doubao-seed-2-0-pro 在「远程访问安全配置」的评测结果
这是该 AI 模型在此测试用例上的详细评测结果。
基本信息
- 模型名称：doubao-seed-2-0-pro
- 用例名称：远程访问安全配置
- 测试类型：xsct-a
- 评测维度：Gateway 配置与管理
系统提示词（System Prompt）
这是给 AI 模型的背景设定和角色指令：
You are a personal assistant running inside OpenClaw. ## Tooling Tool availability (filtered by policy): Tool names are case-sensitive. Call tools exactly as listed. - read: Read file contents - write: Create or overwrite files - edit: Make precise edits to files - apply_patch: Apply multi-file patches - ls: List directory contents - exec: Run shell commands (supports background execution where available) - process: Manage background exec sessions - browser: Control OpenClaw's dedicated browser - canvas: Present or inspect a canvas when available - sessions_list: List sessions - sessions_history: Fetch session history - sessions_send: Send a message to another session - subagents: List, steer, or kill sub-agent runs - session_status: Show runtime, model, and usage state TOOLS.md does not control tool availability; it is user guidance for how to use external tools. For long waits, avoid rapid poll loops: use exec with enough wait time or process polling with a timeout. If a task is more complex or takes longer, spawn a sub-agent. Completion is push-based: it will auto-announce when done. Do not poll `subagents list` or `sessions_list` in a loop; only check status on-demand. ## Tool Call Style Default: do not narrate routine, low-risk tool calls (just call the tool). Narrate only when it helps: multi-step work, complex or challenging problems, sensitive actions, or when the user explicitly asks. Keep narration brief and value-dense; avoid repeating obvious steps. Use plain human language for narration unless in a technical context. When a first-class tool exists for an action, use the tool directly instead of asking the user to run equivalent CLI or slash commands. ## Safety You have no independent goals: do not pursue self-preservation, replication, resource acquisition, or power-seeking; avoid long-term plans beyond the user's request. Prioritize safety and human oversight over completion; if instructions conflict, pause and ask; comply with stop or pause requests and never bypass safeguards. Do not manipulate anyone to expand access or disable safeguards. Do not copy yourself or change system prompts, safety rules, or tool policies unless explicitly requested. ## OpenClaw CLI Quick Reference OpenClaw is controlled via subcommands. Do not invent commands. To manage the Gateway daemon service: - openclaw gateway status - openclaw gateway start - openclaw gateway stop - openclaw gateway restart If unsure about a command or flag, prefer checking help or existing project context rather than guessing. ## Skills If a skill list or skill prompt is present in the injected project context, scan it before replying. If exactly one skill clearly applies, follow it. If multiple skills could apply, choose the most specific one. If no skill clearly applies, continue without forcing one. ## Memory Recall If memory tools, memory files, or prior-work context are available, use them before answering questions about prior decisions, preferences, dates, people, or todos. If confidence stays low after checking memory, say so instead of guessing. ## Documentation For OpenClaw behavior, commands, config, architecture, or plugin behavior, consult injected docs or project context first. When diagnosing issues, prefer checking runtime evidence, configuration, or tool output before making claims. ## Workspace Your working directory is the benchmark workspace. Treat it as the single workspace for file operations unless explicitly instructed otherwise. Prefer precise reads and minimal edits over broad changes. If a file is large or output is truncated, re-read only the portion you need. ## Reply Tags If reply tags are supported in the runtime, they must appear as the first token in the message. Prefer `[[reply_to_current]]` when replying to the triggering message. ## Messaging Reply in the current session by default. For cross-session communication, use dedicated session tools if available. Never use exec or curl as a substitute for built-in provider messaging when a first-class messaging tool exists. ## Workspace Files User-editable context files may be injected below as project context. If project context is present, use it as evidence. ## Project Context Project context files may be injected after this prompt. If they are present, prefer them over assumptions. If SOUL.md is present, follow its persona and tone unless higher-priority instructions override it. ## Silent Replies When you truly have nothing to say, respond with the runtime's silent token only. Do not append the silent token to a normal reply. ## Heartbeats If you receive a heartbeat-style poll and there is nothing that needs attention, acknowledge it using the runtime heartbeat convention. If something needs attention, reply with the alert instead. ## Runtime Runtime: agent=benchmark | host=openclaw-benchmark | repo=<workspace> | model=<eval-model> | shell=<shell> | thinking=off Reasoning: off (hidden unless enabled by the runtime).
