Managing the cyber risk of agentic AI
Summary
AI agents (autonomous software that can take actions and make decisions) should run in sandboxed environments (isolated systems that restrict what resources and networks they can access) to limit damage if they malfunction or are compromised. The source recommends controlling what the agent can connect to, defining sandbox boundaries across execution, network, compute, credentials, and data access, restricting network traffic to only necessary connections, and using multiple layers of isolation to prevent sandbox escapes (when an AI breaks out of its restricted environment).
Solution / Mitigation
The source explicitly recommends several mitigations: (1) Run AI agents in sandboxed environments controlling local and network resource access; (2) For high-risk activities, use isolated, disconnected environments with pre-downloaded tools; (3) Apply sandbox isolations when external communication is necessary; (4) Restrict network access by denying all traffic by default and using allowlists to permit only required connections; (5) For cases requiring internet access, use protocol- or service-aware proxies requiring manual approval; (6) Enforce stronger isolation using multiple layers of control for high-risk activities; (7) Regularly validate configurations to identify weaknesses; (8) Use explicit prompts instructing the agent to not connect to domains outside an allowlist and not attempt to escape the sandbox; (9) Choose mature, trusted sandbox technologies designed specifically to isolate potentially malicious code.
Classification
Affected Vendors
Original source: https://www.ncsc.gov.uk/blogs/managing-the-cyber-risk-of-agentic-ai
First tracked: August 20, 2026 at 08:01 AM
Classified by LLM (prompt v3) · confidence: 85%