IronClaw: Unleash Your AI Agent, With Peace of Mind

IronClaw runs agents inside hardware-encrypted enclaves. This ensures that even if the underlying host OS or hypervisor is compromised, the agent's memory and internal state remain encrypted and inaccessible to external processes. This provides a defense-in-depth layer that standard containerized environments cannot match, effectively isolating the agent's execution from the cloud provider's infrastructure.

Instead of passing raw keys to the LLM, IronClaw stores secrets in a hardened vault. The runtime acts as a secure proxy, injecting credentials into outgoing HTTP requests only when the destination URL matches a pre-configured allow-list. This prevents prompt injection attacks from exfiltrating keys, as the LLM never sees the raw secret values, only the result of the authorized request.

The core runtime is built in Rust, leveraging its strict ownership model and borrow checker to eliminate common memory corruption vulnerabilities like buffer overflows or use-after-free errors. By ensuring memory safety at the language level, IronClaw reduces the attack surface for exploits that target the agent's runtime environment, providing a robust foundation for high-stakes automation.

IronClaw enforces strict egress filtering via an AllowList struct. By explicitly defining which endpoints an agent can communicate with, developers prevent unauthorized data exfiltration to malicious servers. The runtime validates every request against this list before applying authentication headers, ensuring that even a compromised agent cannot send sensitive data to an unapproved third-party domain.

The platform utilizes `wasmparser` to validate agent code before execution. By scanning for unsafe operations and ensuring the bytecode conforms to strict safety standards, IronClaw prevents the execution of malicious or malformed agent logic. This automated verification step occurs during deployment, ensuring that only audited and safe code is permitted to run within the TEE.