Traditional disk forensics — image everything, analyze in the lab — collapses at enterprise scale. When an intrusion may span three hundred endpoints, you do not need three hundred full disk images; you need the right twelve artifacts from all three hundred machines within the hour. That is forensic triage: fast, targeted collection of high-value evidence, prioritized ahead of full imaging, so scoping decisions stop waiting on terabytes.
Two open-source tools dominate this space and complement each other well. KAPE excels at fast, curated artifact collection on a machine you can reach; Velociraptor turns the same idea into a fleet-wide, query-driven hunting and collection platform.
What to Collect First
The triage set is remarkably consistent across Windows intrusions: the artifacts that answer who ran what, when, and from where.
- ▸Execution evidence: prefetch, Amcache, Shimcache, and SRUM — together they establish which binaries ran and roughly when, even after deletion.
- ▸Persistence surfaces: registry run keys, services, scheduled tasks, WMI event subscriptions, and startup folders — the places attackers anchor themselves.
- ▸Account and lateral movement traces: Security, RDP, and WinRM event logs, plus the authentication artifacts that map movement between hosts.
- ▸User and attacker activity: shellbags, jump lists, LNK files, browser history, and PowerShell logs and transcripts where enabled.
- ▸Filesystem metadata: the NTFS MFT and USN journal, which reconstruct file creation and deletion timelines without imaging the volume.
KAPE packages these as maintained target definitions, so a collection is one command with a targets list and an output path, producing a compact, hash-logged archive in minutes instead of the hours a full image takes. Preserve chain of custody the same as any evidence: hashes at collection time, a record of who collected what and when, and write-once storage.
Scaling with Velociraptor
Velociraptor deploys a lightweight agent and exposes the fleet through VQL, a SQL-like query language over live endpoint state and forensic artifacts. The shift it enables is from collect-then-grep to query-then-collect: ask every endpoint whether a scheduled task references a suspicious path, whether a given SHA-256 exists anywhere on disk, whether prefetch shows a particular tool — and pull full triage packages only from the hosts that answer yes.
That inversion matters most during scoping, the phase where incident cost actually accrues. Instead of imaging machines to learn they are clean, you sweep the estate in minutes and concentrate deep forensics on genuinely affected hosts. Hunts are shareable as artifact definitions, so the community's encoded expertise — hundreds of prebuilt artifacts — becomes your baseline capability, and your own incident learnings become reusable queries rather than tribal knowledge.
Run the server infrastructure ahead of need. Standing Velociraptor up mid-incident is possible — it deploys fast, and that is a legitimate use — but agents already in place mean your first fleet-wide question gets answered in minutes on day zero.
From Collections to Timeline
Collections become answers through timelining. Plaso's log2timeline parses the triage output — event logs, MFT, registry, browser artifacts — into a single super timeline, and Timesketch gives the team a collaborative interface over it: tagging, saved searches, and analyst annotations on one shared sequence of events. A super timeline built only from triage artifacts routinely answers the core scoping questions — initial access time, tooling, lateral movement path — without a single full disk image. Full images are then reserved for the handful of hosts where deleted-file recovery or malware carving justifies the cost, or where legal proceedings demand them.
Building the Capability
1. Define your standard triage set and verify that collection completes in under fifteen minutes on representative hardware. 2. Deploy Velociraptor agents fleet-wide, or pre-stage the offline collector for environments where standing agents are not acceptable. 3. Automate hash-verified delivery of collections into a dedicated evidence store with restricted, audited access. 4. Build the timeline pipeline — collection in, Plaso processing, Timesketch out — as a repeatable script, not a manual lab procedure. 5. Rehearse quarterly: pick a random host, collect, timeline, and have an analyst answer a scoping question end-to-end against the clock. 6. Fold every real incident's useful queries back into your artifact library.
The economics are the point. Triage-first response cuts the most expensive quantity in incident response — analyst hours per host — by an order of magnitude, and it shrinks the uncertainty window during which businesses make their worst decisions: overscoped shutdowns, premature all-clears, guesswork notifications. A team that can query its entire fleet before lunch responds to the same intrusion with a fraction of the disruption, and that capability — assembled in advance from open-source components — is one of the cheapest forms of breach-cost insurance an engineering organization can buy.