Python?網(wǎng)易易盾滑塊驗證功能的實現(xiàn)

更新時間：2022年05月11日 08:30:32 作者：拉燈的小手

這篇文章主要介紹了Python?網(wǎng)易易盾滑塊驗證，主要是借助之前寫阿里云盾滑塊和極驗滑塊的經(jīng)驗寫的本文，通過使用selenium請求url，并觸發(fā)滑塊驗證，需要的朋友可以參考下

操作環(huán)境

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

分析

網(wǎng)易易盾滑塊驗證，就長下面這個樣子

具體驗證原理有興趣的可自行查詢官方文檔：網(wǎng)易易盾開發(fā)文檔

話不多少，借助之前寫阿里云盾滑塊和極驗滑塊的經(jīng)驗，直接上代碼，詳細可參考：[python3 破解 geetest（極驗）的滑塊驗證碼功能]極驗滑塊驗證

解決方案

使用selenium請求url，并觸發(fā)滑塊驗證

def open(self):
    # 初始化瀏覽器
    wait = WebDriverWait(self.driver, 5)
     # 點擊對應標簽
     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()

     # 得到背景和滑塊的item, 以及滑動按鈕
     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

獲取驗證圖片并計算滑塊距離

def get_images(self):
   """
   獲取驗證碼圖片
   :return: 圖片的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):
   """
   計算缺口偏移
   """
   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

生成滑動軌跡

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

滑動模塊

def move_to_gap(self, track):
     """滑動滑塊"""
     print('第一步,點擊滑動按鈕')
     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,拖動元素')
     for track in track:
         ActionChains(self.driver).move_by_offset(xoffset=track, yoffset=0).perform()  # 鼠標移動到距離當前位置（x,y）
         time.sleep(0.0001)