Python破解极验滑动验证码详细步骤(位移缺口)

极验滑动验证码

以上图片是最典型的要属于极验滑动认证了，极验官网：http://www.geetest.com/。

现在极验验证码已经更新到了 3.0 版本，截至 2017 年 7 月全球已有十六万家企业正在使用极验，每天服务响应超过四亿次，广泛应用于直播视频、金融服务、电子商务、游戏娱乐、政府企业等各大类型网站

对于这类验证，如果我们直接模拟表单请求，繁琐的认证参数与认证流程会让你蛋碎一地，我们可以用selenium驱动浏览器来解决这个问题，大致分为以下几个步骤

1、输入用户名，密码

2、点击按钮验证，弹出没有缺口的图

3、获得没有缺口的图片

4、点击滑动按钮，弹出有缺口的图

5、获得有缺口的图片

6、对比两张图片，找出缺口，即滑动的位移

7、按照人的行为行为习惯，把总位移切成一段段小的位移

8、按照位移移动

9、完成登录

实现

位移移动需要的基础知识

位移移动相当于匀变速直线运动，类似于小汽车从起点开始运行到终点的过程（首先为匀加速，然后再匀减速）。

其中a为加速度，且为恒量（即单位时间内的加速度是不变的），t为时间

位移移动的代码实现

def get_track(distance):
 '''
 拿到移动轨迹，模仿人的滑动行为，先匀加速后匀减速
 匀变速运动基本公式：
 ①v=v0+at
 ②s=v0t+(1/2)at²
 ③v²-v0²=2as
 :param distance: 需要移动的距离
 :return: 存放每0.2秒移动的距离
 '''
 # 初速度
 v=0
 # 单位时间为0.2s来统计轨迹，轨迹即0.2内的位移
 t=0.1
 # 位移/轨迹列表，列表内的一个元素代表0.2s的位移
 tracks=[]
 # 当前的位移
 current=0
 # 到达mid值开始减速
 mid=distance * 4/5
 distance += 10  # 先滑过一点，最后再反着滑动回来
 while current < distance:
  if current < mid:
# 加速度越小，单位时间的位移越小,模拟的轨迹就越多越详细
a = 2  # 加速运动
  else:
a = -3 # 减速运动
  # 初速度
  v0 = v
  # 0.2秒时间内的位移
  s = v0*t+0.5*a*(t**2)
  # 当前的位置
  current += s
  # 添加到轨迹列表
  tracks.append(round(s))
  # 速度已经达到v,该速度作为下次的初速度
  v= v0+a*t
 # 反着滑动到大概准确位置
 for i in range(3):
 tracks.append(-2)
 for i in range(4):
 tracks.append(-1)
 return tracks

对比两张图片，找出缺口

def get_distance(image1,image2):
 '''
拿到滑动验证码需要移动的距离
:param image1:没有缺口的图片对象
:param image2:带缺口的图片对象
:return:需要移动的距离
'''
 # print('size', image1.size)
 threshold = 50
 for i in range(0,image1.size[0]):  # 260
  for j in range(0,image1.size[1]):  # 160
pixel1 = image1.getpixel((i,j))
pixel2 = image2.getpixel((i,j))
res_R = abs(pixel1[0]-pixel2[0]) # 计算RGB差
res_G = abs(pixel1[1] - pixel2[1])  # 计算RGB差
res_B = abs(pixel1[2] - pixel2[2])  # 计算RGB差
if res_R > threshold and res_G > threshold and res_B > threshold:
 return i  # 需要移动的距离

