GHOSTLOGIC ASSUME BREACH · CAPTURE TRUTH
Review with engineering
Reference architecture

A forensic mesh built to survive
compromised endpoints and noisy networks.

GhostLogic is simple on purpose: collectors on endpoints, a hardened ingest edge, and redundant storage layers that assume attackers will eventually get local admin.

High-level layout

At a glance, GhostLogic looks like this in a typical deployment. Exact details will match your infra, but the separation of duties stays the same.

[Endpoints] [Edge / Cloud] [Cold Evidence] ────────── ───────────── ─────────────── • Linux / macOS agents → • GhostLogic Ingest Worker → • R2 object storage • Servers & workstations • Queues for async processing • Offsite / long-term • Containers (optional) • KV for hot metadata • Optional tape / glacier ╲ ╱ ╲ ╱ ╲ Timeline & ╱ ╲ Analytics ╱ ──────────── • D1 SQL for event metadata • Workers AI for threat scoring • Analytics for volume / trends Investigators ───────────── • Read-only dashboards • Exportable timelines • Evidence bundles for legal

Endpoints are treated as disposable witnesses. The ingest edge and storage backbone exist specifically to outlive them.

Key components

  • Endpoint collectors
    Lightweight processes that watch for file activity, process events, network touches, and privileged actions. They ship structured events, not guesses.
  • Ingest worker
    A Cloudflare Worker that validates, normalizes, signs, and routes evidence into the right storage tiers. Nothing gets trusted without being checked.
  • Queues & pipelines
    Decouple capture from analysis. Evidence lands first, then AI and correlation take a shot at making sense of it.
  • Storage tiers
    KV for hot keys, D1 for queryable timelines, R2 for “don’t lose this, ever.” Each with its own retention and access model.
  • Operator surface
    Dashboards and CLI tooling that let DFIR teams replay incidents, carve out exports, and hand off clean packages to legal or clients.

Threat model & design assumptions

GhostLogic is not a SIEM, not an EDR, and not here to win a “who found it first” contest. It’s designed to win the “who can still prove what happened six months later” contest.

  • • Assume endpoints will be compromised, wiped, or reimaged.
  • • Assume some admins will have bad days or bad incentives.
  • • Assume attackers will try to poison logs and AI models.
  • • Assume you will, eventually, be asked to defend the record under oath.

Every part of the architecture exists to make those assumptions survivable.

Want to run this past your architects?

We can walk through trust boundaries, data flows, and failure modes with whoever signs off on “this is allowed in our environment.”

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