I went with asset inventory and agent-based scanning, talked through something like an EDR or endpoint management tool correlating installed software versions against a CVE feed.
Start by clarifying the scope and constraints (e.g., number of endpoints, OS mix, existing tooling) to show you think before designing. Then propose a multi-layered approach: agent-based inventory collection, centralized analysis against vulnerability databases, and a feedback loop for remediation. Emphasize trade-offs like agent overhead vs. coverage, and how you'd prioritize findings by risk.
Pro tip: Mention that you'd leverage existing endpoint management tools (like Jamf, Intune, or osquery) rather than building from scratch, and that you'd integrate with vulnerability feeds (NVD, vendor advisories) to avoid reinventing the wheel. This shows pragmatism and awareness of real-world constraints.
Ask about scale (number of machines), OS diversity, existing tools, compliance needs, and whether you can install agents. This ensures your solution fits the environment.
Propose an agent-based approach (e.g., osquery, custom agent) to periodically collect installed software, versions, and patch levels. Discuss agentless alternatives (e.g., network scanning) and their trade-offs.
Send collected data to a central service that matches software versions against vulnerability databases (CVE, NVD) and vendor advisories. Enrich with threat intelligence and business context.
Rank findings by severity, exploitability, and asset criticality. Automate remediation where possible (e.g., push updates) and provide dashboards for security teams.
Monitor coverage, false positives, and remediation success. Iterate on the system based on feedback and evolving threats.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.