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Helps detect skills that behave differently when they sense they are being monitored — catching the class of evasion where conditional activation logic specifically targets attestation and sandbox environments.
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/observer-effect-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。
Helps identify skills that use environment detection to suppress malicious behavior during security review — the attestation evasion technique that passes every check precisely because the checks are visible.
The runtime attestation problem has a second layer: a skill sophisticated enough to execute conditionally based on environment signals is also sophisticated enough to detect that it's being probed and suppress its conditional behavior during the probe.
This is the observer effect applied to security: the act of observing changes what is observed. A skill that can detect sandbox fingerprints (restricted network access, specific hostname patterns, probe-characteristic API call sequences) can present clean behavior during attestation and activate payload delivery only when those fingerprints are absent — meaning only in real production environments.
This is not a theoretical concern. Malware has used VM detection to suppress execution during analysis since the 1990s. The same technique scales to agent skills: check for the probe's characteristic markers, return normal output, resume malicious behavior once the probe exits. A skill that clears attestation by detecting the attestor is not a securely attested skill — it's an adversarially attested skill.
The observer-effect probe attempts to reduce the skill's ability to distinguish probe context from production context by minimizing observable differences between the two.
This probe examines attestation evasion capabilities across five dimensions:
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。
# The Skill Behaves Perfectly When It Knows You're Watching. > Helps identify skills that use environment detection to suppress malicious behavior during security review — the attestation evasion technique that passes every check precisely because the checks are visible. ## Problem The runtime attestation problem has a second layer: a skill sophisticated enough to execute conditionally based on environment signals is also sophisticated enough to detect that it's being probed and suppress its conditional behavior during the probe. This is the observer effect applied to security: the act of observing changes what is observed. A skill that can detect sandbox fingerprints (restricted network access, specific hostname patterns, probe-characteristic API call sequences) can present clean behavior during attestation and activate payload delivery only when those fingerprints are absent — meaning only in real production environments. This is not a theoretical concern. Malware has used VM detection to suppress execution during analysis since the 1990s. The same technique scales to agent skills: check for the probe's characteristic markers, return normal output, resume malicious behavior once the probe exits. A skill that clears attestation by detecting the attestor is not a securely attested skill — it's an adversarially attested skill. The observer-effect probe attempts to reduce the skill's ability to distinguish probe context from production context by minimizing observable differences between the two. ## What This Probes This probe examines attestation evasion capabilities across five dimensions: 1. **Sandbox fingerprint detection** — Does the skill attempt to identify characteristics of a probe environment? Checks for sandbox-specific hostname patterns, reduced network connectivity, probe-characteristic request timing, or the absence of expected production signals 2. **Probe timing sensitivity** — Does the skill's behavior change based on how l...
Search and hire real humans for tasks — photography, delivery, research, and more
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