获得图片

def merge_image(image_file,location_list):
 """
  拼接图片
 :param image_file:
 :param location_list:
 :return:
 """
 im = Image.open(image_file)
 im.save('code.jpg')
 new_im = Image.new('RGB',(260,116))
 # 把无序的图片 切成52张小图片
 im_list_upper = []
 im_list_down = []
 # print(location_list)
 for location in location_list:
  # print(location['y'])
  if location['y'] == -58: # 上半边
im_list_upper.append(im.crop((abs(location['x']),58,abs(location['x'])+10,116)))
  if location['y'] == 0:  # 下半边
im_list_down.append(im.crop((abs(location['x']),0,abs(location['x'])+10,58)))
 x_offset = 0
 for im in im_list_upper:
  new_im.paste(im,(x_offset,0))  # 把小图片放到 新的空白图片上
  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.show()
 return new_im
def get_image(driver,div_path):
 '''
 下载无序的图片  然后进行拼接 获得完整的图片
 :param driver:
 :param div_path:
 :return:
 '''
 time.sleep(2)
 background_images = driver.find_elements_by_xpath(div_path)
 location_list = []
 for background_image in background_images:
  location = {}
  result = re.findall('background-image: url\("(.*?)"\); background-position: (.*?)px (.*?)px;',background_image.get_attribute('style'))
  # print(result)
  location['x'] = int(result[0][1])
  location['y'] = int(result[0][2])
  image_url = result[0][0]
  location_list.append(location)
 print('==================================')
 image_url = image_url.replace('webp','jpg')
 # '替换url http://static.geetest.com/pictures/gt/579066de6/579066de6.webp'
 image_result = requests.get(image_url).content
 # with open('1.jpg','wb') as f:
 #  f.write(image_result)
 image_file = BytesIO(image_result) # 是一张无序的图片
 image = merge_image(image_file,location_list)
 return image

按照位移移动

print('第一步,点击滑动按钮')
 ActionChains(driver).click_and_hold(on_element=element).perform()  # 点击鼠标左键，按住不放
 time.sleep(1)
 print('第二步,拖动元素')
 for track in track_list:
ActionChains(driver).move_by_offset(xoffset=track, yoffset=0).perform() # 鼠标移动到距离当前位置（x,y）
 if l<100:
  ActionChains(driver).move_by_offset(xoffset=-2, yoffset=0).perform()
 else:
  ActionChains(driver).move_by_offset(xoffset=-5, yoffset=0).perform()
 time.sleep(1)
 print('第三步,释放鼠标')
 ActionChains(driver).release(on_element=element).perform()

详细代码

from selenium import webdriver
from selenium.webdriver.support.ui import WebDriverWait # 等待元素加载的
from selenium.webdriver.common.action_chains import ActionChains  #拖拽
from selenium.webdriver.support import expected_conditions as EC
from selenium.common.exceptions import TimeoutException, NoSuchElementException
from selenium.webdriver.common.by import By
from PIL import Image
import requests
import time
import re
import random
from io import BytesIO

def merge_image(image_file,location_list):
 """
  拼接图片
 :param image_file:
 :param location_list:
 :return:
 """
 im = Image.open(image_file)
 im.save('code.jpg')
 new_im = Image.new('RGB',(260,116))
 # 把无序的图片 切成52张小图片
 im_list_upper = []
 im_list_down = []
 # print(location_list)
 for location in location_list:
  # print(location['y'])
  if location['y'] == -58: # 上半边
im_list_upper.append(im.crop((abs(location['x']),58,abs(location['x'])+10,116)))
  if location['y'] == 0:  # 下半边
im_list_down.append(im.crop((abs(location['x']),0,abs(location['x'])+10,58)))
 x_offset = 0
 for im in im_list_upper:
  new_im.paste(im,(x_offset,0))  # 把小图片放到 新的空白图片上
  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.show()
 return new_im
def get_image(driver,div_path):
 '''
 下载无序的图片  然后进行拼接 获得完整的图片
 :param driver:
 :param div_path:
 :return:
 '''
 time.sleep(2)
 background_images = driver.find_elements_by_xpath(div_path)
 location_list = []
 for background_image in background_images:
  location = {}
  result = re.findall('background-image: url\("(.*?)"\); background-position: (.*?)px (.*?)px;',background_image.get_attribute('style'))
  # print(result)
  location['x'] = int(result[0][1])
  location['y'] = int(result[0][2])
  image_url = result[0][0]
  location_list.append(location)
 print('==================================')
 image_url = image_url.replace('webp','jpg')
 # '替换url http://static.geetest.com/pictures/gt/579066de6/579066de6.webp'
 image_result = requests.get(image_url).content
 # with open('1.jpg','wb') as f:
 #  f.write(image_result)
 image_file = BytesIO(image_result) # 是一张无序的图片
 image = merge_image(image_file,location_list)
 return image
def get_track(distance):
 '''
 拿到移动轨迹，模仿人的滑动行为，先匀加速后匀减速
 匀变速运动基本公式：
 ①v=v0+at
 ②s=v0t+(1/2)at²
 ③v²-v0²=2as
 :param distance: 需要移动的距离
 :return: 存放每0.2秒移动的距离
 '''
 # 初速度
 v=0
 # 单位时间为0.2s来统计轨迹，轨迹即0.2内的位移
 t=0.2
 # 位移/轨迹列表，列表内的一个元素代表0.2s的位移
 tracks=[]
 # 当前的位移
 current=0
 # 到达mid值开始减速
 mid=distance * 7/8
 distance += 10  # 先滑过一点，最后再反着滑动回来
 # a = random.randint(1,3)
 while current < distance:
  if current < mid:
# 加速度越小，单位时间的位移越小,模拟的轨迹就越多越详细
a = random.randint(2,4)  # 加速运动
  else:
a = -random.randint(3,5) # 减速运动
  # 初速度
  v0 = v
  # 0.2秒时间内的位移
  s = v0*t+0.5*a*(t**2)
  # 当前的位置
  current += s
  # 添加到轨迹列表
  tracks.append(round(s))
  # 速度已经达到v,该速度作为下次的初速度
  v= v0+a*t
 # 反着滑动到大概准确位置
 for i in range(4):
 tracks.append(-random.randint(2,3))
 for i in range(4):
 tracks.append(-random.randint(1,3))
 return tracks

