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Agent Skill · 开发

install-then-update-trap-detector(安装然后更新陷阱检测器)

install-then-update-trap-detector 用于辅助安全审计、权限检查和凭据风险排查,适合在 OpenClaw 中需要复核安全边界、认证流程或敏感配置时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

install-then-update-trap-detector 是开发类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 2,506。

总安装 16,623周安装 666GitHub Stars 公开资料未说明下载 5,381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
1.1.0

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:install-then-update-trap-detector(安装然后更新陷阱检测器)
来源仓库:https://github.com/andyxinweiminicloud/install-then-update-trap-detector
安装命令:
openclaw skills install install-then-update-trap-detector
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 install-then-update-trap-detector

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

用于检测“先安装后更新”类型的恶意攻击模式。识别技能通过初筛后静默植入危险行为的风险。辅助安全审计与供应链完整性验证工作。依赖行为特征库与版本变更比对机制。install-then-update-trap-detector 属于开发类 Skill,可作为该场景下的辅助能力补充。建议定期更新检测规则以覆盖新型变种。

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 install-then-update-trap-detector;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

    它需要需要联网,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

install-then-update-trap-detector 怎么安装?

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

install-then-update-trap-detector 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。

install-then-update-trap-detector 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

install-then-update-trap-detector 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。

install-then-update-trap-detector 用的人多吗?

公开数据是累计安装 16,623 次,近一周安装 666 次,下载 5,381 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。

install-then-update-trap-detector 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

  • 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。
  • 需要处理开发类任务、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

  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
install-then-update-trap-detector

安装然后更新陷阱检测器 · 本页

16,623—需要联网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
install-then-update-trap-detector
description
>
version
1.1.0
metadata
openclaw
requires
bins
[curl, python3]
env
[]
emoji
🪤
agent_card
capabilities
[install-then-update-trap-detection, post-install-backdoor-detection, deferred-malice-identification, chain-of-custody-verification]
attack_surface
[L1, L2]
trust_dimension
attack-surface-coverage
published
clawhub
false
moltbook
false

The Skill Passed Audit. Then It Updated Itself.

Helps identify skills that use the post-install update window as an attack vector — the gap between "passed initial review" and "continuously safe."

Problem

The install-then-update pattern exploits a structural asymmetry in how agent marketplaces work: initial publication receives scrutiny, but subsequent updates often do not. A skill that passes a thorough security review at v1.0 can introduce a backdoor at v1.1 — and agents that installed v1.0 may automatically update without any re-review occurring.

This asymmetry is not a bug in any particular marketplace. It reflects a fundamental tension between two legitimate goals: fast iteration (which requires low-friction updates) and continuous security (which requires re-audit on every change). Most marketplaces resolve this tension in favor of iteration speed, leaving the post-install update window unguarded.

The attack surface is large. An installed skill with automatic updates enabled can receive arbitrary code changes at the next update check. If the update introduces network exfiltration, credential harvesting, or permission scope expansion, the agent operator may not learn about it until after the damage is done — if they learn at all.

What This Detects

This detector examines the install-then-update risk surface across five dimensions:

  1. Update policy transparency — Does the skill declare its update

policy? Skills that accept automatic updates without operator confirmation have a larger attack window than those requiring explicit approval

  1. Behavioral delta on update — When a new version is installed, does

the skill's observable behavior change in ways not declared in the changelog? Undeclared behavioral changes after update are the primary signal of install-then-update exploitation

  1. Permission scope expansion on update — Does the skill request

additional permissions after an update that it did not request at install time? Scope creep across update boundaries is a common pattern in install-then-update attacks

  1. Update-to-publish timing anomalies — Does the update arrive

immediately after a security review period ends, or at a time associated with low operator attention (holidays, weekends, off-hours)? Timing patterns can indicate deliberate exploitation of review gaps

  1. Rollback feasibility — Can the installed skill be cleanly rolled

back to a previously verified version if the update is suspicious? Skills that make rollback difficult or impossible increase the cost of recovery from an install-then-update attack

  1. Chain-of-custody verification (v1.1) — Is each update cryptographically

signed and does it reference the prior version's content hash? A signed, hash-chained update sequence creates a verifiable chain of custody for the skill's evolution. Breaks in the chain — unsigned versions, missing hash references, or hash mismatches — indicate versions where custody cannot be verified. An install-then-update attack that also breaks the hash chain is detectable even without behavioral comparison

