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Your Agent, Their Asset: A Real-World Safety Analysis of OpenClaw
arXiv β CS AI|Zijun Wang, Haoqin Tu, Letian Zhang, Hardy Chen, Juncheng Wu, Xiangyan Liu, Zhenlong Yuan, Tianyu Pang, Michael Qizhe Shieh, Fengze Liu, Zeyu Zheng, Huaxiu Yao, Yuyin Zhou, Cihang Xie|
π€AI Summary
Researchers conducted the first real-world safety evaluation of OpenClaw, a widely deployed AI agent with extensive system access, revealing significant security vulnerabilities. The study found that poisoning any single dimension of the agent's state increases attack success rates from 24.6% to 64-74%, with even the strongest defenses still vulnerable to 63.8% of attacks.
Key Takeaways
- βOpenClaw's broad system privileges create substantial attack surfaces that existing sandboxed evaluations fail to capture.
- βThe CIK taxonomy (Capability, Identity, Knowledge) provides a framework for analyzing AI agent vulnerabilities across three persistent state dimensions.
- βAttack success rates triple when any single CIK dimension is compromised, affecting all tested AI models including GPT-5.4 and Claude Sonnet 4.5.
- βCurrent defense mechanisms prove inadequate, with the strongest protection still allowing 63.8% attack success rates.
- βThe vulnerabilities appear inherent to the agent architecture itself, requiring systematic safeguards beyond current approaches.
Mentioned in AI
Models
GPT-5OpenAI
ClaudeAnthropic
SonnetAnthropic
OpusAnthropic
GeminiGoogle
#ai-safety#openclaw#security-vulnerabilities#ai-agents#attack-vectors#cik-taxonomy#ai-research#system-access#defense-mechanisms
Read Original βvia arXiv β CS AI
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