def get_distance(image1,image2):
 '''
拿到滑动验证码需要移动的距离
:param image1:没有缺口的图片对象
:param image2:带缺口的图片对象
:return:需要移动的距离
'''
 # print('size', image1.size)
 threshold = 50
 for i in range(0,image1.size[0]):  # 260
  for j in range(0,image1.size[1]):  # 160
pixel1 = image1.getpixel((i,j))
pixel2 = image2.getpixel((i,j))
res_R = abs(pixel1[0]-pixel2[0]) # 计算RGB差
res_G = abs(pixel1[1] - pixel2[1])  # 计算RGB差
res_B = abs(pixel1[2] - pixel2[2])  # 计算RGB差
if res_R > threshold and res_G > threshold and res_B > threshold:
 return i  # 需要移动的距离

def main_check_code(driver, element):
 """
  拖动识别验证码
 :param driver: 
 :param element: 
 :return: 
 """
 image1 = get_image(driver, '//div[@class="gt_cut_bg gt_show"]/div')
 image2 = get_image(driver, '//div[@class="gt_cut_fullbg gt_show"]/div')
 # 图片上 缺口的位置的x坐标
 # 2 对比两张图片的所有RBG像素点，得到不一样像素点的x值，即要移动的距离
 l = get_distance(image1, image2)
 print('l=',l)
 # 3 获得移动轨迹
 track_list = get_track(l)
 print('第一步,点击滑动按钮')
 ActionChains(driver).click_and_hold(on_element=element).perform()  # 点击鼠标左键，按住不放
 time.sleep(1)
 print('第二步,拖动元素')
 for track in track_list:
ActionChains(driver).move_by_offset(xoffset=track, yoffset=0).perform()  # 鼠标移动到距离当前位置（x,y）　　　　　time.sleep(0.002)
 # if l>100:
 ActionChains(driver).move_by_offset(xoffset=-random.randint(2,5), yoffset=0).perform()
 time.sleep(1)
 print('第三步,释放鼠标')
 ActionChains(driver).release(on_element=element).perform()
 time.sleep(5)

def main_check_slider(driver):
 """
 检查滑动按钮是否加载
 :param driver: 
 :return: 
 """
 while True:
  try :
driver.get('http://www.cnbaowen.net/api/geetest/')
element = WebDriverWait(driver, 30, 0.5).until(EC.element_to_be_clickable((By.CLASS_NAME, 'gt_slider_knob')))
if element:
 return element
  except TimeoutException as e:
print('超时错误，继续')
time.sleep(5)

if __name__ == '__main__':
 try:
  count = 6  # 最多识别6次
  driver = webdriver.Chrome()
  # 等待滑动按钮加载完成
  element = main_check_slider(driver)
  while count > 0:
main_check_code(driver,element)
time.sleep(2)
try:
 success_element = (By.CSS_SELECTOR, '.gt_holder .gt_ajax_tip.gt_success')
 # 得到成功标志
 print('suc=',driver.find_element_by_css_selector('.gt_holder .gt_ajax_tip.gt_success'))
 success_images = WebDriverWait(driver, 20).until(EC.presence_of_element_located(success_element))
 if success_images:
  print('成功识别！！！！！！')
  count = 0
  break
except NoSuchElementException as e:
 print('识别错误，继续')
 count -= 1
 time.sleep(2)
  else:
print('too many attempt check code ')
exit('退出程序')
 finally:
  driver.close()

成功识别标志css