验证码的另一种方法：极验验证码，
此文章代码非原创，如有侵权，请告知删除。
我们以bilibili为例：https://passport.bilibili.com/login
1-1
首先需要找到验证码的图片，一个是背景图片，一个缺口图片
1-2
1-3
将这些图片碎片下载下来
browser = webdriver.Chrome()
browser.get(url)
bg = []
fullgb = []
while bg == []and fullgb == []:
bf = BeautifulSoup(browser.page_source,'lxml')
#找到图片
bg = bf.find_all('div',class_='gt_cut_bg_slice')
fullgb = bf.find_all('div',class_='gt_cut_fullbg_slice')
#正则匹配图片的url
bg_url = re.findall('url\(\"(.*)\"\);', bg[0].get('style'))[0].replace('webp','jpg')
fullgb_url = re.findall('url\(\"(.*)\"\);', fullgb[0].get('style'))[0].replace('webp','jpg')
bg_location_list = []
fullbg_location_list = []
for each_bg in bg:
location = {}
location['x'] =int(re.findall('background-position: (.*)px (.*)px;', each_bg.get('style'))[0][0])
location['y'] =int(re.findall('background-position: (.*)px (.*)px;', each_bg.get('style'))[0][1])
#将图片碎片存放在一个列表中
bg_location_list.append(location)
for each_fullgb in fullgb:
location = {}
location['x'] =int(re.findall('background-position: (.*)px (.*)px;', each_fullgb.get('style'))[0][0])
location['y'] =int(re.findall('background-position: (.*)px (.*)px;', each_fullgb.get('style'))[0][1])
#将图片碎片存放在一个列表中
fullbg_location_list.append(location)
# 把资源下载到临时目录
urlretrieve(url=bg_url,filename='bg.jpg')
print('缺口图片下载完成')
urlretrieve(url=fullgb_url,filename='fullbg.jpg')
print('背景图片下载完成')
1-4
图片是乱序的，需要排序
然后将乱序的图片排序后重新保存一下，两张图片都需要排序
im = image.open('fullbg.jpg')
new_im = image.new('RGB', (260,116))
im_list_upper = []
im_list_down = []
#循环图片列表，开始还原图片
for location in fullbg_location_list:
if location['y'] == -58:
im_list_upper.append(im.crop((abs(location['x']),58,abs(location['x']) +10,166)))
if location['y'] ==0:
im_list_down.append(im.crop((abs(location['x']),0,abs(location['x']) +10,58)))
new_im = image.new('RGB', (260,116))
x_offset =0
for imin im_list_upper:
new_im.paste(im, (x_offset,0))
x_offset += im.size[0]
x_offset =0
for imin im_list_down:
new_im.paste(im, (x_offset,58))
x_offset += im.size[0]
new_im.save('fullbg1.jpg')
1-5
还原完成之后就是能根据两张图片像素之间的差别确定缺口的位置，然后计算出滑块需要移动的距离，模拟滑块移动即可。
import random
import time
from selenium.webdriver import ActionChains
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.common.by import By
from urllib.request import urlretrieve
from selenium import webdriver
from bs4 import BeautifulSoup
import PIL.Image as image
import re
class Crack():
def __init__(self, username, passwd):
self.url ='https://passport.bilibili.com/login'
self.browser = webdriver.Chrome()
self.wait = WebDriverWait(self.browser,100)
self.BORDER =6
self.passwd = passwd
self.username = username
def open(self):
"""打开浏览器,并输入查询内容"""
self.browser.get(self.url)
keyword =self.wait.until(EC.presence_of_element_located((By.ID,'login-username')))
keyword.send_keys(self.username)
keyword =self.wait.until(EC.presence_of_element_located((By.ID,'login-passwd')))
keyword.send_keys(self.passwd)
# bowton.click()
def get_images(self, bg_filename='bg.jpg', fullbg_filename='fullbg.jpg'):
"""获取验证码图片:return: 图片的location信息"""
bg = []
fullgb = []
while bg == []and fullgb == []:
bf = BeautifulSoup(self.browser.page_source,'lxml')
bg = bf.find_all('div',class_='gt_cut_bg_slice')
fullgb = bf.find_all('div',class_='gt_cut_fullbg_slice')
bg_url = re.findall('url\(\"(.*)\"\);', bg[0].get('style'))[0].replace('webp','jpg')
fullgb_url = re.findall('url\(\"(.*)\"\);', fullgb[0].get('style'))[0].replace('webp','jpg')
bg_location_list = []
fullbg_location_list = []
for each_bg in bg:
location = {}
location['x'] =int(re.findall('background-position: (.*)px (.*)px;', each_bg.get('style'))[0][0])
location['y'] =int(re.findall('background-position: (.*)px (.*)px;', each_bg.get('style'))[0][1])
bg_location_list.append(location)
for each_fullgb in fullgb:
location = {}
location['x'] =int(re.findall('background-position: (.*)px (.*)px;', each_fullgb.get('style'))[0][0])
