Secure AI Coding Policy Template for Startup and Enterprise Teams
A practical policy structure for preventing security drift in AI-assisted development.
February 14, 2026 · 8 min read
Policy sections that matter
A useful AI coding security policy needs five sections:
- scope (repos, tools, data classes)
- approved patterns (auth, validation, storage)
- forbidden patterns (hardcoded secrets, insecure crypto)
- human review requirements
- exception handling with expiration
Non-negotiables
- No direct secret output in generated code
- All external input validated at boundary
- Privileged operations require explicit auth checks
- Security-sensitive diffs require second reviewer
Assistant configuration
Define mandatory rule files per repo and enforce via CI presence checks. If the policy exists only in docs, it will drift.
Auditability
Require a short AI-use note on high-risk PRs:
- model/tool used
- prompts or rule references
- human verification completed
Keep it lightweight
Policies fail when they are long and untestable. Keep each clause enforceable through code review, lint, tests, or CI automation.