "Suspicious"
return render_template('result.html',
URL=url,
STATUS=URLStatus,
PHISHSTATUS=PTResult,
PercentageOfSafety=pos,
GLOBALRANK=GlobalRank,
NATIONNAME=NationName,
NATIONRANK=NationRank)
return render_template('index.html')
def make_prediction():
classifier = joblib.load('rf_final.pkl')
if request.method=='POST':
url = request.form['url']
if not url:
return render_template('home.html', label = 'Please input url')
elif(not(regex.search(r'^(http|ftp)s?://', url))):
return render_template('home.html', label = 'Please input full url, for exp- https://facebook.com')
checkprediction = inputScript.main(url)
prediction = classifier.predict(checkprediction)
if prediction[0]==1 :
label = 'website is not legitimate'
elif prediction[0]==-1:
label ='website is legitimate'
return render_template('home.html', label=label)
# -*- code: utf-8 -*-
#importing libraries
from sklearn.externals import joblib
import inputScript
#load the pickle file
classifier = joblib.load('final_models/rf_final.pkl')
#input url
print("enter url")
url = input()
#checking and predicting
checkprediction = inputScript.main(url)
prediction = classifier.predict(checkprediction)
print(prediction)
file.close()
if(len(urlList)==0):
print ("Email has no URL")
return None
else:
return urlList
#checking and predicting
if (extractURL('email.txt') == None):
print("Email does not contain a URL")
else:
urlValue = []
urlValue = extractURL('email.txt')
length = len(urlValue)
for i in range(length):
checkprediction = inputScript.main(urlValue[i])
<<<<<<< HEAD
white_black_test = WhiteBlackApp(urlValue[i], self.domain)
white_black_results = white_black_test.run()
if white_black_results[0]:
=======
prediction = classifier.predict(checkprediction)
#print (prediction)
if (prediction == 1):
>>>>>>> b57b169535b57c497d9e244b4ddd8785e0632966
print("Email contains URL that may be a phishing attack: " + urlValue[i])
elif white_black_results[1]:
print("Email contains URL that seems safe: " + urlValue[i])
prediction = classifier.predict(checkprediction)
else:
if (prediction == 1):
port=3307)
# print(mydb)
# specify a cursor
cursor = db.cursor()
# get the url from db
url = "SELECT website_url FROM phishing WHERE type=''"
cursor.execute(url)
result = cursor.fetchall()
for row in result:
website = row[0]
# print(website)
# checking and predicition
checkprediction = inputScript.main(website)
prediction = classifier.predict(checkprediction)
if (prediction == 1):
type_result = "THE SITE A PHISHING SITE :'{"
else:
type_result = "The site is not a phishing site :)"
#updating db
type_update = 'UPDATE phishing SET type="' + type_result + '" WHERE website_url= "' + website + '"'
try:
cursor.execute(type_update)
db.commit()
except:
db.rollback()
# close connection
#create a list that contains each word in each line
wordsInLine = line.split(' ')
#For each word try to split it with :
for word in wordsInLine:
tempWord = word.split(":")
#Check to see if the word is a URL
if len(tempWord) == 2:
if tempWord[0] == "http" or tempWord[0] == "https":
urlList.append(word)
file.close()
return urlList[0]
def phishng_detection(urlname):
checkprediction = inputScript.main(urlname)
prediction = classifier.predict(checkprediction)
if (prediction == 1):
return("URL may be a phishing attack!")
else:
return("URL seems safe")
#checking and predicting
checkprediction = inputScript.main(extractURL('email.txt'))
prediction = classifier.predict(checkprediction)
if (prediction == 1):
print("Email contains URL that may be a phishing attack!")
else:
print("Email contains URL that seems safe")
