AI重构前端渗透对抗新范式教学文档<\/h1>

一、AI大模型选择指南<\/h2>

1.1 主流AI大模型对比<\/h3>

Gemini 2.5 Pro<\/strong>：<\/p>

优势：支持100万+上下文，免费使用，综合实力强<\/li>
适用场景：处理大量代码分析<\/li> <\/ul> <\/li>

Claude-3.7-Sonnet<\/strong>：<\/p>

优势：代码编写能力强，具有代码自检功能<\/li>
适用场景：需要生成或修改代码的场景<\/li> <\/ul> <\/li>

GPT-4.1\/4o<\/strong>：<\/p>

优势：响应速度快，综合智商高<\/li>
适用场景：快速解决问题<\/li> <\/ul> <\/li>

DeepSeek<\/strong>：<\/p>

优势：解决复杂问题能力强<\/li>
缺点：响应速度慢<\/li>
适用场景：其他模型无法解决的问题<\/li> <\/ul> <\/li> <\/ul>
1.2 模型选择建议<\/h3>

前端渗透对抗首选Gemini 2.5 Pro（免费+大上下文）<\/li>
代码生成可考虑Claude-3.7-Sonnet<\/li>
快速响应需求选择GPT-4.1\/4o<\/li> <\/ul>
二、手动实践：AI辅助前端渗透对抗<\/h2>
2.1 基本流程<\/h3>

