Google Cloud and the Foundations of Cloud-Based Digital Forensics

Why Google Cloud Matters for DFIR

Most enterprise workloads still run on-premise, not because cloud platforms are weak, but because migration introduces architectural and operational complexity.

Unlike traditional environments, investigators in Google Cloud cannot rely on physical access, predictable network paths, or full host-level visibility.

Instead, identity events, service-level logs, and resource metadata become the primary evidence sources.

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Google Cloud Global Architecture (DFIR Angle)

Google Cloud is built on regions and zones:

• Regions are geographic areas (e.g., Europe-West, US-Central)

• Zones are isolated deployment areas within regions

Why this matters for DFIR:

• Evidence may be generated in one zone and stored or processed in another

• Data residency and regulatory requirements apply when collecting evidence

• Network paths inside Google Cloud are abstracted and not traceable

You cannot reconstruct packet paths like on-prem networks. Investigations must focus on what happened, who did it, and which resource was affected, not how traffic flowed.

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Core Google Cloud Services for Incident Response & Forensics

These five services provide the highest forensic value during cloud incidents:

1. Identity & Access Management (IAM)

2. Compute Engine (VMs)

3. Cloud Logging

4. Cloud Networking

5. Cloud Storage Buckets

Almost every cloud compromise touches IAM + Logging + Compute

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Google Cloud Resource Hierarchy (Critical for Investigators)

Google Cloud follows a strict hierarchy:

Organization
 └── Folder(s)
      └── Project(s)
           └── Resource(s)

Breakdown

Organization

• Highest level in Google Cloud

• Usually mapped to a company’s domain

• Often linked with Google Workspace

• Central point for IAM and security policies

From a DFIR perspective, this is where global controls and investigation-wide visibility are established.

Folders

• Used to group teams, environments, or functions

• Policies applied here affect everything beneath them

• Can have multiple layers (sub-folders)

DFIR benefit:

• Separate DFIR resources from production

• Apply investigation-specific policies

• Limit blast radius during incidents

Projects

• Where services actually run

• Billing and resource ownership boundary

• Minimum requirement for creating resources

Most compromises are identified inside projects, making them the primary focus during investigations.

Resources

• Compute, Storage, Networking, Logging, etc.

• Inherit permissions and constraints from above

• Generate most forensic artifacts

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IAM vs Policies (Very Important Distinction)

Concept	Controls
IAM	Who can access resources
Policies / Constraints	What resources can do

Example:

• IAM: Who can access a VM

• Policy: Whether logging can be disabled on that VM

Use policies to:

• Prevent attackers from:

  • Disabling logs

  • Creating resources in rogue regions

• Lock down compromised assets instantly

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Google Cloud Organization Benefits for DFIR

What DFIR Teams Can Do Quickly

• Apply constraints globally

  • Allowed VM templates

  • Approved regions only

• Grant DFIR read-only visibility everywhere

• Prevent destructive actions:

  • Turning off logging

  • Deleting evidence

• Isolate compromised projects without downtime

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Key Google Cloud Resources Attackers Abuse

Focus first on these during investigations:

Compute & Platform

• Compute Engine

• App Engine

• Kubernetes Engine

Storage

• Cloud Storage

• Filestore

Ops & Visibility

• Logging

• Monitoring

Networking

• VPC

• Network Security Services

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Data Transfer Pricing (Why DFIR Teams Get Burned)

Important Cost Rules

• Same zone + internal IP → No cost

• Different zone or region → Cost

• VM-to-VM traffic can incur:

  • Egress

  • Response ingress (TCP)

DFIR Best Practices

✅ Place DFIR VMs in:

• Same region

• Same zone

• Use internal IPs only

Avoid:

• Moving evidence across zones

• Exporting raw evidence unnecessarily

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Cost Reduction Options for DFIR

1. Preemptible VMs

• Cheaper

• No guaranteed CPU

• Good for:

  • Distributed tasks

• Bad for:

  • Single-VM processing (e.g., Plaso)

2. Keep Processing Local

• Same zone = free internal traffic

• Faster acquisition & analysis

3. Be Smart with BigQuery

• Charged per bytes processed

• Reduce cost by:

  • Fewer queries

  • Better SQL

  • Documenting results to avoid reruns

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Key Takeaways

• IAM + Policies = Cloud Incident Control Plane

• Folder & project structure directly affects response speed

• Logging enforcement is your strongest defense

• Data movement = cost + legal risk

• DFIR architecture planning matters before incidents happen

--------------------------------------------Dean-----------------------------------------------------------