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collecting-volatile-evidence-from-a-suspect-host

Collects volatile evidence from a potentially compromised host in correct order of volatility: memory, network state, running processes, logged-on users, and open handles, while preserving integrity and minimizing footprint. Activates for requests to collect volatile evidence, perform live response, or capture host state before shutdown.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

설치 방법 보기

포함된 파일(4)

  • SKILL.md3.4 KB
  • LICENSE340 B
  • references/api-reference.md1.3 KB
  • scripts/analyst.py2.3 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Collecting Volatile Evidence from a Suspect Host

When to Use

  • A host is suspected of compromise and you must capture state that disappears on reboot.
  • You are performing live response before isolating or imaging the machine.
  • You need an ordered, integrity-preserving collection for later analysis.

Do not use this as a substitute for full disk imaging when persistence matters — volatile collection complements, not replaces, a forensic image. And do not reboot before collecting.

Prerequisites

  • Trusted, statically linked collection tools run from external media (not host binaries).
  • Authorization to collect, and a destination on external/write-once media.

Safety & Handling

  • Assume host tools are compromised; use your own trusted binaries to avoid rootkit deception.
  • Hash every artifact at collection time and record actions for chain of custody; minimize changes to the host.

Workflow

Step 1: Follow the order of volatility

Collect most-volatile first (RFC 3227): CPU/registers and cache → RAM → network state and connections → running processes → logged-on users/sessions → open files/handles → then disk.

Step 2: Capture memory first

Acquire a full RAM image with a trusted acquisition tool before anything that alters memory; it is the richest and most perishable source.

Step 3: Snapshot network and process state

Record active connections, listening ports, ARP/DNS cache, running processes with command lines and parent links, and loaded modules.

python scripts/analyst.py manifest ./collection --case IR-42 --host WS01

Step 4: Record users and handles

Capture logged-on users, sessions, scheduled tasks, and open handles/files.

Step 5: Hash, log, and hand off

Hash each artifact, write a collection manifest with timestamps, and transfer to the analysis environment preserving integrity.

Validation

  • Artifacts are collected in order of volatility, memory first, before any reboot.
  • Every artifact has a recorded hash and collection timestamp in the manifest.
  • Trusted external tools were used; host changes are documented.

Pitfalls

  • Rebooting or shutting down before capturing RAM, destroying the best evidence.
  • Using the host's own (possibly trojaned) tools and trusting their output.
  • No hashing/manifest, undermining evidentiary integrity.

References

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