ClawKeeper: Comprehensive Safety Protection for OpenClaw Agents Through Skills, Plugins, and Watchers
Songyang Liu, Chaozhuo Li, Chenxu Wang, Jinyu Hou, Zejian Chen, Litian Zhang, Zheng Liu, Qiwei Ye, Yiming Hei, Xi Zhang, Zhongyuan Wang

TL;DR
ClawKeeper is a comprehensive, multi-layered security framework designed to protect OpenClaw autonomous agents from system-level threats by integrating skills, plugins, and watchers for real-time defense.
Contribution
This paper introduces ClawKeeper, the first holistic security framework for OpenClaw, combining skill, plugin, and watcher protections to address security gaps.
Findings
Effective in mitigating diverse security threats
Reduces risk of data leakage and privilege escalation
Supports real-time intervention and monitoring
Abstract
OpenClaw has rapidly established itself as a leading open-source autonomous agent runtime, offering powerful capabilities including tool integration, local file access, and shell command execution. However, these broad operational privileges introduce critical security vulnerabilities, transforming model errors into tangible system-level threats such as sensitive data leakage, privilege escalation, and malicious third-party skill execution. Existing security measures for the OpenClaw ecosystem remain highly fragmented, addressing only isolated stages of the agent lifecycle rather than providing holistic protection. To bridge this gap, we present ClawKeeper, a real-time security framework that integrates multi-dimensional protection mechanisms across three complementary architectural layers. (1) \textbf{Skill-based protection} operates at the instruction level, injecting structured…
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Taxonomy
TopicsSecurity and Verification in Computing · Advanced Malware Detection Techniques · Adversarial Robustness in Machine Learning
