Transformer论文作者重造龙虾，Rust搓出钢铁版，告别OpenClaw裸奔漏洞

Core Viewpoint - The article discusses the security vulnerabilities associated with OpenClaw and introduces IronClaw as a secure alternative, emphasizing the importance of user data protection and privacy in AI applications [1][2]. Group 1: OpenClaw Vulnerabilities - OpenClaw has been criticized for its severe security issues, including remote code execution and credential exposure, leading to over 25,000 instances being publicly accessible without adequate security controls [7][8]. - The architecture of OpenClaw allows user credentials to be directly sent to LLM providers, raising significant privacy concerns [10][11]. - Users' sensitive information, including employer data, can potentially be accessed by company employees, highlighting a lack of true privacy [11][12]. Group 2: Introduction of IronClaw - IronClaw is a complete rewrite of OpenClaw using Rust, which enhances memory safety and eliminates traditional vulnerabilities like buffer overflows [13][14]. - The security architecture of IronClaw includes four layers of defense: Rust's memory safety, WASM sandbox isolation, encrypted credential storage, and a Trusted Execution Environment (TEE) [15][16][17][18]. - A key feature of IronClaw is that the large language model (LLM) never has access to raw credentials, ensuring that sensitive information remains protected [21][22]. Group 3: Community and Future Developments - The developer community remains cautious due to past vulnerabilities in OpenClaw, but IronClaw's design aims to address these core issues [24]. - Future plans include red team testing and professional security audits to further enhance IronClaw's security [26]. - The article discusses the need for a more intelligent strategy system to combat prompt injection attacks, which could compromise user data [30][31]. Group 4: Vision for User-Owned AI - The creator of IronClaw, Illia Polosukhin, envisions a future where users have complete control over their data and AI agents operate in a trusted environment [42][44]. - NEAR Protocol is building infrastructure to support this vision, including an AI cloud platform and decentralized GPU market [45]. - The concept of user-owned AI includes a marketplace for specialized AI agents, allowing users to automate workflows and tasks [46][49].