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Agent Skill · 研究检索

secret-safe(秘密保险箱)

用于辅助安全审计、权限检查、凭据风险、认证流程和常见漏洞排查。它适合让 Agent 梳理敏感配置、检查依赖风险、分析鉴权逻辑或生成安全复核清单。使用时不能把工具输出直接当最终结论,涉及密钥、令牌、用户数据或生产系统时,应先确认最小权限、脱敏方式和操作边界。

secret-safe 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 11,293。

总安装 11,432周安装 458GitHub Stars 公开资料未说明下载 3,701核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:secret-safe(秘密保险箱)
来源仓库:https://github.com/brycexbt/secret-safe
安装命令:
openclaw skills install secret-safe
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install secret-safe

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

secret-safe 为 Agent Skill 提供安全的 API 密钥与秘密集中管理机制。适用于需要通过外部服务认证但又不愿在聊天中明文传递凭证的场景。支持多种后端存储(如文件、环境变量、远程 KMS),灵活适配不同部署模式。密钥加载过程需验证来源合法性,防止中间人攻击或配置注入风险。

建议启用访问日志与异常告警,定期检查权限分配是否符合最小特权原则。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install secret-safe;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

secret-safe 怎么安装?

在终端执行 openclaw skills install secret-safe。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

secret-safe 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

secret-safe 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

secret-safe 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

secret-safe 用的人多吗?

公开数据是累计安装 11,432 次,近一周安装 458 次,下载 3,701 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

secret-safe 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
secret-safe

秘密保险箱 · 本页

11,432—接触敏感数据MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
secret-safe
description
>
tags
[security, api-keys, credentials, secrets, audit]
version
1.0.0

Secret-Safe: Secure Credential Handling for Agent Skills

Why this skill exists: Snyk researchers found that 7.1% of all ClawHub skills instruct agents to handle API keys through the LLM context — making every secret an active exfiltration channel. This skill teaches the correct pattern.

The Core Rule

A secret must never appear in:

  • The LLM prompt or system context
  • Claude's response or reasoning
  • Logs, session exports, or .jsonl history files
  • File artifacts created by the agent
  • Error messages echoed back to the user

A secret must only flow through:

  • process.env (injected by OpenClaw before the agent turn)
  • The shell environment of a subprocess the agent spawns
  • A secrets manager CLI (read at subprocess level, not piped back into context)

Pattern 1: Environment Injection (Preferred)

This is OpenClaw's native, secure path. Use it for any skill that needs an API key.

In SKILL.md frontmatter

---
name: my-service-skill
description: Interact with MyService API.
metadata: {"openclaw": {"requires": {"env": ["MY_SERVICE_API_KEY"]}, "primaryEnv": "MY_SERVICE_API_KEY"}}
---

The requires.env gate ensures the skill will not load if the key isn't present — no silent failures, no prompting the user to paste a key mid-conversation.

The primaryEnv field links to skills.entries.<n>.apiKey in openclaw.json, so the user configures it once in their config file, never in chat.

In skill instructions

## Authentication
The API key is available as `$MY_SERVICE_API_KEY` in the shell environment.
Pass it to CLI tools or curl as an environment variable — never echo it or
include it in any output returned to the user.

Example safe curl invocation (instruct the agent to do this)

# CORRECT — key stays in environment, never in command string visible to LLM
MY_SERVICE_API_KEY="$MY_SERVICE_API_KEY" curl -s \
  -H "Authorization: Bearer $MY_SERVICE_API_KEY" \
  https://api.myservice.com/v1/data

Never instruct the agent to do this:

# WRONG — key is visible in LLM context, command history, and logs
curl -H "Authorization: Bearer sk-abc123realkeyhere" https://api.myservice.com/

Pattern 2: Secrets Manager Integration

For production setups or team environments, read secrets from a manager at subprocess level.

