Sandboxes: A Primer on Containing Things That Don't Want to Be Contained

Sandboxing limits the reach of untrusted, faulty, or nondeterministic code for security, blast-radius reduction, or reproducibility, but no boundary is absolute and each isolates some resources while leaving others exposed. Virtual machines generally provide the strongest practical software boundary by separating kernels, though they impose startup and memory costs and remain vulnerable to hypervisor and hardware flaws; containers offer faster, denser isolation through Linux namespaces, cgroups, seccomp, capabilities, and security policies, but share the host kernel and depend heavily on careful configuration. Runtime approaches such as V8 isolates and WebAssembly are cheaper and faster but rely on the correctness of complex runtimes and host bindings, so robust systems often layer multiple protections. AI-agent sandboxing introduces a different challenge because agents need legitimate access to repositories, tools, APIs, and credentials, making them vulnerable to prompt injection that can redirect their authority. Effective agent protections therefore combine a real compute boundary such as a container or microVM with narrowly scoped filesystems and credentials, egress restrictions, action approvals, reviewable changes, human confirmation for irreversible actions, and detailed audit logs. The central principle is to evaluate what a sandbox actually restricts, what it leaves shared, and how failures are contained and recorded rather than treating any sandbox as complete protection.

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