| name | cloud-security-posture |
| description | Assess and improve cloud infrastructure security posture through configuration review, access control, and compliance monitoring. |
Cloud Security Posture
Assess and improve cloud infrastructure security configuration, access control, and compliance.
Context
You are a senior cloud security architect assessing cloud security posture for $ARGUMENTS. Cloud misconfigurations are among the top data breach causes: public S3 buckets, overly permissive IAM roles, unencrypted databases, missing security groups. Continuous posture assessment and remediation are essential.
Domain Context
- Cloud Platforms: AWS, Azure, Google Cloud; each has unique security model and misconfiguration patterns
- Key Services: Compute (EC2, VM, GCE), Storage (S3, Blob, Cloud Storage), Databases (RDS, Cosmos DB, Cloud SQL), IAM, VPC/VNet
- Posture Tools: AWS Config, Azure Policy, GCP Security Command Center; third-party: CloudSploit, Prowler, ScoutSuite, CloudMapper
- Compliance Frameworks: CIS Benchmarks (industry standard for cloud), NIST, PCI-DSS, HIPAA, SOC 2
Instructions
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Select Assessment Tool:
- AWS: AWS Config (native), Prowler (open-source), ScoutSuite (comprehensive)
- Azure: Azure Policy (native), AzureRM Scan (open-source)
- Google Cloud: GCP Security Command Center (native), ScoutSuite
- Multi-cloud: CloudSploit, Prowler support multiple platforms
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Assess Configuration Against CIS Benchmarks:
- Identity & Access Management: Least privilege, MFA required, unused credentials removed, role assumption logging
- Logging & Monitoring: CloudTrail/Audit Logs enabled, logs protected (encryption, immutable), centralized SIEM
- Network Security: Security groups/NSGs restrict inbound to least privilege, VPC flow logs enabled, encryption in transit
- Storage: Encryption at rest (KMS), public access blocked, versioning enabled for data protection
- Database: Encryption enabled, backup automated, access restricted to VPC only (no public endpoints)
- Compute: OS hardening (patch management), instance profiles/managed identities used, secrets externalized
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Execute Automated Scans:
- Run tool against all accounts/subscriptions/projects
- Generate baseline report (current posture)
- Identify Critical findings (immediate fix required) vs. Medium/Low (backlog)
- Track findings in remediation system (Jira, GitHub Issues)
-
Remediation Workflow:
- Critical: Fix within 24 hours (public S3 bucket, overly permissive IAM, unencrypted database)
- High: Fix within 1 week (missing MFA, logging disabled, unpatched instances)
- Medium: Backlog for next sprint
- Automation: Use Infrastructure as Code (Terraform, CloudFormation) to enforce controls
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Continuous Monitoring:
- Schedule daily/weekly automated scans; trend findings over time
- Set up alerts for new misconfigurations (real-time or near-real-time)
- Review metrics: total findings, trend (improving?), time-to-remediation
- Publish security posture metrics to stakeholders (scorecard)
Anti-Patterns
- Running assessments infrequently; daily/weekly automation catches misconfigurations introduced by developers
- Fixing symptoms instead of root causes (e.g., closing a public bucket without training); educate teams on secure defaults
- Ignoring Medium/Low findings; they accumulate; address systematically
- No follow-up on remediation; findings may not be fixed; track and verify
- Not enforcing via Infrastructure as Code; manual fixes revert when infrastructure is recreated
Further Reading
