GCP SCC Custom Findings & Security Posture Management

The Problem and Why It Mattered

I deployed GCP Security Command Center Premium and extended it with four custom security findings for organisation-specific threats — plus a security posture dashboard tracking finding resolution over time and a Jira integration for CRITICAL and HIGH findings. The relevant technical and business risk is the cost of leaving this workflow, control, or product boundary unclear, manual, insecure, or difficult to operate. The case study focuses on the decisions used to make that risk manageable.

Objectives and Success Criteria

• Deliver the capability described in the project objective using a maintainable technical design.
• Make the main workflow, control boundary, and operational responsibilities explicit.
• Produce reviewable implementation evidence without publishing confidential values or customer data.

Requirements and Constraints

The security design had to improve control coverage without exposing sensitive architecture, credentials, customer data, or internal findings in the public record.

My Role and Ownership

I owned the technical design and implementation described in this portfolio record, including the technology choices, core system boundaries, and the documentation of the resulting approach. Related organisational decisions, vendor operations, and formal certification decisions remain outside the scope of this technical case study unless stated explicitly.

Solution Overview

The solution is built around Security Command Center, Cloud Functions, Pub/Sub. Its implementation is organised as the components below so that the architecture, control points, and operating model can be evaluated separately rather than treated as a list of tools.

Architecture and System Design

The public architecture description follows the path from the initiating user, workload, or operator action through the relevant cybersecurity components. Access boundaries, data or state handling, and operational controls are described at a safe level; secrets, private addresses, and client-sensitive implementation details are intentionally omitted.

Technology Decisions and Trade-Offs

I selected Security Command Center, Cloud Functions, Pub/Sub because they support the project objective and make the critical engineering boundaries explicit. The trade-off is operational and platform complexity: the design depends on documented configuration, controlled access, and ongoing review rather than assuming that a managed service or framework removes engineering responsibility.

Implementation Walkthrough

The following implementation notes describe the components that matter most to the project outcome. They are intentionally focused on technical decisions and operating behaviour instead of reproducing entire source files or sensitive configuration.

Implementation: SCC Premium Deployment

Enabled Security Command Center Premium at the Organisation level: Event Threat Detection, Security Health Analytics, Container Threat Detection for GKE, Web Security Scanner for externally accessible apps.

Implementation: Custom Finding 1 — Unapproved Service Account Creation

Any service account created outside Terraform (no managed-by: terraform label) generates a custom MEDIUM finding with creating principal, timestamp, and current IAM bindings.

Implementation: Custom Findings 2 & 3 — Deprecated K8s APIs & Unusual Storage Access

GKE workload using deprecated Kubernetes APIs triggers a LOW finding. A BigQuery scheduled query runs hourly comparing Storage object access counts to the 30-day hourly average — any principal accessing 5× their average triggers a HIGH finding.

Implementation: Custom Finding 4 — Terraform State File Public Exposure

Scans GCS buckets for objects named *.tfstate and checks IAM policies for public access. Creates a CRITICAL finding if any state file is publicly readable — Terraform state files frequently contain secrets.

Implementation: Security Posture Dashboard & Jira Integration

SCC findings export to BigQuery. Tracks mean time to remediate by category and severity, open finding backlog, new vs. resolved findings per week. CRITICAL/HIGH findings auto-create Jira tickets pre-populated with finding details and recommended remediation.

Challenges, Failures and Corrections

This portfolio record does not invent deployment failures, client incidents, or corrective actions that are not supported by the published project evidence. Where operational details are confidential or were not captured for public release, the case study documents the design boundary and lesson instead of presenting an unsupported narrative.

Security, Compliance and Risk

The implementation is described with least privilege, traceability, controlled configuration, and evidence boundaries in mind. Where the project supports a regulated environment, these are technical safeguards and audit-readiness contributions, not a claim that an application or product is independently certified.

Testing, Validation and Evidence

The evidence published for this project is the documented implementation, its stated architecture and controls, and the portfolio record. The published record documents the implemented architecture, the core controls, and the technology choices that can be reviewed without exposing confidential operational data. Claims are limited to the implementation details and outcomes documented in this case study.

Results and Evidence

The published record documents the implemented architecture, the core controls, and the technology choices that can be reviewed without exposing confidential operational data.

What I Learned

This project reinforced that cybersecurity work is not a technology checklist. The durable value comes from making boundaries, trade-offs, ownership, and evidence clear enough for another engineer or stakeholder to review and operate the system responsibly.

What I Would Improve Next

• Expand automated validation around the most important workflow and control boundaries.
• Add or deepen operational evidence, such as dashboards, test artefacts, or an architecture diagram where it is safe to publish one.
• Review the design against the next expected scale, reliability, and governance requirement before extending the system.

Final Takeaway

This cloud security engineering case study addresses a defined technical problem through Security Command Center, Cloud Functions, Pub/Sub. It demonstrates my ability to turn requirements into an explainable design, implement the important controls, and document outcomes and limitations without overstating what the evidence proves.