Safety
Sandboxing
ActiveUpdated: 5 September 2026Published
Key
innovation
Isolating the execution of untrusted code or AI agent actions inside a controlled environment to limit its impact on the host system.
Category
Safety
Abstraction level
Pattern
Operation level
Evaluation (runtime)Tooling
Use cases
Executing code generated by AI agentsRunning untrusted tools (tool use)Evaluating and red-teaming dangerous model behaviorsIsolating code interpreters in LLM products
How it works
Code or a tool is executed in a dedicated runtime with restricted access to the file system, network, memory and system calls. Least-privilege policies, resource limits and operation whitelisting define what the process may do. When finished, the environment is destroyed, guaranteeing no persistent side effects.
Problem solved
Autonomous AI systems that run code and use tools can take unforeseen or harmful actions; without isolation they threaten the integrity and security of the host system.
Strengths & limitations
Strengths
✓Limits the blast radius of faulty or malicious actions
✓Enables safe testing of autonomous agents
✓Enforces the principle of least privilege
Limitations
✗Does not eliminate all attack vectors (sandbox escapes are possible)
✗Introduces performance overhead and complexity
✗Requires careful policy configuration