iam-policy-autopilot
Reduces time and security risk in IAM policy creation by generating least-privilege baselines from code analysis, eliminating manual policy drafting and comm…
IAM Policy Autopilot is an open source static code analysis tool that helps you quickly create baseline AWS IAM policies that you can refine as your application evolves. This tool is available as a command-line utility and MCP server for use within AI coding assistants for quickly building IAM policies.
- Generate baseline AWS IAM policies from application code automatically
- Analyze code to identify required AWS permissions before deployment
- Create least-privilege IAM policies faster during development cycles
Reduces time and security risk in IAM policy creation by generating least-privilege baselines from code analysis, eliminating manual policy drafting and common misconfigurations.
AWS platform teams and DevSecOps engineers building or reviewing application IAM policies.
https://github.com/awslabs/iam-policy-autopilot
By awslabs
How to Get It
uvx iam-policy-autopilot # recommended (needs uv); or: pip install iam-policy-autopilot
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
After installing, paste this into Claude:
Help me generate baseline AWS IAM policies from application code automatically
Trust Signals Auto-scanned
Community Pulse Growing
Discussed on Reddit
- Breaking into IAM — Reddit · 39 pts
- Autopilot Hybrid Join - TimeToLive — Reddit · 9 pts
- IAM Policy Autopilot Explained: What It Is, IAM Governance Benefits, How It Work — Reddit · 1 pts
3 mentions across 1 sources
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 366 GitHub stars; contributors unknown; last commit 1d ago; license Apache-2.0.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
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Evaluation
Scored from trust signals (evidence-eval-v1): 366 GitHub stars; contributors unknown; last commit 1d ago; license Apache-2.0.