破解滑动验证码案例

步骤一:点击按钮，弹出没有缺口的图片

#步骤二：获取步骤一的图片

#步骤三：点击滑动按钮，弹出带缺口的图片

#步骤四：获取带缺口的图片

#步骤五：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

#步骤六：模拟人的行为习惯（先匀加速拖动后匀减速拖动），把需要拖动的总距离分成一段一段小的轨迹

#步骤七：按照轨迹拖动，完全验证

#步骤八：完成登录

from selenium import webdriver
from selenium.webdriver import ActionChains
from PIL import Image
import time


def get_snap(driver):

    driver.save_screenshot('full_snap.png')
    page_snap_obj = Image.open('full_snap.png')
    return page_snap_obj


def get_image(driver):

    img = driver.find_element_by_class_name('geetest_canvas_img')
    time.sleep(2)
    # 获取图片元素坐标
    location = img.location
    # 获取图片大小
    size = img.size

    left = location['x']
    top = location['y']
    right = left+size['width']
    bottom = top+size['height']

    # 获取截屏图片对象
    page_snap_obj = get_snap(driver)
    # crop处理裁剪后的图片-->获取裁剪后的图片对象
    image_obj = page_snap_obj.crop((left, top, right, bottom))
    # image_obj.show()
    return image_obj


def get_distance(image1, image2):

    start = 57
    threhold = 60

    for i in range(start, image1.size[0]):
        for j in range(image1.size[1]):
            rgb1 = image1.load()[i, j]
            rgb2 = image2.load()[i, j]
            res1 = abs(rgb1[0]-rgb2[0])
            res2 = abs(rgb1[1]-rgb2[1])
            res3 = abs(rgb1[2]-rgb2[2])
            # print(res1,res2,res3)
            if not (res1 < threhold and res2 < threhold and res3 < threhold):
                return i-7
    return i-7


def get_tracks(distance):

    distance += 20 #先滑过一点，最后再反着滑动回来
    v = 0
    t = 0.2
    forward_tracks = []

    current = 0
    mid = distance*3/5
    while current < distance:
        if current < mid:
            a = 2
        else:
            a = -3

        s = v*t+0.5*a*(t**2)
        v = v+a*t
        current += s
        forward_tracks.append(round(s))

    #反着滑动到准确位置
    back_tracks = [-3, -3, -2, -2, -2, -2, -2, -1, -1, -1] #总共等于-20

    return {'forward_tracks': forward_tracks, 'back_tracks': back_tracks}


def crack(driver):  # 破解滑动认证

    # 1、点击按钮，得到没有缺口的图片
    button = driver.find_element_by_class_name('geetest_radar_tip')
    button.click()

    # 2、获取没有缺口的图片
    image1 = get_image(driver)

    # 3、点击滑动按钮，得到有缺口的图片
    button = driver.find_element_by_class_name('geetest_slider_button')
    button.click()

    # 4、获取有缺口的图片
    image2 = get_image(driver)

    # 5、对比两种图片的像素点，找出位移
    distance = get_distance(image1, image2)

    # 6、模拟人的行为习惯，根据总位移得到行为轨迹
    tracks = get_tracks(distance)
    print(tracks)

    # 7、按照行动轨迹先正向滑动，后反滑动
    button = driver.find_element_by_class_name('geetest_slider_button')
    ActionChains(driver).click_and_hold(button).perform()

    # 正向滑动
    for track in tracks['forward_tracks']:
        ActionChains(driver).move_by_offset(xoffset=track, yoffset=0).perform()

    # 开始反向滑动
    time.sleep(0.5)
    for back_track in tracks['back_tracks']:
        ActionChains(driver).move_by_offset(xoffset=back_track, yoffset=0).perform()

    # 小范围震荡一下，进一步迷惑极验后台，这一步可以极大地提高成功率
    ActionChains(driver).move_by_offset(xoffset=-3, yoffset=0).perform()
    ActionChains(driver).move_by_offset(xoffset=3, yoffset=0).perform()

    # 成功后，然后松开手
    time.sleep(0.5)
    ActionChains(driver).release().perform()


def login_cnblogs(username, password):

    driver = webdriver.Chrome(executable_path=r'E:chenweilearning爬虫chromedriver_win32chromedriver.exe')
    try:
        # 1、输入账号密码回车
        driver.implicitly_wait(3)
        driver.get('https://passport.cnblogs.com/user/signin')

        input_username = driver.find_element_by_id('input1')
        input_pwd = driver.find_element_by_id('input2')
        signin = driver.find_element_by_id('signin')

        input_username.send_keys(username)
        input_pwd.send_keys(password)
        signin.click()
        button = driver.find_element_by_class_name('close')
        button.click()
        # 2、破解滑动认证
        crack(driver)

        time.sleep(10)  # 睡时间长一点，确定登录成功
    finally:
        driver.close()

if __name__ == '__main__':
    login_cnblogs(username='xxxxx',password='xxxx')