Codex sandbox explained: modes, boundaries and approvals
Understand what the Codex sandbox isolates, how its modes differ from approval policy, and what files, writes and network access still require review.
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Policy and controls
Practical policies, control maps and operating rules for responsible AI use.
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Policy and controls guides and articles.
Articles can appear here while keeping their primary category, so related guidance stays discoverable across the library.
15 articles
Codex permissions and workspace access explained
Learn how Codex permissions control local file and network access, how profiles differ from legacy sandbox settings, and where document checks fit.
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Claude Code sandbox explained
Understand how the Claude Code sandbox constrains Bash, how auto-allow differs from permissions, and which file and network exposures still need attention.
Read articleClaude Code permissions and workspace access explained
Learn how Claude Code permissions, modes and working-directory rules govern file access, and how those controls complement its Bash sandbox.
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How to build an internal AI knowledge base
Build an internal AI knowledge base from governed company documents, with a practical blueprint for ownership, retrieval, permissions, testing and upkeep.
Read articleWhat is an AI agent harness? Components and controls
Learn what an AI agent harness is, how its runtime components fit together, and where permissions, observability, context and safety controls belong.
Read articleRAG access control: preserving permissions through retrieval
Design RAG access control that preserves source permissions through indexing, retrieval and generation, with practical patterns and failure checks.
Read articleRAG security: risks, controls and a practical threat model
Threat-model a RAG system across documents, indexing, retrieval and generation, then apply layered controls for permissions, provenance and testing.
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AI acceptable use policy: a practical template
Use this AI acceptable use policy template to define approved tools, prohibited uses, data-handling rules, human review and escalation.
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AI governance framework: a practical guide
Build a practical AI governance framework covering ownership, inventory, risk tiers, approval, monitoring, incidents and improvement.
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AI governance policy: a practical guide
Learn how to write an AI governance policy covering scope, decision rights, risk ownership, approvals, monitoring, exceptions and review.
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AI policy template for organisations
Use this copy-and-adapt AI policy template to define scope, approved tools, data handling, human oversight, disclosure, incidents and review.
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Data classification levels: a practical guide
Learn how data classification levels work, compare common schemes and adapt a practical Public, Internal, Confidential and Restricted model.
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Data classification matrix: map levels to handling controls
Use this data classification matrix template to map Public, Internal, Confidential and Restricted information to practical handling controls.
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Data classification policy template: a practical guide
Use this practical data classification policy template to define levels, ownership, handling rules, exceptions and review for your organisation.
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