美团滑块 分析

发布于:2025-04-06 ⋅ 阅读:(12) ⋅ 点赞:(0)

声明
本文章中所有内容仅供学习交流使用,不用于其他任何目的,抓包内容、敏感网址、数据接口等均已做脱敏处理,严禁用于商业用途和非法用途,否则由此产生的一切后果均与作者无关!

逆向过程

距离识别不准简单学习一下,这个小程序、web、app都是公用的。

 

response = requests.post(url, headers=headers, cookies=cookies, data=data)
data0 = json.loads(response.json()['data']["prompt"]['items'][0])['bgImage']
with open(f'./bg.png', 'wb') as fp:
    fp.write(base64.b64decode(data0))

model = YOLO(model='./best.pt', task='detect')
results = model.predict(
    source='./bg.png',
    save=True
)
        cp = execjs.compile(open('run.js', 'r', encoding='utf-8').read())
        result = cp.call('verify', env_data, distance)
        headers = {
            "Accept": "*/*",
            "Accept-Language": "zh-CN,zh;q=0.9",
     
            "Cache-Control": "no-cache",
            "Connection": "keep-alive",

            "Pragma": "no-cache",
            "sec-ch-ua-mobile": "?0",
            "sec-ch-ua-platform": "\"Windows\""
        }
        url = ""
        data = result['data']
        headers["Authencation"] = result['auth']
        headers["TimesTamp"]  = str(env_data["timestamp"])
        point = result['point']
        response = requests.post(url, headers=headers, cookies=cookies, data=data)
        print(response.json())
        data = response.json()

 结果

总结

    1.出于安全考虑,本章未提供完整流程,调试环节省略较多,只提供大致思路,具体细节要你自己还原,相信你也能调试出来。