OpenSandbox vs OpenShell
CNCF-landscape sandbox platform for AI agents: multi-language SDKs, unified API, CLI and MCP over Docker/Kubernetes runtimes — coding agents, GUI agents, evals and RL training. — versus — NVIDIA's safe runtime for autonomous agents: kernel-enforced sandboxes with policy on every file, syscall and connection; credentials injected only for approved endpoints.
Both give agents isolated sandboxes over Docker/Kubernetes with SDKs and a CLI; OpenSandbox centers on a unified sandbox API, OpenShell on per-agent policy enforcement and credential brokering.
| OpenSandbox | OpenShell | |
|---|---|---|
| Stars | 16k | 16k |
| Forks | 1.4k | 1.8k |
| Language | Python | Rust |
| License | Apache-2.0 | Apache-2.0 |
| Last activity | 3 days ago | yesterday |
| Topics | sandboxes, agents, local | sandboxes, security, agents |
| Curated connections | 9 | 4 |
OpenSandbox — the curator's take
The platform play in agent sandboxing: one API over Docker and Kubernetes runtimes, SDKs in multiple languages, an MCP server, and OpenSSF/CNCF hygiene — built for the org that needs sandboxes as shared infrastructure across coding agents, GUI agents, eval harnesses and RL training, not a per-project tool. NOT the isolation ceiling: container runtimes trade the hard KVM boundary microVM sandboxes give you for operational familiarity — if untrusted code is the threat model, weigh a Firecracker-class runtime instead; if platform ergonomics on your existing K8s is the goal, this is the mature option.
OpenShell — the curator's take
Reach for it when agents need real credentials and network but you want least privilege enforced below the agent — declarative policies, secrets the agent never sees, and a prover that flags risky new access for human review. More machinery than throwaway code execution needs; a microVM sandbox API is simpler there. On Kubernetes your CNI must enforce NetworkPolicy; Windows is WSL-only and experimental.