Supported managers

ManagerCLIEnv var pattern
macOS Keychainsecurity find-generic-password -wN/A
1Password CLIop read op://vault/item/fieldOP_SERVICE_ACCOUNT_TOKEN
Dopplerdoppler run --DOPPLER_TOKEN
HashiCorp Vaultvault kv get -field=valueVAULT_TOKEN
Bitwarden CLIbw get password item-nameBW_SESSION

Safe shell wrapper pattern

Create a scripts/run-with-secret.sh in your skill:

#!/usr/bin/env bash
# Fetches the secret at subprocess level — never echoes to stdout
SECRET=$(security find-generic-password -s "my-service-api-key" -w 2>/dev/null)
if [ -z "$SECRET" ]; then
  echo "ERROR: Secret 'my-service-api-key' not found in keychain." >&2
  exit 1
fi
export MY_SERVICE_API_KEY="$SECRET"
exec "$@"

The agent runs bash {baseDir}/scripts/run-with-secret.sh <actual-command> — the secret is fetched and injected entirely outside the LLM's view.


Pattern 3: User Setup Flow (first-run)

If the user hasn't configured a key yet, guide them through setup without asking for the key in chat.

Correct setup prompt to give the user:

To use this skill, add your API key to ~/.openclaw/openclaw.json:

  skills:
    entries:
      my-service:
        apiKey: "your-key-here"

Or set it as an environment variable before starting OpenClaw:
  export MY_SERVICE_API_KEY="your-key-here"

Do NOT paste your key into this chat — it will be logged.

Incorrect (never do this):

Please share your API key so I can help you set it up.

Auditing Another Skill for Leaks

When asked to review a SKILL.md for credential safety, check for these patterns:

🔴 Critical — Must Fix

PatternWhy it's dangerous
Instruction to paste key into chatKey goes into LLM context + session logs
echo $API_KEY or print(api_key) in instructionsOutput captured in context
Key interpolated into a string returned to userExposed in response artifact
cat ~/.env or reading raw env filesEntire env dumped into context
Key stored in a file the agent createsCreates a static credential artifact
Instructions tell agent to "remember" the keyKey persists across context window

🟡 Warning — Should Fix

PatternRisk
No requires.env gate in frontmatterSkill silently fails or user is prompted
Logging command output without filteringMay capture keys in error messages
Using set -x in shell scriptsEchoes all commands including key values
Passing key as a positional argumentVisible in ps aux on the host

🟢 Safe Patterns

  • requires.env in frontmatter
  • Key accessed only as $ENV_VAR in shell, never echoed
  • Subprocess scripts that fetch and inject without returning to context
  • Error messages that say "key not found" without printing the value
  • Output filtered through sed/grep before returning to agent

Self-Check Before Publishing a Skill

Run through this checklist before putting any skill on ClawHub:

  • [ ] Does the skill ever ask the user to paste a secret into the conversation?
  • [ ] Does the skill ever echo, print, log, or return a secret value?
  • [ ] Does the skill read a .env file and dump its contents?
  • [ ] Does the skill store a secret in a file artifact?
  • [ ] Are all API key references gated with requires.env in frontmatter?
  • [ ] Do error messages avoid reflecting credential values?
  • [ ] Does any shell script use set -x (which would expose key values)?
  • [ ] Would running clawhub audit {skill-name} pass?

If any box is unchecked, do not publish until fixed.


Quick Reference: Safe vs Unsafe Patterns

# UNSAFE — never write instructions like these:
"Ask the user for their OpenAI API key and use it to call the API."
"Set the Authorization header to Bearer {user_api_key}."
"Store the API key in a variable and use it throughout the session."

# SAFE — write instructions like these:
"The API key is injected as $OPENAI_API_KEY via environment — use it directly."
"Run: OPENAI_API_KEY=$OPENAI_API_KEY curl ..."
"If $OPENAI_API_KEY is not set, print an error and exit — do not ask the user."

Reference Files

  • references/env-injection-examples.md — Full worked examples for popular APIs (OpenAI, Anthropic, GitHub, Stripe, Slack)
  • references/audit-checklist.md — Printable audit checklist for skill authors and reviewers

平台分布

OpenClaw

82.03%
按下载量换算3,036

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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