Python破解极验滑动验证码详细步骤
作者:一只小小的寄居蟹
学习python知识越来越多,大家都知道极验验证码应用非常广泛,今天小编就给大家分享Python破解极验滑动验证码的详细步骤,对Python极验滑动验证码相关知识感兴趣的朋友一起看看吧
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
以上就是Python破解极验滑动验证码的详细内容,更多关于Python极验滑动验证码的资料请关注脚本之家其它相关文章!