IronClaw

IronClaw is an open-source alternative to OpenClaw, engineered to run artificial intelligence agents with a defense-in-depth security model. The platform hosts user credentials in an encrypted vault within a Trusted Execution Environment (TEE) on NEAR AI Cloud, injecting them only into pre-approved network endpoints, ensuring the language model (LLM) never accesses the plaintext values. The entire runtime is built in Rust, and every tool executes in its own WebAssembly (Wasm) container, eliminating entire classes of memory safety vulnerabilities.

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• Encrypted Vault. API keys, tokens, and passwords are stored encrypted at rest inside a secure enclave. The AI agent cannot view these values; the system injects them directly into outbound requests at the host level, exclusively for domains or endpoints the user has placed on an allowlist.
• Sandboxed Tools. Every agent skill or tool runs in an isolated WebAssembly (Wasm) container. This container operates with capability-based permissions, has no access to the host filesystem, and enforces strict resource limits, containing any potential compromise.
• Encrypted Enclaves. The entire agent instance runs inside a Trusted Execution Environment (TEE) on NEAR AI Cloud infrastructure. This guarantees that data is encrypted in memory during execution, from boot to shutdown, protecting it even from the cloud provider.
• Leak Detection. All outbound traffic from the instance is analyzed in real-time. If a sequence matching the format of a credential (such as an API key) is detected attempting to exit the environment, the connection is automatically blocked to prevent data exfiltration.
• Built in Rust. The entire IronClaw codebase is written in Rust. This systems programming language guarantees memory safety at compile time, completely eliminating classic vulnerabilities like buffer overflows, use-after-free errors, and double frees.
• Network Allowlisting. The administrator can define a strict list of endpoints (URLs or domains) that tools are permitted to connect to. Any attempt to communicate with a server outside this list is blocked, preventing a malicious tool from "phoning home" to leak information.
• Credential Injection at the Network Boundary. Credentials are not passed to the agent; instead, they are intercepted and injected by the system precisely when an outbound network request is made to an authorized endpoint, ensuring the LLM never has direct access to them.
• Wasm Binary Verification. Before executing any tool, the system validates the WebAssembly binary to ensure it contains no dangerous instructions or unauthorized behaviors, acting as an additional security filter.
• One-Click Deployment. IronClaw is available for instant deployment on NEAR AI Cloud. Upon launch, the instance boots directly inside a Trusted Execution Environment, requiring no manual setup from the user.
• Security by Architecture. Unlike solutions that rely on verbal instructions to the model ("please don't share this key"), IronClaw implements secret protection at the hardware and software architecture level, rendering certain attack vectors (like prompt injections) incapable of accessing credentials.

The history of IronClaw is directly linked to the evolution of OpenClaw and the necessity to address its security risks. OpenClaw, an open-source personal AI agent project with system access capabilities and persistent memory, gained popularity but also exposed users to threats: prompt injections that could dump secrets, malicious skills in community repositories designed to steal credentials, and thousands of instances exposed to the internet. To fundamentally solve these problems, IronClaw was created by the team at NEAR AI, leveraging the company's cryptographically secure infrastructure. The primary goal from its conception was to build a version of an agent similar to OpenClaw, but with a security model that did not rely on the goodwill of the language model. The program's development commenced using the Rust programming language for its memory safety guarantees and performance, and it integrates deeply with NEAR AI Cloud's Trusted Execution Environment (TEE) technology to provide a hardware-verified and encrypted runtime environment.

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