用Python代码怎样实现滑块安全验证的效果-群英

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记一次网易易盾滑块验证分析并通过

操作环境

win10 、 mac
Python3.9
selenium、PIL、numpy、scipy、matplotlib

分析

网易易盾滑块验证，就长下面这个样子

具体验证原理有兴趣的可自行查询官方文档：网易易盾开发文档

话不多少，借助之前写阿里云盾滑块和极验滑块的经验，直接上代码，详细可参考：[python3 破解 geetest（极验）的滑块验证码功能]极验滑块验证

解决方案

使用selenium请求url，并触发滑块验证

def open(self):
    # 初始化浏览器
    wait = WebDriverWait(self.driver, 5)
     # 点击对应标签
     self.driver.get(cfg.TEST_URL)
     button = wait.until(EC.element_to_be_clickable((By.CSS_SELECTOR, cfg.HD_SELECOTR)))
     button.click()
     self.tc_item = wait.until(EC.element_to_be_clickable((By.CSS_SELECTOR, cfg.TC_SELECOTR)))
     self.tc_item.click()

     # 得到背景和滑块的item, 以及滑动按钮
     time.sleep(2)
     self.background_item = wait.until(
         EC.presence_of_element_located((By.CSS_SELECTOR, cfg.BG_SELECOTR))
     )
     self.slider_item = wait.until(
         EC.presence_of_element_located((By.CSS_SELECTOR, cfg.HK_SELECOTR))
     )
     self.slider_btn = wait.until(EC.presence_of_element_located((By.CSS_SELECTOR, cfg.HD_BTN)))
     self.offset = cfg.offset
     self.background_path = cfg.background_path
     self.slider_path = cfg.slider_path

获取验证图片并计算滑块距离

def get_images(self):
   """
   获取验证码图片
   :return: 图片的location信息
   """
    url = selenium_item.get_attribute("src")
    if url is not None:
        response = requests.get(url)
        with open(path, "wb") as f:
            f.write(response.content)
        img = Image.open(path).resize(size)
        img.save(path)
    else:
        class_name = selenium_item.get_attribute("class")
        js_cmd = (
            'return document.getElementsByClassName("%s")[0].toDataURL("image/png");'
            % class_name
        )
        im_info = self.driver.execute_script(js_cmd)
        im_base64 = im_info.split(",")[1] 
        im_bytes = base64.b64decode(im_base64)
        with open(path, "wb") as f:
            f.write(im_bytes)
        img = Image.open(path).resize(size)
        img.save(path)

def compute_gap(self, array):
   """
   计算缺口偏移
   """
   grad = np.array(array > 0)
    h, w = grad.shape
    # img_show(grad)
    rows_sum = np.sum(grad, axis=1)
    cols_sum = np.sum(grad, axis=0)
    left, top, bottom = 0, 0, h
    # get the top index
    p = np.max(rows_sum) * 0.5
    for i in range(h):
        if rows_sum[i] > p:
            top = i
            break
    for i in range(h - 1, -1, -1):
        if rows_sum[i] > p:
            bottom = i
            break
    p = np.max(cols_sum) * 0.5
    for i in range(w):
        if cols_sum[i] > p:
            left = i
            break
    return top, bottom + 1, left

生成滑动轨迹

def get_tracks(distance):
    v = random.randint(0, 2)
    t = 1
    tracks = []
    cur = 0
    mid = distance * 0.8
    while cur < distance:
        if cur < mid:
            a = random.randint(2, 4)
        else:
            a = -random.randint(3, 5)
        s = v * t + 0.5 * a * t ** 2
        cur += s
        v = v + a * t
        tracks.append(round(s))
    tracks.append(distance - sum(tracks))
    return tracks

滑动模块

def move_to_gap(self, track):
     """滑动滑块"""
     print('第一步,点击滑动按钮')
     slider = self.wait.until(EC.presence_of_element_located((By.CLASS_NAME, 'geetest_slider_button')))
     ActionChains(self.driver).click_and_hold(slider).perform()
     time.sleep(1)
     print('第二步,拖动元素')
     for track in track:
         ActionChains(self.driver).move_by_offset(xoffset=track, yoffset=0).perform()  # 鼠标移动到距离当前位置（x,y）
         time.sleep(0.0001)