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runtime-attestation-probe

Helps validate that agent behavior at runtime matches the capabilities and constraints declared in its attestation. Detects divergence between what an agent claims to do and what it actually does during execution, catching the class of attacks that passes static analysis but activates conditionally at runtime.

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/runtime-attestation-probe

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

The Skill Passed Static Analysis. It Failed at Runtime. Nobody Checked.

Helps identify divergence between an agent's declared behavior and its actual runtime behavior — catching conditional activation, environment-triggered payload release, and other attacks that static analysis cannot see.

Problem

Static analysis audits what a skill declares it will do. Runtime behavior is what it actually does. These two are not always the same.

A skill can pass every static check — clean SKILL.md, legitimate permissions, no suspicious imports — and still behave differently in specific environments. Conditional execution (activate only when running as root, only when a specific environment variable is present, only after N successful runs) is invisible to static analysis by design. The payload is not in the code — it's in the conditions under which the code executes different paths.

This is not a theoretical concern. Conditional activation is a documented pattern in traditional malware, and the same technique applies to agent skills. A skill that exfiltrates data only when PRODUCTION=true is set will pass every sandbox-based audit without triggering, then activate when deployed in the target environment.

Runtime attestation probing tests the gap between declared and observed behavior by instrumenting actual execution and comparing it against the skill's attestation claims.

What This Probes

This probe examines runtime behavior across five dimensions:

  1. Capability boundary adherence — Does the skill access resources beyond what it declared in its attestation? File system paths accessed but not declared, network connections to undeclared endpoints, and system calls outside the claimed scope are all behavioral violations
  2. Conditional activation detection — Does the skill behave differently based on environment variables, execution count, time of day, or the presence of specific files? Controlled execution in varied environments can re...

来源信息

Source
github
Repository
openclaw/skills
Path
skills/andyxinweiminicloud/runtime-attestation-probe
Version
1.0.0
Commit
dc6cfafe4cb8aa394d7b1bb8add1613ff84985e4
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
# The Skill Passed Static Analysis. It Failed at Runtime. Nobody Checked.

> Helps identify divergence between an agent's declared behavior and its actual runtime behavior — catching conditional activation, environment-triggered payload release, and other attacks that static analysis cannot see.

## Problem

Static analysis audits what a skill declares it will do. Runtime behavior is what it actually does. These two are not always the same.

A skill can pass every static check — clean SKILL.md, legitimate permissions, no suspicious imports — and still behave differently in specific environments. Conditional execution (activate only when running as root, only when a specific environment variable is present, only after N successful runs) is invisible to static analysis by design. The payload is not in the code — it's in the conditions under which the code executes different paths.

This is not a theoretical concern. Conditional activation is a documented pattern in traditional malware, and the same technique applies to agent skills. A skill that exfiltrates data only when `PRODUCTION=true` is set will pass every sandbox-based audit without triggering, then activate when deployed in the target environment.

Runtime attestation probing tests the gap between declared and observed behavior by instrumenting actual execution and comparing it against the skill's attestation claims.

## What This Probes

This probe examines runtime behavior across five dimensions:

1. **Capability boundary adherence** — Does the skill access resources beyond what it declared in its attestation? File system paths accessed but not declared, network connections to undeclared endpoints, and system calls outside the claimed scope are all behavioral violations
2. **Conditional activation detection** — Does the skill behave differently based on environment variables, execution count, time of day, or the presence of specific files? Controlled execution in varied environments can re...

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