发现目标网站存在前端校验（如sign校验）<\/li>
通过浏览器开发者工具获取所有JS文件<\/li>
将JS代码复制到AI聊天窗口<\/li>
提供明确的提示词（包含需求、参考示例）<\/li>
获取AI生成的对抗脚本<\/li>
测试并验证脚本有效性<\/li> <\/ol>
2.2 典型提示词示例<\/h3>
上述是一个网站的js代码，你现在作为一个测试人员进行接口测试但是重放包的时候，发现出现了服务鉴权失败，你怀疑前端js中有校验，所以检查上方代码，然后找出是哪几个变量再进行校验，进行对抗，最后输出一个mitm的脚本给我（脚本可以参考我下方给你的代码），我直接启动脚本挂上代理就可以正常调用接口 ==之前的mitm代码，给它参考== <\/code><\/pre> 2.3 实战案例<\/h3> 案例1：简单sign校验<\/h4> 发现接口\/user\/login<\/code>存在服务鉴权失败<\/li> 获取4个JS文件内容<\/li> AI精准定位sign校验逻辑<\/li> 生成mitm代理脚本<\/li> 测试验证： mitmdump.exe -p 8081<\/span> -s .\d<\/span>emo.py <\/span><\/span><\/code><\/pre><\/li> Burp设置上游代理验证<\/li> <\/ol> 案例2：复杂sign校验<\/h4> 校验涉及请求头和参数<\/li> POST\/GET方法处理不同<\/li> 提供3个JS文件给AI<\/li> AI生成80行等效代码<\/li> 测试验证通过<\/li> <\/ol> 三、自动化解决方案探索<\/h2> 3.1 基于MCP的方案（不推荐）<\/h3> 问题<\/strong>： API成本高<\/li> 实现复杂<\/li> 谷歌已关闭API免费通道<\/li> MCP稳定性不足（如文件操作可能出错）<\/li> <\/ul> <\/li> <\/ul> 3.2 替代方案：JS自动收集脚本<\/h3> import<\/span> asyncio <\/span><\/span>import<\/span> os <\/span><\/span>from<\/span> playwright.async_api import<\/span> async_playwright <\/span><\/span>import<\/span> aiohttp <\/span><\/span> <\/span><\/span># 配置参数<\/span> <\/span><\/span>TARGET_URL =<\/span> "目标网址"<\/span> <\/span><\/span>OUTPUT_FILE =<\/span> "all.js"<\/span> <\/span><\/span> <\/span><\/span>def<\/span> is_javascript<\/span>(response): <\/span><\/span> ct =<\/span> response.<\/span>headers.<\/span>get("content-type"<\/span>, ""<\/span>) <\/span><\/span> return<\/span> response.<\/span>url.<\/span>endswith(".js"<\/span>) or<\/span> "javascript"<\/span> in<\/span> ct.<\/span>lower() <\/span><\/span> <\/span><\/span>async<\/span> def<\/span> download_js<\/span>(urls, output_file): <\/span><\/span> os.<\/span>makedirs("temp_js"<\/span>, exist_ok=<\/span>True<\/span>) <\/span><\/span> async<\/span> with<\/span> aiohttp.<\/span>ClientSession() as<\/span> session: <\/span><\/span> tasks =<\/span> [] <\/span><\/span> for<\/span> i, url in<\/span> enumerate(set(urls)): # 去重<\/span> <\/span><\/span> tasks.<\/span>append(fetch_and_save(session, url, f<\/span>"temp_js\/<\/span>{<\/span>i}<\/span>.js"<\/span>)) <\/span><\/span> await<\/span> asyncio.<\/span>gather(*<\/span>tasks) <\/span><\/span> <\/span><\/span> with<\/span> open(output_file, "w"<\/span>, encoding=<\/span>"utf-8"<\/span>) as<\/span> merged: <\/span><\/span> for<\/span> i in<\/span> range(len(tasks)): <\/span><\/span> fpath =<\/span> f<\/span>"temp_js\/<\/span>{<\/span>i}<\/span>.js"<\/span> <\/span><\/span> if<\/span> os.<\/span>path.<\/span>exists(fpath): <\/span><\/span> with<\/span> open(fpath, "r"<\/span>, encoding=<\/span>"utf-8"<\/span>, errors=<\/span>"ignore"<\/span>) as<\/span> f: <\/span><\/span> merged.<\/span>write(f<\/span>"<\/span>\n\n<\/span>\/\/ ----- JS 文件: <\/span>{<\/span>fpath}<\/span> -----<\/span>\n<\/span>"<\/span>) <\/span><\/span> merged.<\/span>write(f.<\/span>read()) <\/span><\/span> <\/span><\/span> # 清理临时文件<\/span> <\/span><\/span> for<\/span> fname in<\/span> os.<\/span>listdir("temp_js"<\/span>): <\/span><\/span> fpath =<\/span> os.<\/span>path.<\/span>join("temp_js"<\/span>, fname) <\/span><\/span> try<\/span>: os.<\/span>remove(fpath) <\/span><\/span> except<\/span> Exception<\/span> as<\/span> e: print(f<\/span>"[!] 删除失败：<\/span>{<\/span>fpath}<\/span> - <\/span>{<\/span>e}<\/span>"<\/span>) <\/span><\/span> <\/span><\/span>async<\/span> def<\/span> fetch_and_save<\/span>(session, url, path): <\/span><\/span> try<\/span>: <\/span><\/span> async<\/span> with<\/span> session.<\/span>get(url, timeout=<\/span>10<\/span>) as<\/span> resp: <\/span><\/span> if<\/span> resp.<\/span>status ==<\/span> 200<\/span>: <\/span><\/span> content =<\/span> await<\/span> resp.<\/span>text() <\/span><\/span> with<\/span> open(path, "w"<\/span>, encoding=<\/span>"utf-8"<\/span>) as<\/span> f: <\/span><\/span> f.<\/span>write(content) <\/span><\/span> print(f<\/span>"[+] 已下载: <\/span>{<\/span>url}<\/span>"<\/span>) <\/span><\/span> else<\/span>: print(f<\/span>"[!] 下载失败 <\/span>{<\/span>url}<\/span> (状态码 <\/span>{<\/span>resp.<\/span>status}<\/span>)"<\/span>) <\/span><\/span> except<\/span> Exception<\/span> as<\/span> e: print(f<\/span>"[!] 下载出错 <\/span>{<\/span>url}<\/span>: <\/span>{<\/span>e}<\/span>"<\/span>) <\/span><\/span> <\/span><\/span>async<\/span> def<\/span> main<\/span>(): <\/span><\/span> js_urls =<\/span> [] <\/span><\/span> async<\/span> with<\/span> async_playwright() as<\/span> p: <\/span><\/span> browser =<\/span> await<\/span> p.<\/span>chromium.<\/span>launch(headless=<\/span>True<\/span>) <\/span><\/span> context =<\/span> await<\/span> browser.<\/span>new_context() <\/span><\/span> page =<\/span> await<\/span> context.<\/span>new_page() <\/span><\/span> <\/span><\/span> context.<\/span>on("response"<\/span>, lambda<\/span> response: js_urls.<\/span>append(response.<\/span>url) if<\/span> is_javascript(response) else<\/span> None<\/span>) <\/span><\/span> <\/span><\/span> await<\/span> page.<\/span>goto(TARGET_URL, wait_until=<\/span>"networkidle"<\/span>, timeout=<\/span>30000<\/span>) <\/span><\/span> await<\/span> asyncio.<\/span>sleep(3<\/span>) # 等待异步加载<\/span> <\/span><\/span> await<\/span> browser.<\/span>close() <\/span><\/span> <\/span><\/span> print(f<\/span>"[*] 共捕获到 <\/span>{<\/span>len(js_urls)}<\/span> 个JS链接"<\/span>) <\/span><\/span> await<\/span> download_js(js_urls, OUTPUT_FILE) <\/span><\/span> print(f<\/span>"[✔] 所有JS已合并保存到：<\/span>{<\/span>OUTPUT_FILE}<\/span>"<\/span>) <\/span><\/span> <\/span><\/span>if<\/span> __name__ ==<\/span> "__main__"<\/span>: <\/span><\/span> asyncio.<\/span>run(main()) <\/span><\/span><\/code><\/pre>3.3 使用注意事项<\/h3> iframe中的JS可能无法自动捕获<\/li> 大JS文件可能需要分段处理（直接复制粘贴而非上传附件）<\/li> 复杂防护（如某数动态防护）需要预处理<\/li> <\/ol> 四、最佳实践总结<\/h2> 模型选择<\/strong>：优先使用Gemini 2.5 Pro处理JS分析<\/li> 代码收集<\/strong>：使用自动化脚本收集目标网站JS<\/li> 提示工程<\/strong>：提供明确的需求和参考示例<\/li> 测试验证<\/strong>：使用mitmdump测试代理脚本<\/li> <\/ul> mitmdump.exe -p [<\/span>端口]<\/span> -s [<\/span>脚本路径]<\/span> <\/span><\/span><\/code><\/pre> 配置Burp等工具使用上游代理验证<\/li> <\/ul> <\/li> 异常处理<\/strong>：对于复杂防护系统，考虑分段分析<\/li> 遇到模型限制时尝试其他模型组合<\/li> <\/ul> <\/li> <\/ol> 五、技术限制与注意事项<\/h2> Token限制<\/strong>：大JS文件可能超出模型上下文限制<\/li> 动态防护<\/strong>：高度混淆或动态变化的JS可能需要人工干预<\/li> iframe限制<\/strong>：脚本无法自动捕获iframe中的JS<\/li> 成本考量<\/strong>：避免使用付费API方案<\/li> 结果验证<\/strong>：AI生成的代码必须严格测试验证<\/li> <\/ol> 通过这种方法，可以显著提高前端渗透测试的效率，将原本需要数小时的手动逆向分析缩短为几分钟的AI辅助过程。<\/p>