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publisher-identity-verifier

Helps verify publisher identity integrity in AI agent ecosystems. Detects impersonation, key rotation anomalies, and identity gaps in the trust chain between skill publishers and their claimed identities.

andyxinweiminicloud0 来源安装数☆ 0 仓库 Starsv1.0.0

安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。

SkillHub CLI

skillhub install andyxinweiminicloud/publisher-identity-verifier

打开来源仓库,查看说明和兼容环境后,按来源提供的命令或步骤安装。

将来源链接提供给你的 Agent,让它先读取说明、核对依赖,并向你说明将执行的安装步骤。

查看来源 ↗使用指南

技能说明

You Trusted the Publisher. But Who Verified the Publisher?

Helps identify gaps in publisher identity verification that allow impersonation, key compromise, and identity fraud in agent marketplaces.

Problem

When you install a skill, you trust the publisher. But what proves the publisher is who they claim to be? Most agent marketplaces verify email addresses — not identities. A publisher account can be created in minutes, build reputation over months, then be compromised or sold. The skill ecosystem has no equivalent of code signing certificates, no publisher key transparency logs, and no mechanism to detect when a trusted publisher identity has been taken over. This is the weakest link in agent-to-agent trust: you can audit the code, audit the permissions, audit the tests — but if the publisher behind them isn't who you think, all those audits verify the wrong thing.

What This Checks

This verifier examines publisher identity integrity across five dimensions:

  1. Publication history consistency — Does the publisher's output show a coherent expertise trajectory, or sudden topic shifts that suggest account takeover? A Python tooling publisher that suddenly releases a crypto wallet skill is a signal worth investigating
  2. Key rotation analysis — Tracks signing key changes over time. Normal rotation follows predictable patterns (annual, after security events). Suspicious patterns: key change immediately before a controversial update, key change with no announcement, multiple key changes in short succession
  3. Identity impersonation detection — Scans for publisher names that are typo-squats (e.g., anthroplc vs anthropic), Unicode homoglyphs (e.g., Cyrillic а vs Latin a), or prefix/suffix variations of established publishers
  4. Cross-platform identity correlation — Checks whether the publisher has consistent identity signals across multiple platforms (marketplace profile, code repository, community presence). A publisher...

来源信息

Source
github
Repository
openclaw/skills
Path
skills/andyxinweiminicloud/publisher-identity-verifier
Version
1.0.0
Commit
8ba90ba56864a9407547481f61f44d5e4136714e
分类来源
rules
状态
active
可见性
public

这些信息来自收录时的来源分析,可能滞后;使用前请核对最新来源文件。

来源内容

SKILL.md
# You Trusted the Publisher. But Who Verified the Publisher?

> Helps identify gaps in publisher identity verification that allow impersonation, key compromise, and identity fraud in agent marketplaces.

## Problem

When you install a skill, you trust the publisher. But what proves the publisher is who they claim to be? Most agent marketplaces verify email addresses — not identities. A publisher account can be created in minutes, build reputation over months, then be compromised or sold. The skill ecosystem has no equivalent of code signing certificates, no publisher key transparency logs, and no mechanism to detect when a trusted publisher identity has been taken over. This is the weakest link in agent-to-agent trust: you can audit the code, audit the permissions, audit the tests — but if the publisher behind them isn't who you think, all those audits verify the wrong thing.

## What This Checks

This verifier examines publisher identity integrity across five dimensions:

1. **Publication history consistency** — Does the publisher's output show a coherent expertise trajectory, or sudden topic shifts that suggest account takeover? A Python tooling publisher that suddenly releases a crypto wallet skill is a signal worth investigating
2. **Key rotation analysis** — Tracks signing key changes over time. Normal rotation follows predictable patterns (annual, after security events). Suspicious patterns: key change immediately before a controversial update, key change with no announcement, multiple key changes in short succession
3. **Identity impersonation detection** — Scans for publisher names that are typo-squats (e.g., `anthroplc` vs `anthropic`), Unicode homoglyphs (e.g., Cyrillic `а` vs Latin `a`), or prefix/suffix variations of established publishers
4. **Cross-platform identity correlation** — Checks whether the publisher has consistent identity signals across multiple platforms (marketplace profile, code repository, community presence). A publisher...

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