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

Agent Skill

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。

总安装

16,623

周安装

666

GitHub Stars

公开资料未说明

下载量

5,381
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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

简介

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。

SKILL.md

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.*

适合场景

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用户想查找某类 Agent Skill 时

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需要根据任务场景推荐可安装能力包时

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能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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