One Agent Sandbox Is Not Enough (multikernel.io)

A new tool called sandlock.mcp has been released, addressing a critical flaw in existing AI agent sandboxes that treat all tools equally, potentially allowing for dangerous cross-tool access. Sandlock.mcp introduces a per-tool-call sandboxing layer where each tool operates within its own isolated environment, enforcing a strict security model that denies all capabilities by default. Permissions must be explicitly granted, preventing tools like web searches from accessing sensitive data or executing unauthorized commands, which is a significant advancement for safeguarding AI systems from prompt injection and other attacks. This innovative approach enhances security by ensuring that tools cannot misuse each other's permissions, protecting sensitive credentials such as API keys or environment variables. For instance, if a malicious search result tempts the agent to execute a command, sandlock.mcp would block unauthorized network access based on predefined capabilities, thus mitigating the risk of data exfiltration. The deployment options include client-side local tools and server-side models, making this tool flexible for various development environments. With its ability to enforce least privilege and detailed permissions control, sandlock.mcp sets a new standard in tool-specific security, paving the way for safer AI applications.