location['y'] =int(re.findall('background-position: (.*)px (.*)px;', each_fullgb.get('style'))[0][1])
fullbg_location_list.append(location)
# 把资源下载到临时目录
urlretrieve(url=bg_url,filename=bg_filename)
print('缺口图片下载完成')
urlretrieve(url=fullgb_url,filename=fullbg_filename)
print('背景图片下载完成')
return bg_location_list, fullbg_location_list
def get_merge_image(self, filename, location_list):
"""根据位置对图片进行合并还原 :filename:图片 :location_list:图片位置"""
im = image.open(filename)
new_im = image.new('RGB', (260,116))
im_list_upper = []
im_list_down = []
for location in location_list:
if location['y'] == -58:
im_list_upper.append(im.crop((abs(location['x']),58,abs(location['x']) +10,166)))
if location['y'] ==0:
im_list_down.append(im.crop((abs(location['x']),0,abs(location['x']) +10,58)))
new_im = image.new('RGB', (260,116))
x_offset =0
for im in im_list_upper:
new_im.paste(im, (x_offset,0))
x_offset += im.size[0]
x_offset =0
for im in im_list_down:
new_im.paste(im, (x_offset,58))
x_offset += im.size[0]
new_im.save(filename)
return new_im
def is_pixel_equal(self, img1, img2, x, y):
"""判断两个像素是否相同 :param image1: 图片1:param image2: 图片2:param x: 位置x :param y: 位置y:return: 像素是否相同"""
# 取两个图片的像素点
pix1 = img1.load()[x, y]
pix2 = img2.load()[x, y]
threshold =60
if (abs(pix1[0] - pix2[0]) < threshold and abs(pix1[1] - pix2[1]) < threshold and abs(
pix1[2] - pix2[2]) < threshold):
return True
else:
return False
def get_gap(self, img1, img2):
"""获取缺口偏移量:param img1: 不带缺口图片:param img2: 带缺口图片 :return"""
left =43
for i in range(left, img1.size[0]):
for j in range(img1.size[1]):
if not self.is_pixel_equal(img1, img2, i, j):
left = i
return left
return left
def get_track(self, distance):
"""根据偏移量获取移动轨迹 :param distance: 偏移量:return: 移动轨迹"""
# 移动轨迹
track = []
# 当前位移
current =0
# 减速阈值
mid = distance *0.8
# 计算间隔
t =0.05
# 初速度
v =0
while current <1.5*distance:
if current < mid:
# 加速度为正2
a =18
else:
# 加速度为负3
a = -6
# 初速度v0
v0 = v
# 当前速度v = v0 + at
v = v0 + a * t
# 移动距离x = v0t + 1/2 * a * t^2
move = v0 * t +1 /2 * a * t * t
# 当前位移
current += move
# 加入轨迹
track.append(round(move))
print('forword', current, distance)
v =0
while current - distance >2:
a = -40
v0 = v
v = v0 + a * t
# 移动距离x = v0t + 1/2 * a * t^2
move = v0 * t +1 /2 * a * t * t
# 当前位移
current += move
# 加入轨迹
track.append(round(move))
print('backword',current,distance)
move = current - distance
# 加入轨迹
track.append(round(move))
return track
def get_slider(self):
"""获取滑块:return: 滑块对象"""
while True:
try:
slider =self.browser.find_element_by_xpath("//div[@class='gt_slider_knob gt_show']")
break
except:
time.sleep(0.5)
return slider
def move_to_gap(self, slider, track):
""" 拖动滑块到缺口处:param slider: 滑块 :param track: 轨迹 :return:"""
ActionChains(self.browser).click_and_hold(slider).perform()
while track:
#x = random.choice(track)
x=track.pop(0)
ActionChains(self.browser).move_by_offset(xoffset=x,yoffset=0).perform()
#track.remove(x)
time.sleep(0.01)
time.sleep(2)
print('release')
ActionChains(self.browser).release(slider).perform()
time.sleep(2)
#self.browser.quit()
def crack(self):
# 打开浏览器
self.open()
# 保存的图片名字
bg_filename ='./images/bg.jpg'
fullbg_filename ='./images/fullbg.jpg'
# 获取图片
bg_location_list, fullbg_location_list =self.get_images(bg_filename, fullbg_filename)
# 根据位置对图片进行合并还原
bg_img =self.get_merge_image(bg_filename, bg_location_list)
fullbg_img =self.get_merge_image(fullbg_filename, fullbg_location_list)
# 获取缺口位置
gap =self.get_gap(fullbg_img, bg_img)
print('缺口位置', gap)
track =self.get_track(gap -self.BORDER)
print('滑动滑块')
# 点按呼出缺口
slider =self.get_slider()
# 拖动滑块到缺口处
self.move_to_gap(slider, track)
time.sleep(1)
mspan =self.browser.find_element_by_class_name('gt_info_content')
info = mspan.text
print('info:', info)
try:
if '怪物吃了拼图' in info:
print(mspan.text)
time.sleep(2)
self.crack()
elif '正确拼合' in info:
self.crack()
except Exception as e:
print(e)
if __name__ =='__main__':
crack = Crack('username','passwd')
crack.crack()
print('验证成功')
1-6
网友评论