undermybelt/hermes-skills/aws-iam-prvlg-escltn
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Detect AWS IAM privilege escalation paths using boto3 and Cloudsplaining policy analysis to identify overly permissive
Install
npx vskill@latest install undermybelt/hermes-skills/aws-iam-prvlg-escltnSKILL.md
Detecting AWS IAM Privilege Escalation
Overview
This skill uses boto3 and Cloudsplaining-style analysis to identify IAM privilege escalation paths in AWS accounts. It downloads the account authorization details, analyzes each policy for dangerous permission combinations (iam:PassRole + lambda:CreateFunction, iam:CreatePolicyVersion, sts:AssumeRole), and flags policies that violate least-privilege principles.
When to Use
- When investigating security incidents that require detecting aws iam privilege escalation
- When building detection rules or threat hunting queries for this domain
- When SOC analysts need structured procedures for this analysis type
- When validating security monitoring coverage for related attack techniques
Prerequisites
- Python 3.8+ with boto3 library
- AWS credentials with IAM read-only access (iam:GetAccountAuthorizationDetails)
- Optional: cloudsplaining Python package for HTML report generation
Steps
- Download IAM Authorization Details — Call iam:GetAccountAuthorizationDetails to retrieve all users, groups, roles, and policies
- Analyze Policies for Privilege Escalation — Check each policy for known escalation permission combinations
- Identify Wildcard Resource Policies — Flag policies using Resource: "*" with dangerous actions
- Map Principal-to-Policy Relationships — Build a graph of which principals can access which escalation paths
- Score and Prioritize Findings — Rank findings by severity based on escalation vector type
- Generate Report — Produce structured JSON report with remediation guidance
Expected Output
- JSON report of privilege escalation findings with severity scores
- List of dangerous permission combinations per principal
- Wildcard resource policy audit results
- Remediation recommendations for each finding
Security
- Security scanPassed, 100 of 100Pattern checks on the skill's files.
- Model reviewNot runA model review is scheduled for the next rescan.
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskills/red-teaming/anthropic-cybersecurity-skills/skills/aws-iam-prvlg-escltn/SKILL.md
Popularity
- Repository stars
- 10
- Repository forks
- 2
- 7-day trend score
- 17
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
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