Security Incident Response Automation on GCP

The Problem and Why It Mattered

I built an automated incident response system that contains threats, collects evidence, and notifies the right people — all within minutes of an SCC finding, before a human analyst has even opened their laptop. 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 Cloud Functions, Pub/Sub, Security Command Center. 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 Cloud Functions, Pub/Sub, Security Command Center 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: Trigger Layer — Security Command Center

GCP Security Command Center publishes all HIGH and CRITICAL findings to a Pub/Sub topic in real time. A Cloud Function consumes the stream and routes each finding type to the appropriate response handler.

Implementation: Automated Response — 8 Handler Types

Cryptomining: stops VM, snapshots disk, removes external IP, quarantines with restrictive firewall tag. Public Storage bucket: removes public IAM binding, enables uniform bucket-level access. Anomalous IAM change: revokes binding, logs principal activity to forensics bucket. Compromised SA key: disables key, rotates to new key.

Implementation: Automated Response — Continued

SSH brute force: adds attacking IP to Cloud Armor deny rule. Malware hash in container: revokes Binary Authorization attestation, triggering pod eviction. Unused active SA: disables SA. Secret Manager access anomaly: logs recent access and notifies the secret owner.

Implementation: Notification & Evidence Layer

Every response action logged to BigQuery and Cloud Logging with full audit record. PagerDuty incidents for P1 events with timeline of automated actions. Slack messages with direct link to the SCC finding and Cloud Function response log.

Implementation: Results

Mean time to initial containment: 2.3 minutes (fully automated). 8 incident types handled automatically for initial containment. Zero manual containment steps required for 6 of 8 types for full resolution.

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. Mean time to initial containment: 2.3 minutes (fully automated). 8 incident types handled automatically for initial containment. Zero manual containment steps required for 6 of 8 types for full resolution. Claims are limited to the implementation details and outcomes documented in this case study.

Results and Evidence

Mean time to initial containment: 2.3 minutes (fully automated). 8 incident types handled automatically for initial containment. Zero manual containment steps required for 6 of 8 types for full resolution.

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 Cloud Functions, Pub/Sub, Security Command Center. 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.