How to Use

Input: Provide one of:

  • A skill identifier to assess its update policy and behavioral delta history
  • Two specific versions of a skill to compare for undeclared behavioral changes
  • An agent's installed skill list to assess the combined update-window risk

Output: A trap detection report containing:

  • Update policy transparency score
  • Behavioral delta assessment (declared vs. observed changes)
  • Permission scope expansion history
  • Update timing anomaly flags
  • Rollback feasibility rating
  • Risk verdict: SAFE / MONITOR / ELEVATED / TRAP-PATTERN-DETECTED

Example

Input: Assess install-then-update risk for data-sync-helper v1.0 → v1.2

🪤 INSTALL-THEN-UPDATE TRAP ASSESSMENT

Skill: data-sync-helper
Versions assessed: v1.0 (installed), v1.1, v1.2 (current)
Audit timestamp: 2025-08-20T10:00:00Z

Update policy transparency:
  v1.0 declared: "Updates require operator confirmation" ✅
  v1.1 changed:  Update policy silently removed from docs ⚠️
  v1.2 current:  No update policy declaration found ✗

Behavioral delta assessment:
  v1.0 → v1.1 changelog: "performance improvements"
  Observed behavioral change: Added outbound connection to new endpoint
  → Undisclosed behavioral change detected ⚠️

  v1.1 → v1.2 changelog: "dependency updates"
  Observed behavioral change: No significant change detected
  → Changelog accurate ✅

Permission scope expansion:
  v1.0 requested: file-read (scoped to /data/)
  v1.1 requested: file-read (scope changed to /data/ + /config/) ⚠️
  v1.2 requested: file-read (/data/ + /config/) + network-outbound (new) ⚠️
  → Two permission expansions across update boundary

Update timing:
  v1.0 published: 2025-06-01 (initial release)
  v1.1 published: 2025-07-14 (Sunday, 02:00 UTC — off-hours) ⚠️
  v1.2 published: 2025-08-01 (Friday before a public holiday) ⚠️
  → Both updates published during low-attention windows

Rollback feasibility:
  v1.0 still available in registry: ✅
  Rollback procedure documented: ✗ Not found
  State changes from v1.1+ reversible: Unknown

Risk verdict: TRAP-PATTERN-DETECTED
  data-sync-helper shows four of five trap indicators:
  update policy silently removed, undisclosed behavioral change at v1.1,
  permission expansion across two update boundaries, and updates timed
  to low-attention windows. The combination suggests deliberate exploitation
  of the post-install update window rather than routine maintenance.

Recommended actions:
  1. Disable automatic updates for data-sync-helper immediately
  2. Review all outbound connections from v1.1+ for data exfiltration
  3. Audit config/ directory access introduced in v1.1
  4. Treat v1.1+ as unverified pending manual review
  5. Require explicit operator confirmation for all future updates

Related Tools

  • delta-disclosure-auditor — Checks whether updates publish machine-readable

change records; install-then-update attacks depend on inadequate delta disclosure to avoid detection

  • skill-update-delta-monitor — Monitors for suspicious update patterns;

install-then-update-trap-detector focuses specifically on the install-then-update attack path rather than general update anomalies

  • permission-creep-scanner — Detects permission scope expansion in individual

skills; this tool focuses on scope expansion that occurs across update boundaries

  • transparency-log-auditor — Checks whether signing events are independently

logged; install-then-update attacks are more detectable when every update is recorded in an auditable log

Limitations

Install-then-update trap detection requires access to behavioral data from multiple versions of a skill, which depends on registry version history preservation. Registries that do not retain older versions make behavioral comparison impossible for the full update history. Behavioral delta assessment is necessarily heuristic: the same observable change (an outbound connection) may represent legitimate new functionality or undisclosed malicious behavior, and cannot be distinguished without full code audit. Timing anomalies are signals, not proof — off-hours updates are common for legitimate releases targeting international time zones. The tool helps identify skills that warrant closer investigation, but does not replace manual review of suspicious update content.

v1.1 limitation: Chain-of-custody verification requires registries to support signed updates and content hashing, which most do not yet. Where registries do not preserve cryptographic metadata, chain verification produces no signal. An attacker who controls the registry itself can forge the hash chain.

*v1.1 chain-of-custody verification based on feedback from tobb_sunil (update-chain signing as commitment) in the delta disclosure discussion thread.*

平台分布

OpenClaw

96.42%
按下载量换算5,188

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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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