Prioritised findings
Review concentrates on material changes and credible evidence rather than every informational result.
Security Engineering Case Study
Vulnerability management built for safe remediation.
Greenbone provides repeatable evidence of known weaknesses across the homelab. The workflow compares daily reports, prioritises meaningful changes and keeps remediation deterministic and approval-led.
The Challenge
Find the issues that deserve attention.
Regular scanning is useful only when its findings can be assessed, prioritised and acted on without creating unnecessary change risk. This project turns scan output into a deliberate operational review rather than a list of alerts.
It covers four Linux servers across x86 and ARM hardware, focusing on new or worsened findings with a quality of detection of 70% or above.
Workflow
Evidence through to controlled change
The platform connects scanning, comparison, observability and human approval.
01Greenbone scans
Scheduled scans assess managed hosts.
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02Daily comparison
Reports identify new and worsened findings.
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03Review brief
Findings are explained and prioritised.
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04Approved playbook
Only deterministic remediation is applied.
Capabilities
Security visibility with operational guardrails
Prometheus metrics
Scan health, report recency and finding trends are exposed to the monitoring platform.
AI review briefs
Reports are translated into concise remediation context for informed operator review.
Controlled remediation
Approved playbooks cover APT security updates, Docker production mode, HTTP cookie hardening and unnecessary managed services.
Engineering Outcome
Automation that preserves accountability.
Greenbone supplies the evidence; automation helps make it actionable. Changes are never made simply because a scanner suggested them: approved deterministic playbooks keep the response safe, auditable and repeatable.