1、前言：
目前很多网站会在正常的账号密码认证之外加一些验证码，以此来明确区分人/机行为，最典型的就是极验滑动验证。（如下图）
这里我们以简单实例说明如何实现自动校验类似验证。
2、步骤：
1）点击验证，弹出验证码图片；
2）操作JS，获取完整验证码图片并截图；
3）操作JS恢复原图，获取带有缺口的验证码图片并截图；
4）对比两张图片所有的像素点，得到要移动的距离；
5）模拟人的行为，把需要拖动的总距离分成一段一段的轨迹；
6）按照轨迹拖动，完成验证；
7）完成登录；
3、准备工作：
1）安装chrome浏览器；
2）配置好python+selenium环境；
3）安装Pillow模块；
4、详细代码：
from selenium import webdriver
from selenium.webdriver import ActionChains # 破解滑动验证码的时候用的 可以拖动图片
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from PIL import Image
from io import BytesIO
import time class AccessCode(object):
def __init__(self,driver):
self.driver = driver
self.wait = WebDriverWait(driver, 20)
self.border = 6 #设置偏差值
def get_position(self):
"""
获取验证码位置
:return: 验证码位置元组
"""
img = self.wait.until(EC.presence_of_element_located((By.CLASS_NAME, 'geetest_window')))
time.sleep(2)
location = img.location
size = img.size
top, bottom, left, right = location['y'], location['y'] + size['height'], location['x'], location['x'] + size['width']
return (top, bottom, left, right) def get_screenshot(self):
"""
获取网页截图
:return: 截图对象
"""
screenshot = self.driver.get_screenshot_as_png()
screenshot = Image.open(BytesIO(screenshot))
return screenshot def get_image1(self,filename):
'''
获取完整验证码图片
:return: 图片对象
'''
time.sleep(0.2)
js_code = '''document.getElementsByClassName('geetest_canvas_fullbg')[0].style.display="block";'''
time.sleep(1)
self.driver.execute_script(js_code)
# 截取图片
top, bottom, left, right = self.get_position()
screenshot = self.get_screenshot()
captcha = screenshot.crop((2 * left, 2 * top, 2 * right, 2 * bottom))
size = 258, 159
captcha.thumbnail(size) # 生成缩略图
captcha.save(filename)
return captcha def get_image2(self,filename):
'''
获取有缺口的验证码图片
:param filename: 图片名称
:return: 有缺口的验证码图片对象
'''
time.sleep(0.2)
js_code = '''document.getElementsByClassName('geetest_canvas_fullbg')[0].style.display="none";'''
self.driver.execute_script(js_code)
time.sleep(1)
# 截取图片
top, bottom, left, right = self.get_position()
screenshot = self.get_screenshot()
captcha = screenshot.crop((2*left, 2*top, 2*right, 2*bottom))
size = 258, 159
captcha.thumbnail(size) # 生成缩略图
captcha.save(filename)
return captcha def get_gap(self,image1, image2):
"""
获取缺口偏移量
:param img1: 不带缺口图片
:param img2: 带缺口图片
:return:缺口偏移量
"""
left = 57
for i in range(left, image1.size[0]):
for j in range(image1.size[1]):
if not self.is_pixel_equal(image1, image2, i, j):
left = i
return left
return left 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
pixel1 = img1.getpixel((x, y))
pixel2 = img2.getpixel((x, y)) for i in range(0, 3):
if abs(pixel1[i] - pixel2[i]) >= 60:
return False
return True 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 * 4 / 5
# 计算间隔
t = 0.2
# 初速度
v = 0
while current < distance:
if current < mid:
# 加速度为正2
a = 2
else:
# 加速度为负3
a = -3
# 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))
return track 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.driver).click_and_hold(slider).perform()
for x in track:
ActionChains(self.driver).move_by_offset(xoffset=x, yoffset=0).perform()
time.sleep(0.5)
ActionChains(self.driver).release().perform() def get_slider(self):
"""
获取滑块
:return: 滑块对象
"""
slider = self.wait.until(EC.element_to_be_clickable((By.CLASS_NAME, 'geetest_slider_button')))
return slider def crack(self):
'''验证操作'''
#1.针对完整的图片进行截取
image1 = self.get_image1('snap_full.png')
#2.针对有缺口的图片进行截取
image2 = self.get_image2('snap.png')
#3.对比两张图片,获取滑动距离
distance = self.get_gap(image1,image2)
#4减去缺口位移
distance -= self.border
#5.获取滑块对象
slider = self.get_slider()
#6.模拟人为滑动轨迹
track = self.get_track(distance)
#7.拖动滑块
self.move_to_gap(slider, track)
time.sleep(0.5)
#8.失败重试
try:
success = self.wait.until(EC.text_to_be_present_in_element((By.XPATH,"//span[@class='geetest_success_radar_tip_content']"), '验证成功'))
if not success:
content = self.driver.find_element_by_xpath("//div[@class='geetest_result_content']").text
if "怪物吃了拼图" in content:
# 如果出现"怪物吃了拼图"字样，需要等待3S后继续操作
time.sleep(3)
if "拖动滑块将悬浮图像正确拼合" in content:
#距离计算错误，刷新图片验证码重试
self.driver.find_element_by_xpath("/html/body/div[3]/div[2]/div[1]/div/div[2]/div/a[2]").click()
self.crack()
else:
#博客园校验成功后自动登录跳转
time.sleep(5)
print("------------登录成功--------------")
except Exception as e:
content = self.driver.find_element_by_xpath("//div[@class='geetest_result_content']").text
if "怪物吃了拼图" in content:
# 如果出现"怪物吃了拼图"字样，需要等待3S后继续操作
time.sleep(3)
if "拖动滑块将悬浮图像正确拼合" in content:
# 距离计算错误，刷新图片验证码重试
self.driver.find_element_by_xpath("/html/body/div[3]/div[2]/div[1]/div/div[2]/div/a[2]").click()
self.crack() if __name__ == '__main__':
chrome_options = webdriver.ChromeOptions()
chrome_options.add_argument('--start-maximized') # 指定浏览器分辨率
chrome_options.add_argument('--disable-gpu') # 谷歌文档提到需要加上这个属性来规避bug
driver = webdriver.Chrome(executable_path=DRIVER_PATH, options=chrome_options) #DRIVER_PATH为chromedriver存放路径，自行变更
crack = AccessCode(driver)
# 1.打开网页
driver.get("https://passport.cnblogs.com/user/signin")
driver.maximize_window() #窗口最大化
# 2.输入用户名,username自行补全
driver.find_element_by_xpath("//input[@id='input1']").send_keys(username)
# 3.输入密码,password自行补全
driver.find_element_by_xpath("//input[@id='input2']").send_keys(password)
# 4.点击登录，弹出验证按钮
driver.find_element_by_xpath("//input[@id='signin']").click()
# 5.点击验证按钮
time.sleep(3)
driver.find_element_by_xpath("//div[@class='modal-content center-block']").click()
driver.find_element_by_xpath("//div[@class='geetest_radar_tip']").click()
# 6.调用验证
crack.crack()