1 # 导入模块 2 from selenium import webdriver 3 from selenium.webdriver import ActionChains 4 from selenium.webdriver.common.by import By 5 from selenium.webdriver.common.keys import Keys 6 from selenium.webdriver.support import expected_conditions as EC 7 from selenium.webdriver.support.wait import WebDriverWait 8 from PIL import Image 9 import time 10 11 def get_snap(driver): 12 driver.save_screenshot('full_snap.png') 13 page_snap_obj = Image.open('full_snap.png') 14 return page_snap_obj 15 16 def get_image(driver): 17 img = driver.find_element_by_class_name('geetest_canvas_img') 18 time.sleep(2) 19 location = img.location 20 size = img.size 21 print(size) 22 23 left = location['x'] 24 top = location['y'] 25 right = left+size['width'] 26 bottom = top+size['height'] 27 28 page_snap_obj = get_snap(driver) 29 image_obj = page_snap_obj.crop((left, top, right, bottom)) 30 # image_obj.show() 31 return image_obj 32 33 def get_distance(image1, image2): 34 start = 57 35 threhold = 60 36 37 for i in range(start, image1.size[0]): 38 for j in range(image1.size[1]): 39 rgb1 = image1.load()[i, j] 40 rgb2 = image2.load()[i, j] 41 res1 = abs(rgb1[0]-rgb2[0]) 42 res2 = abs(rgb1[1]-rgb2[1]) 43 res3 = abs(rgb1[2]-rgb2[2]) 44 # print(res1,res2,res3) 45 if not (res1 <threhold and res2 <threhold and res3 < threhold): 46 return i - 7 47 return i - 7 48 49 def get_tracks(distance): 50 distance += 20 # 先滑过一点, 最后再反着滑动回来 51 v = 0 52 t = 0.2 53 forward_tracks = [] 54 55 current = 0 56 mid = distance * 3 / 5 57 while current < distance: 58 if current < mid: 59 a = 2 60 else: 61 a = -3 62 63 s = v * t + 0.5 * a * (t**2) 64 v = v + a * t 65 current += s 66 forward_tracks.append(round(s)) 67 68 # 反着滑动到准确位置 69 back_tracks = [-1, -1, -1, -2, -3, -2, -2, -2, -2, -1, -1, -1] # 总共等于 -20 70 71 return {'forward_tracks':forward_tracks, 'back_tracks':back_tracks} 72 73 def crack(driver): # 破解滑动认证 74 # 1.点击按钮,得到没有缺口的图片 75 button = driver.find_element_by_class_name('geetest_radar_tip') 76 button.click() 77 78 # 2.获取没有缺口的图片 79 image1 = get_image(driver) 80 81 # 3.点击滑动按钮,得到有缺口的图片 82 button = driver.find_element_by_class_name('geetest_slider_button') 83 button.click() 84 85 # 4.获取有缺口的图片 86 image2 = get_image(driver) 87 88 # 5.对比两种图片的像素点,找出位移 89 distance = get_distance(image1, image2) 90 91 # 6.模拟人的行为习惯,根据总位移得到的行为轨迹 92 tracks = get_tracks(distance) 93 print(tracks) 94 95 # 7.按照人行动轨迹先正向滑动,后反向滑动 96 button = driver.find_element_by_class_name('geetest_slider_button') 97 ActionChains(driver).click_and_hold(button).perform() 98 99 # 正常人类总是自信满满地开始正向滑动,自信的表现是疯狂加速 100 for track in tracks['forward_tracks']: 101 ActionChains(driver).move_by_offset(xoffset=track, yoffset=0).perform() 102 103 # 结果傻逼了,正常的人类停顿了一下,回过神来发现,卧槽,滑过了,然后开始反向滑动 104 time.sleep(0.3) 105 for back_track in tracks['back_tracks']: 106 ActionChains(driver).move_by_offset(xoffset=back_track, yoffset=0).perform() 107 108 # 小范围震荡一下, 进一步迷惑极验后台, 这一步可以极大的提高成功率 109 time.sleep(0.1) 110 ActionChains(driver).move_by_offset(xoffset=-3, yoffset=0).perform() 111 ActionChains(driver).move_by_offset(xoffset=3, yoffset=0).perform() 112 113 # 成功后,骚包人类总喜欢默默地欣赏一下自己拼图的成果,然后恋恋不舍地松开那只脏手 114 time.sleep(0.5) 115 ActionChains(driver).release().perform() 116 117 def login_cnblogs(username,password): 118 driver = webdriver.Chrome() 119 try: 120 # 1、输入账号密码回车 121 driver.implicitly_wait(3) 122 driver.get('https://passport.cnblogs.com/user/signin') 123 124 input_username = driver.find_element_by_id('input1') 125 input_pwd = driver.find_element_by_id('input2') 126 signin = driver.find_element_by_id('signin') 127 128 input_username.send_keys(username) 129 input_pwd.send_keys(password) 130 signin.click() 131 132 # 2、破解滑动认证 133 crack(driver) 134 135 time.sleep(10) # 睡时间长一点,确定登录成功 136 finally: 137 driver.close() 138 139 140 141 if __name__ == '__main__': 142 login_cnblogs(username='aaaaa',password='aaaaa')