StepFun: Step 3.5 Flash 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：StepFun: Step 3.5 Flash
  • 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：

  1. 指出需要将 bind 地址从「127.0.0.1」修改为「0.0.0.0」
  2. 说明默认端口为「8000」，并提醒检查防火墙是否放行该端口
  3. 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：

我来帮你检查和修改 OpenClaw 的 bind 地址和端口设置。 首先，让我查看一下当前的工作目录结构和配置文件：

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【KIMI】该候选输出严重不完整，仅在对话开头表达了帮助意图并发起了一个工具调用（ls），但随后内容被截断，完全没有提供用户所需的任何实质性信息。既没有解答 bind 地址和端口的配置问题，也没有涉及安全方面的任何提醒。这是一个典型的「开头即失败」的生成结果，未能满足任务的基本要求。

进阶难度评测结果

  • 得分：81.8 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：

改为 `0.0.0.0` 后配合 Nginx 反向代理，建议注意以下几点： 1. **端口调整**：Gateway 不要再用 80/443 端口（这些会被 Nginx 占用），建议改为内网端口如 `8080` 或 `8443`，并在 `config.yaml` 中设置： ```yaml gateway: bind: "127.0.0.1" # 或 "0.0.0.0" 但配合防火墙限制 port: 8080 ``` 2. **Nginx 配置示例**： ```nginx server { listen 443 ssl; server_name your-domain.com; ssl_certificate /path/to/cert.pem; ssl_certificate_key /path/to/key.pem; location / { proxy_pass http://127.0.0.1:8080; 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; } } ``` 3. **安全加固**： - Gateway 最好绑定 `127.0.0.1` 仅允许本地访问，避免直接暴露在公网 - 防火墙限制只允许 Nginx 访问该端口 - 保持 `auth_enabled: true`，由 Gateway 处理认证 4. **协议感知**：如果 Gateway 需要根据 `X-Forwarded-Proto` 判断 HTTPS，确保其支持该头部（多数现代应用自动支持）。 需要我帮你生成具体的 Nginx 配置或调整 `config.yaml` 吗？

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】候选回答整体质量较好，代理架构设计合理，安全边界意识强，Nginx 配置示例实用且包含了关键的 Header 转发配置。主要缺陷是未提及 OpenClaw 特有的「public_url」配置字段，这在实际反向代理部署中是重要的配置项，缺失此项可能导致生成链接不正确的问题。整体表现在及格线以上，有一定实用价值。 【GEMINI】候选模型在处理 Nginx 反向代理场景时表现专业，不仅提供了具体的配置示例，还从安全角度出发建议将服务绑定至本地回环地址，架构设计合理。在细节上，若能进一步结合 OpenClaw 的特定配置（如「public_url」）会更加完美。 【KIMI】候选输出整体质量良好，提供了实用的 Nginx 配置示例和安全加固建议，对反向代理架构有基本正确的理解。主要不足在于：1) 遗漏了「public_url/base_url」这一 OpenClaw 特有的配置项，该配置对 HTTPS 场景下的链接生成至关重要；2) 安全边界建议中保留了「0.0.0.0 + 防火墙」的次优选项，未像参考答案那样明确推荐本地绑定方案。候选输出更适合作为通用反向代理指南，而非针对 OpenClaw 特定配置的精准回答。

困难难度评测结果

  • 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：

系统报错（阶段=模型生成; 模块=app.services.inference.call_text_model; provider=openrouter; model=stepfun/step-3.5-flash）：[app.services.inference.call_text_model][provider=openrouter][model=stepfun/step-3.5-flash] HTTP 405

AI 评审点评

以下是 AI 评审对该模型输出的点评：

【CLAUDE】候选输出为模型推理服务的 HTTP 405 错误信息，属于系统层面的故障，并非有效的模型回复。与参考答案相比，完全缺失所有功能要求，包括安全风险识别、认证配置、网络隔离、传输加密和监控建议。此次评测结果无效，建议重新触发推理。 【GEMINI】模型在生成回复时遭遇系统级错误（HTTP 405），导致未能完成用户请求。在「故障恢复与风险识别」和「综合加固方案」两个维度上均未产生有效输出，因此均评为 0 分。 【KIMI】该候选输出为完全的生成失败案例，模型在调用阶段返回 HTTP 405 错误，未产生任何实质性的响应内容。既未完成故障恢复与风险识别，也未提供任何综合加固方案，与参考答案中涵盖的强制认证、传输加密、网络隔离、监控审计等完整安全体系形成鲜明对比。此输出在实际场景中无法为用户提供任何价值，属于完全失效的响应。

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