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Auditar políticas IAM de AWS en busca de permisos riesgosos con…

Usa Cloudsplaining cuando un agente necesite marcar rutas de escalada de privilegios y permisos IAM demasiado amplios antes de que un cambio en la política de AWS llegue a producción.

¿Qué es Auditar políticas IAM de AWS en busca de permisos riesgosos con…?

Esta habilidad permite a un agente de IA auditar políticas IAM de AWS utilizando Cloudsplaining, una herramienta de código abierto de Salesforce. Es útil para detectar rutas de escalada de privilegios y permisos excesivos antes de implementar cambios en producción, lo que ayuda a prevenir brechas de seguridad. Soporta cualquier plataforma que permita ejecutar Python y comandos de shell, como Claude Code, Cursor o Codex. Funciona analizando archivos JSON de políticas IAM o los datos de la cuenta de AWS, generando un informe detallado que identifica roles de IAM que pueden ser asumidos por servicios de cómputo (EC2, ECS, EKS, Lambda) y permite excluir falsos positivos mediante un archivo de exclusiones personalizado.

Compatible con~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/agentskillexchange/skills/tree/main/skills/audit-aws-iam-policies-for-risky-permissions-with-cloudsplaining
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Auditar políticas IAM de AWS en busca de permisos riesgosos con Cloudsplaining

Usa Cloudsplaining cuando un agente necesite marcar rutas de escalada de privilegios y permisos IAM demasiado amplios antes de que un cambio en la política de AWS llegue a producción.

Prerrequisitos

Python 3, un archivo JSON de políticas IAM de AWS o datos de la cuenta, y Cloudsplaining.

Instalación

Usa la ruta de instalación oficial o la configuración que coincida con tu entorno:

Requisitos y advertencias de la fuente oficial:

  • Python Version
  • Debes tener los privilegios para ejecutar iam:GetAccountAuthorizationDetails. La política arn:aws:iam::aws:policy/SecurityAudit incluye...
  • default-iam-results.json: Este contiene la salida JSON cruda del informe. Puedes usar este archivo de datos para operar sobre los resultados del escaneo con diversos fines. Por ejemplo, podrías escribir un script en Python que analice...

Notas de uso básico o para comenzar:

  • Informe de ejemplo

  • Cloudsplaining también identifica Roles IAM que pueden ser asumidos por servicios de cómputo de AWS (como EC2, ECS, EKS o Lambda), ya que pueden presentar un mayor riesgo que los roles definidos por el usuario, especialmente si el servicio de cómputo de AWS...

  • También puedes especificar un archivo de exclusiones personalizado para filtrar resultados que sean falsos positivos por diversas razones. Por ejemplo, las políticas de usuario son permisivas por diseño, mientras que los roles del sistema suelen ser más restrictivos...

  • Fuente: https://github.com/salesforce/cloudsplaining

  • Extraído de la documentación oficial: https://raw.githubusercontent.com/salesforce/cloudsplaining/HEAD/README.md

Documentación

Fuente

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

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ActivityWatch Cross-Platform Automated Time Tracker and Producti

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act Local GitHub Actions Runner

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Use AgentClick when an agent should pause before risky commands, plans, drafts, or code changes so a human can inspect, edit, approve, or reject them in a purpose-built browser UI.

Add Claude design-system and accessibility workflows with UX/UI

Use UX/UI Agent Skills when Claude should generate tokens, component specs, accessibility audits, and framework-specific UI code from a repeatable design workflow.

Add executable smoke tests for shell scripts and CLIs before ref

Use Bats-core when an agent needs to turn fragile shell scripts or command-line workflows into something it can verify repeatedly after edits. The agent writes focused Bash tests for success paths, failure paths, and output contracts, then runs them locally or in CI before a refactor, release, or incident fix goes out.

Add graph-backed memory and context retrieval to agent workflows

Use Cognee to ingest project knowledge into graph and vector memory so agents can retrieve durable context across sessions and workflows.

Add IDE-style semantic code navigation and symbol-safe refactors

Give a coding agent symbol-aware lookup, cross-file rename, and structural edit tools before it starts making brittle text-only changes.

Add managed long-term memory to LangGraph agents with LangMem

Give LangGraph agents memory management and search tools so they can store, retrieve, and update durable facts across sessions.

Add multimodal lifelong memory to MCP and Python agents with Sim

Use SimpleMem to store, compress, index, and retrieve text or multimodal memories for agents through MCP or Python integrations.

Add persistent project memory and hook-driven synthesis with Cla

Keep Claude Code sessions grounded in prior decisions, project context, and daily handoff notes instead of starting from zero every time.

Add Postgres-native vector retrieval to agent and RAG workflows

Store embeddings beside application data in Postgres, create vector indexes, and query nearest neighbors for semantic search, RAG, recommendations, or agent memory retrieval.

Address GitHub PR review comments from the current branch with g

Find the open PR for the current branch, gather unresolved review comments, and drive a focused comment-resolution workflow with gh-authenticated context.

Add runtime guardrails to TypeScript agents with VoltAgent

Use VoltAgent to intercept, validate, and enforce input/output policies in TypeScript agent workflows.

Add temporal context memory to agent workflows with Zep

Use Zep as an external context layer for agents that need to store events, assemble temporal graph context, and retrieve relevant memory before model calls.

Adobe Firefly API Batch Image Generator

Calls Adobe Firefly

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