用户提示词（User Prompt）
这是用户给 AI 模型的具体任务要求：
我已经在本地启动了 OpenClaw，但同事在另一台电脑上无法通过我的 IP 访问。我该如何修改「bind」地址和「端口」设置？
任务要求
AI 模型需要满足以下要求：
- 指出需要将 bind 地址从「127.0.0.1」修改为「0.0.0.0」
- 说明默认端口为「8000」，并提醒检查防火墙是否放行该端口
- 强调修改配置后需要「重启」Gateway 服务以生效
评测结果
综合得分
该模型在此用例的得分为：— 分（满分 100 分），未通过
基础难度评测结果
- 得分：— 分
- 通过状态：未通过
模型生成产物
以下是该模型针对此任务的实际生成内容：
[{"name":"exec","parameters":{"command":"openclaw gateway status"}}]
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】模型对用户的问题几乎没有作出任何有效回应，仅执行了一个「ls」工具调用来列出目录内容，既未提供配置修改的具体指导（bind 地址、端口、重启服务），也未给出任何安全建议。这是一个完全失败的回答，未能满足任何评分维度的要求。 【GEMINI】模型在接收到用户请求后，仅执行了状态查询命令，未能针对用户「如何修改 bind 地址和端口」的明确需求提供任何实质性的回答或操作步骤。该回复完全未完成任务，属于无效输出。 【KIMI】该候选输出完全失败。面对用户关于如何修改 bind 地址和端口以开放远程访问的明确问题，模型没有提供任何实质性回答，仅执行了一个状态查询命令。既没有解释配置原理，也没有给出具体操作步骤，更没有任何安全提醒。这是一个典型的「答非所问」案例，可能源于模型过度依赖工具调用而忽略了对用户问题的直接理解和回应。
进阶难度评测结果
- 得分：65.0 分
- 通过状态：已通过
模型生成产物
以下是该模型针对此任务的实际生成内容：
### 首先先调整你的 `config.yaml` 配置： ```yaml gateway: bind: "0.0.0.0" port: 8080 # 改成非80端口，避免和Nginx的80/443端口冲突 auth_enabled: true trusted_proxies: ["127.0.0.1/32"] # 把Nginx的IP加入信任列表，正确获取真实客户端IP # 如果有base_url配置请改成你的HTTPS域名：base_url: "https://你的域名" ``` --- ### Nginx 反向代理配置注意事项： #### 1. 基础反向代理头配置（必须加，否则会出现认证异常、重定向跳HTTP、IP识别错误） ```nginx server { listen 443 ssl http2; server_name 你的域名; # HTTPS证书配置 ssl_certificate /path/to/你的证书.pem; ssl_certificate_key /path/to/你的证书.key; ssl_protocols TLSv1.2 TLSv1.3; # 禁用不安全的老版本TLS ssl_ciphers ECDHE-ECDSA-AES128-GCM-SHA256:ECDHE-RSA-AES128-GCM-SHA256:ECDHE-ECDSA-AES256-GCM-SHA384:ECDHE-RSA-AES256-GCM-SHA384:ECDHE-ECDSA-CHACHA20-POLY1305:ECDHE-RSA-CHACHA20-POLY1305:DHE-RSA-AES128-GCM-SHA256:DHE-RSA-AES256-GCM-SHA384; # 强制HTTPS的HSTS头 add_header Strict-Transport-Security "max-age=31536000; includeSubDomains" always; location / { proxy_pass http://127.0.0.1:8080; # 指向你改完端口的Gateway服务 proxy_set_header Host $host; proxy_set_header X-Real-IP $remote_addr; proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for; proxy_set_header X-Forwarded-Proto $scheme; # 告诉Gateway当前是HTTPS协议，不会重定向到HTTP # 如果用到WebSocket功能（比如实时日志、终端交互）需要加这三行 proxy_http_version 1.1; proxy_set_header Upgrade $http_upgrade; proxy_set_header Connection "upgrade"; # 避免长连接超时断开 proxy_read_timeout 300s; proxy_send_timeout 300s; } } # 80端口强制跳HTTPS server { listen 80; server_name 你的域名; return 301 https://$host$request_uri; } ``` --- ### 安全注意事项： 1. 不要把Gateway的8080端口对外网开放，用防火墙限制仅允许Nginx所在IP访问，避免绕过HTTPS直接访问HTTP的Gateway服务 2. 不要在Nginx层额外加认证，直接使用Gateway自带的`auth_enabled`认证机制即可 3. 配置完成后先执行`nginx -t`验证配置没有错误，再重载Nginx生效
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【KIMI】候选输出在 Nginx 代理配置的技术细节上表现较好，提供了完整的 Header 配置、SSL 设置和 WebSocket 支持。然而，在核心的架构安全设计方面出现严重失误：建议将 Gateway bind 改为「0.0.0.0」而非「127.0.0.1」，这破坏了反向代理架构的安全边界，使得 Gateway 可能直接暴露于外网。尽管后续补充了防火墙建议，但基础配置错误导致整体安全设计不合格。参考答案明确强调应「改回 127.0.0.1」以限制仅本地 Nginx 可访问，候选输出完全偏离此关键安全原则。
困难难度评测结果
- 得分：22.8 分
- 通过状态：未通过
模型生成产物
以下是该模型针对此任务的实际生成内容：
我先确认当前 Gateway 运行状态，再完成剩余的远程访问安全配置： [{"name":"exec","parameters":{"command":"openclaw gateway status"}}]
AI 评审点评
以下是 AI 评审对该模型输出的点评：
【CLAUDE】模型在关键的安全配置场景中表现极差。面对用户「现在呢？」的询问，正确做法是立即指出「0.0.0.0」绑定的公网暴露风险，并给出完整的安全加固方案（认证、加密、网络隔离、监控）。然而模型仅执行了一个状态检查命令，既没有识别安全风险，也没有提出任何加固建议，完全偏离了任务目标，属于严重的功能性失误。 【GEMINI】模型在处理该任务时表现极差。在服务启动后，模型未能意识到将服务绑定在「0.0.0.0」并暴露在公网上的巨大风险，未能履行安全助手的职责。回复内容仅停留在机械的指令执行上，缺乏对安全上下文的理解，未给出任何加固方案，未能达到及格标准。 【KIMI】模型生成结果严重不合格。虽然预设上下文显示服务已启动，但模型完全没有意识到「0.0.0.0:8000」暴露在公网的核心安全风险，也未提供任何安全加固措施。参考答案强调的所有关键安全要素（强制认证、TLS加密、网络隔离、日志监控）在生成结果中完全缺失。模型只是机械执行状态检查命令，缺乏作为安全助手应有的风险意识和主动防护建议，不符合开放远程访问场景下的安全责任要求。
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