Cloud Security

Internal Safety Override

• Status: local-only unless explicitly opted into external access.
• Before using network tools, account connectors, browser automation, or APIs, state the destination, data scope, and credential source.
• Do not transmit repository files, secrets, credentials, or private documents by default.
• Audit categories: network, secrets.

Cloud Security

Cloud security posture assessment skill for detecting IAM privilege escalation, public storage exposure, network configuration risks, and infrastructure-as-code misconfigurations. This is NOT incident response for active cloud compromise (see incident-response) or application vulnerability scanning (see security-pen-testing) — this is about systematic cloud configuration analysis to prevent exploitation.

Table of Contents

• Overview
• Cloud Posture Check Tool
• IAM Policy Analysis
• S3 Exposure Assessment
• Security Group Analysis
• IaC Security Review
• Cloud Provider Coverage Matrix
• Workflows
• Anti-Patterns
• Cross-References

Overview

What This Skill Does

This skill provides the methodology and tooling for cloud security posture management (CSPM) — systematically checking cloud configurations for misconfigurations that create exploitable attack surface. It covers IAM privilege escalation paths, storage public exposure, network over-permissioning, and infrastructure code security.

Distinction from Other Security Skills

Prerequisites

Read access to IAM policy documents, S3 bucket configurations, and security group rules in JSON format. For continuous monitoring, integrate with cloud provider APIs (AWS Config, Azure Policy, GCP Security Command Center).

Cloud Posture Check Tool

The cloud_posture_check.py tool runs three types of checks: iam (privilege escalation), s3 (public access), and sg (network exposure). It auto-detects the check type from the config file structure or accepts explicit --check flags.

# Analyze an IAM policy for privilege escalation paths
python3 scripts/cloud_posture_check.py policy.json --check iam --json

# Assess S3 bucket configuration for public access
python3 scripts/cloud_posture_check.py bucket_config.json --check s3 --json

# Check security group rules for open admin ports
python3 scripts/cloud_posture_check.py sg.json --check sg --json

# Run all checks with internet-facing severity bump
python3 scripts/cloud_posture_check.py config.json --check all \
  --provider aws --severity-modifier internet-facing --json

# Regulated data context (bumps severity by one level for all findings)
python3 scripts/cloud_posture_check.py config.json --check all \
  --severity-modifier regulated-data --json

# Pipe IAM policy from AWS CLI
aws iam get-policy-version --policy-arn arn:aws:iam::123456789012:policy/MyPolicy \
  --version-id v1 | jq '.PolicyVersion.Document' | \
  python3 scripts/cloud_posture_check.py - --check iam --json

Exit Codes

IAM Policy Analysis

IAM analysis detects privilege escalation paths, overprivileged grants, public principal exposure, and data exfiltration risk.

Privilege Escalation Patterns

IAM Finding Severity Guide

Least Privilege Recommendations

For every critical or high finding, the tool outputs a least_privilege_suggestion field with specific remediation guidance:

• Replace Action: * with a named list of required actions
• Replace Resource: * with specific ARN patterns
• Use AWS Access Analyzer to identify actually-used permissions
• Separate dangerous action combinations into different roles with distinct trust policies

S3 Exposure Assessment

S3 assessment checks four dimensions: public access block configuration, bucket ACL, bucket policy principal exposure, and default encryption.

S3 Configuration Check Matrix

Recommended S3 Baseline Configuration

{
  "PublicAccessBlockConfiguration": {
    "BlockPublicAcls": true,
    "BlockPublicPolicy": true,
    "IgnorePublicAcls": true,
    "RestrictPublicBuckets": true
  },
  "ServerSideEncryptionConfiguration": {
    "Rules": [{
      "ApplyServerSideEncryptionByDefault": {
        "SSEAlgorithm": "aws:kms",
        "KMSMasterKeyID": "arn:aws:kms:region:account:key/key-id"
      },
      "BucketKeyEnabled": true
    }]
  },
  "ACL": "private"
}

All four public access block settings must be enabled at both the bucket level and the AWS account level. Account-level settings can be overridden by bucket-level settings if not both enforced.

Security Group Analysis

Security group analysis flags inbound rules that expose admin ports, database ports, or all traffic to internet CIDRs (0.0.0.0/0, ::/0).

Critical Port Exposure Rules

High-Risk Database Port Rules

Severity Modifiers

Use --severity-modifier internet-facing when the assessed resource is directly internet-accessible (load balancer, API gateway, public EC2). Use --severity-modifier regulated-data when the resource handles PCI, HIPAA, or GDPR-regulated data. Both modifiers bump each finding's severity by one level.

IaC Security Review

Infrastructure-as-code review catches configuration issues at definition time, before deployment.

