滑动验证码的识别

时间:2024-03-03 14:11:07

什么是滑动验证码:

 

如何识别滑动验证码:

第一步,模拟点击验证按钮,这一步操作比较简单,我们可以直接用 Selenium 模拟点击按钮

第二步,识别滑动缺口的位置,缺口的四周边缘有明显的断裂边缘,边缘和边缘周围有明显的区别。我们可以实现一个边缘检测算法来找出缺口的位置。
对于极验验证码来说,我们可以利用和原图对比检测的方式来识别缺口的位置,因为在没有滑动滑块之前, 缺口并没有呈现,我们可以同时获取两张图片,
设定一个对比阔值,然后遍历两张图片,找出相同位置像素RGB差距超过此阔值的像素点,那么此像素点的位置就是缺口的位置。

第三步,模拟拖动滑块,这一步看似简单,但其中的坑比较多。极验验证码增加了机器轨迹识别,匀速移动、随机速度移动等方法都不能通过验证,只有
完全模拟人的移动轨迹才可以通过验证。人的移动轨迹一般是先加速后减速,我们需要模拟这个过程才能成功。

 

使用 Python 识别滑动验证码:

import time
from io import BytesIO
from PIL import Image
from selenium import webdriver
from selenium.webdriver import ActionChains
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC

EMAIL = \'xxxxx\'
PASSWORD = \'xxxxx\'
BORDER = 6
INIT_LEFT = 60

class CrackGeetest():
def __init__(self): self.url = \'https://account.geetest.com/login\' self.browser = webdriver.Chrome() self.wait = WebDriverWait(self.browser, 20) self.email = EMAIL self.password = PASSWORD def __del__(self): self.browser.close() def get_geetest_button(self): """ 获取初始验证按钮 :return: """ button = self.wait.until(EC.element_to_be_clickable((By.CLASS_NAME, \'geetest_radar_tip\'))) return button 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_canvas_img\'))) 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.browser.get_screenshot_as_png() screenshot = Image.open(BytesIO(screenshot)) return screenshot 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 get_geetest_image(self, name=\'captcha.png\'): """ 获取验证码图片 :return: 图片对象 """ top, bottom, left, right = self.get_position() print(\'验证码位置\', top, bottom, left, right) screenshot = self.get_screenshot() captcha = screenshot.crop((left, top, right, bottom)) captcha.save(name) return captcha def open(self): """ 打开网页输入用户名密码 :return: None """ self.browser.get(self.url) email = self.wait.until(EC.presence_of_element_located((By.ID, \'email\'))) password = self.wait.until(EC.presence_of_element_located((By.ID, \'password\'))) email.send_keys(self.email) password.send_keys(self.password) def get_gap(self, image1, image2): """ 获取缺口偏移量 :param image1: 不带缺口图片 :param image2: 带缺口图片 :return: """ left = 60 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, image1, image2, 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 = image1.load()[x, y] pixel2 = image2.load()[x, y] threshold = 60 if abs(pixel1[0] - pixel2[0]) < threshold and abs(pixel1[1] - pixel2[1]) < threshold and abs( pixel1[2] - pixel2[2]) < threshold: return True else: return False 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.browser).click_and_hold(slider).perform() for x in track: ActionChains(self.browser).move_by_offset(xoffset=x, yoffset=0).perform() time.sleep(0.5) ActionChains(self.browser).release().perform() def login(self): """ 登录 :return: None """ submit = self.wait.until(EC.element_to_be_clickable((By.CLASS_NAME, \'login-btn\'))) submit.click() time.sleep(10) print(\'登录成功\') def crack(self): # 输入用户名密码 self.open() # 点击验证按钮 button = self.get_geetest_button() button.click() # 获取验证码图片 image1 = self.get_geetest_image(\'captcha1.png\') # 点按呼出缺口 slider = self.get_slider() slider.click() # 获取带缺口的验证码图片 image2 = self.get_geetest_image(\'captcha2.png\') # 获取缺口位置 gap = self.get_gap(image1, image2) print(\'缺口位置\', gap) # 减去缺口位移 gap -= BORDER # 获取移动轨迹 track = self.get_track(gap) print(\'滑动轨迹\', track) # 拖动滑块 self.move_to_gap(slider, track) success = self.wait.until( EC.text_to_be_present_in_element((By.CLASS_NAME, \'geetest_success_radar_tip_content\'), \'验证成功\')) print(success) # 失败后重试 if not success: self.crack() else: self.login() if __name__ == \'__main__\': crack = CrackGeetest() crack.crack()