Understanding and mitigating the risks of OpenClaw for non-technical users: A practical guide with Skill

Agent Agent Planning Human Agent Interaction AI Safety / AI Ethics PIAAP AVAR
2026年06月09日
OpenClaw 迅速崛起为一种变革性的人工智能(AI)智能体框架,其自主执行复杂、多步骤任务的能力,正持续吸引着日益庞大且多元化的用户群体。然而,这一能力也伴随着显著风险。尽管现有研究已在刻画此类威胁方面取得重要进展,但相关工作主要面向具备较高技术素养的受众,对非技术背景用户而言仍普遍难以理解与获取。而这一群体如今正日益成为社区中占比越来越大、却长期缺乏适配支持的重要组成部分;恰恰是他们,最迫切需要切实可行、通俗易懂的操作指引。为此,我们通过一系列环环相扣的举措,着力降低非技术用户使用 OpenClaw 的安全风险门槛: 首先,我们识别并系统归类了用户在日常使用 OpenClaw 过程中最可能遭遇的七大核心风险,并以平实、清晰的语言逐一阐释,确保非技术用户能够快速理解每类风险的本质及其潜在危害; 其次,针对每一类已识别的风险,我们提炼出相应的一组防御策略,并将其转化为简明、具体、可立即上手的操作步骤,便于用户轻松执行; 第三,为进一步简化防护流程,我们配套开发了一个 OpenClaw 技能(Skill),可自动完成多项关键安全配置,使用户仅需极少人工干预即可有效保护自身系统。 本研究证明:防范智能体带来的安全风险,绝非安全专家的专属领域;非技术用户完全可以通过简单、务实的行动,切实参与到风险防控之中,并发挥不可或缺的积极作用。
OpenClaw has rapidly emerged as a transformative artificial intelligence (AI) agent framework, and its ability to autonomously execute complex, multi-step tasks has attracted an ever-growing and diverse user base. However, this capability comes with significant risks. While existing research has made important strides in characterizing these threats, such work is predominantly directed at technically sophisticated audiences. It remains largely inaccessible to non-technical users. This demographic now makes up an increasingly large and underserved portion of the community, yet it is these very users who most urgently need practical and straightforward guidance. In response, we bridge this gap through a series of interconnected efforts designed to lower the risk barrier for non-technical OpenClaw users. First, we identify and categorize seven core risks that OpenClaw users may encounter in daily usage, explaining each in plain language so that non-technical users can readily grasp the nature and potential consequences of these threats. Second, for each identified risk, we distill a set of corresponding defensive strategies into clear and actionable operational steps that are easy to follow. Third, to make protection even easier, we provide a companion OpenClaw Skill that automates key security configurations, enabling users to safeguard their systems with minimal manual intervention. Through this work, we demonstrate that safeguarding against the risks of intelligent agents need not be the exclusive domain of security experts, and that non-technical users can meaningfully participate in reducing these risks through simple, practical actions.
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