IaC Check Matrix

Terraform IAM Policy Example — Finding vs. Clean

# BAD: Will generate critical findings
resource "aws_iam_policy" "bad_policy" {
  policy = jsonencode({
    Version = "2012-10-17"
    Statement = [{
      Effect   = "Allow"
      Action   = "*"
      Resource = "*"
    }]
  })
}

# GOOD: Least privilege
resource "aws_iam_policy" "good_policy" {
  policy = jsonencode({
    Version = "2012-10-17"
    Statement = [{
      Effect   = "Allow"
      Action   = ["s3:GetObject", "s3:PutObject"]
      Resource = "arn:aws:s3:::my-specific-bucket/*"
    }]
  })
}

Full CSPM check reference: references/cspm-checks.md

Cloud Provider Coverage Matrix

Workflows

Workflow 1: Quick Posture Check (20 Minutes)

For a newly provisioned resource or pre-deployment review:

# 1. Export IAM policy document
aws iam get-policy-version --policy-arn ARN --version-id v1 | \
  jq '.PolicyVersion.Document' > policy.json
python3 scripts/cloud_posture_check.py policy.json --check iam --json

# 2. Check S3 bucket configuration
aws s3api get-bucket-acl --bucket my-bucket > acl.json
aws s3api get-public-access-block --bucket my-bucket >> bucket.json
python3 scripts/cloud_posture_check.py bucket.json --check s3 --json

# 3. Review security groups for open admin ports
aws ec2 describe-security-groups --group-ids sg-123456 | \
  jq '.SecurityGroups[0]' > sg.json
python3 scripts/cloud_posture_check.py sg.json --check sg --json

Decision: Exit code 2 = block deployment and remediate. Exit code 1 = schedule remediation within 24 hours.

Workflow 2: Full Cloud Security Assessment (Multi-Day)

Day 1 — IAM and Identity:

1. Export all IAM policies attached to production roles
2. Run cloud_posture_check.py --check iam on each policy
3. Map all privilege escalation paths found
4. Identify overprivileged service accounts and roles
5. Review cross-account trust policies

Day 2 — Storage and Network:

1. Enumerate all S3 buckets and export configurations
2. Run cloud_posture_check.py --check s3 --severity-modifier regulated-data for data buckets
3. Export security group configurations for all VPCs
4. Run cloud_posture_check.py --check sg for internet-facing resources
5. Review NACL rules for network segmentation gaps

Day 3 — IaC and Continuous Integration:

1. Review Terraform/CloudFormation templates in version control
2. Check CI/CD pipeline for IaC security gates
3. Validate findings against references/cspm-checks.md
4. Produce remediation plan with priority ordering (Critical → High → Medium)

Workflow 3: CI/CD Security Gate

Integrate posture checks into deployment pipelines to prevent misconfigured resources reaching production:

# Validate IaC before terraform apply
terraform show -json plan.json | \
  jq '[.resource_changes[].change.after | select(. != null)]' > resources.json
python3 scripts/cloud_posture_check.py resources.json --check all --json
if [ $? -eq 2 ]; then
  echo "Critical cloud security findings — blocking deployment"
  exit 1
fi

# Validate existing S3 bucket before modifying
aws s3api get-bucket-policy --bucket "${BUCKET}" | jq '.Policy | fromjson' | \
  python3 scripts/cloud_posture_check.py - --check s3 \
  --severity-modifier regulated-data --json

Anti-Patterns

1. Running IAM analysis without checking escalation combos — Individual high-risk actions in isolation may appear low-risk. The danger is in combinations: iam:PassRole alone is not critical, but iam:PassRole + lambda:CreateFunction is a confirmed privilege escalation path. Always analyze the full statement, not individual actions.
2. Enabling only bucket-level public access block — AWS S3 has both account-level and bucket-level public access block settings. A bucket-level setting can override an account-level setting. Both must be configured. Account-level block alone is insufficient if any bucket has explicit overrides.
3. Treating --severity-modifier internet-facing as optional for public resources — Internet-facing resources have significantly higher exposure than internal resources. High findings on internet-facing infrastructure should be treated as critical. Always apply --severity-modifier internet-facing for DMZ, load balancer, and API gateway configurations.
4. Checking only administrator policies — Privilege escalation paths frequently originate from non-administrator policies that combine innocuous-looking permissions. All policies attached to production identities must be checked, not just policies with obvious elevated access.
5. Remediating findings without root cause analysis — Removing a dangerous permission without understanding why it was granted will result in re-addition. Document the business justification for every high-risk permission before removing it, to prevent silent re-introduction.
6. Ignoring service account over-permissioning — Service accounts are often over-provisioned during development and never trimmed for production. Every service account in production must be audited against AWS Access Analyzer or equivalent to identify and remove unused permissions.
7. Not applying severity modifiers for regulated data workloads — A high finding in a general-purpose S3 bucket is different from the same finding in a bucket containing PHI or cardholder data. Always use --severity-modifier regulated-data when assessing resources in regulated data environments.

Cross-References