Digital Forensics Methodology, Investigation, and Reporting Questions

Situation & goal
I inherit an active incident: attackers used LOLbins for long-term persistence and logging is incomplete. My prioritized plan balances immediate containment, evidence preservation, and full eradication.

Prioritized eradication & validation plan

1. Triage / Containment (minutes–hours)

• Isolate high-confidence infected hosts (network segmentation or host quarantine) but keep images/snapshots for forensics.
• Turn on enhanced logging (Sysmon, PowerShell logging, Process Command Line) centrally before remediation where possible.

2. Hunting (hours)

• Broad hunting queries to find persistence artifacts (examples below).

3. Targeted removal (hours–days)

• Revoke suspicious credentials, disable suspected accounts, remove scheduled tasks/registry Run keys, replace binaries where tampered.
• Use signed, centralized remediation (EDR live response / GPO / Intune) to remove at scale.

4. Validation (days)

• Re-scan endpoints, validate absence of artifacts, review network telemetry, and replay suspicious behavior against endpoint baselines.

5. Hardening & prevention (weeks)

• Block or constrain LOLbins, enforce AppLocker/WDAC, restrict admin rights, enable least privilege, improve telemetry, and implement allowlists.

Hunting queries (examples)

• Sysmon / KQL (Azure Sentinel / Defender for Endpoint)

DeviceProcessEvents
| where FileName in ("bitsadmin.exe","certutil.exe","regsvr32.exe","rundll32.exe","wmic.exe","powershell.exe")
| where ProcessCommandLine contains_any ("/s","/url","/download","/encodedCommand","certutil -decode","Invoke-WebRequest","IEX")
| where Timestamp > ago(14d)

• Splunk SPL

index=main (proc_name="powershell.exe" OR proc_name="regsvr32.exe" OR proc_name="rundll32.exe")
| search (cmdline="*EncodedCommand*" OR cmdline="*-e *" OR cmdline="*IEX*")
| stats count by host, user, cmdline, _time

• Registry and Scheduled Tasks (Windows Event Logs)

DeviceRegistryEvents
| where RegistryKey startswith @"HKEY_LOCAL_MACHINE\Software\Microsoft\Windows\CurrentVersion\Run"
or RegistryKey contains "RunOnce"

Removal steps at scale

• Create curated playbooks: identify artifact types (Scheduled Tasks, Services, Run keys, WMI Event Consumers, DLL search order hijacks, Startup folder, persistence via scripts).
• Use EDR bulk actions:
  • Dump and archive artifact for forensic imaging.
  • Disable scheduled task / service via EDR.
  • Remove offending registry keys and files; quarantine.
  • Rotate credentials and secrets (LSA secrets, service accounts).
• Where EDR unavailable, push signed PowerShell scripts via SCCM/Intune with strict logging enabled.

Validation checks

• Endpoint: verify absence of artifacts; run yara/sigs; confirm process hashes match known-good; ensure telemetry (sysmon events) show no re-creation.
• Network: confirm no callbacks to C2 domains; DNS logs show no suspicious resolves.
• Identity: monitor for anomalous logins; verify no new privileged accounts.
• Timebox and re-scan at 24h, 72h, and 14 days.

Architectural hardening

• Deploy Sysmon with centralized collection and 30–90 day retention; enable Audit Process Creation, CommandLine.
• Enforce application control (AppLocker/WDAC) for critical hosts; allowlist approved LOLbins only with constrained arguments.
• Enforce constrained endpoints for admin activity (jump hosts).
• Block risky scripting at network egress and use web proxy with SSL inspection for binaries downloads.
• Implement Just-In-Time and Just-Enough-Administration for elevated operations.
• Regular purple-team exercises to validate detection of LOLbin techniques.

Trade-offs & rationale

• Immediate isolation reduces spread but risks losing volatile evidence — take memory dumps and images first.
• Aggressive blocking prevents re-infection but may disrupt business; use phased rollout and exceptions handled via change control.

This plan prioritizes evidence preservation, rapid containment, scalable eradication using EDR/GPO, and durable architecture changes to prevent re-establishment.

1) Clarify scope & preserve image

• Verify acquisition metadata (host, OS, timestamp, acquisition tool/hash).
• Work on copies; compute hashes before/after analysis.

2) Triage memory image

• Use Volatility3 / Rekall to list processes, DLLs, threads, handles, network sockets.
• Look for anomalies: injected process (hollowing, suspicious parent/child), mismatched module timestamps, RWX regions.

3) Carve injected code

• Enumerate process VADs / mmapped regions; dump RWX and anonymous regions.
• Use volatility plugins (vadinfo, memmap) then bulk-dump regions.
• Apply yara signatures to dumped blobs; run binwalk and strings to find PE headers or shellcode patterns.
• If no headers, perform entropy analysis to detect compressed/encrypted payloads.

4) Unpack and reconstruct

• If PE present: repair headers (pefile), load in IDA/Ghidra. Resolve relocations using process base and import tables observed in memory.
• If raw shellcode: use capstone to disassemble; identify loader stubs, API resolution (GetProcAddress, LoadLibrary) and reconstruct IAT by emulating or using dynamic in-memory import recovery.
• If packed/obfuscated: identify unpacker stub in-memory, set breakpoints in a sandboxed VM attached to the memory snapshot (or use a live debugger) to dump unpacked image after OEP.

5) Determine functionality

• Static: analyze APIs, strings, config blobs, C2 domains/IPs, crypto routines.
• Dynamic (if safe): execute in controlled lab or emulate extracted payload; observe network behavior, filesystem, process injection routines.
• Map capabilities to MITRE ATT&CK techniques.

6) Attribution indicators

• Compile IOCs: C2, domains, IPs, user-agent, mutexes, PE compile timestamps, code overlaps (YARA), compiler artifacts, language/CRT usage.
• Compare to threat intel (VirusTotal, MISP, public reports). Look for unique strings, encryption keys, protocol formats, or bespoke packers.
• Consider operational patterns: targeting, timing, debug strings, localization hints.

7) Report & remediate

• Document artifacts, reproduce extraction steps, provide IOCs, recommended containment (kill process, block C2), and suggested detection rules (memory scanner signatures, telemetry to capture RWX allocations and anomalous CreateRemoteThread).

Key techniques: VAD/RWX carving, entropy + YARA triage, import/relocation recovery, dynamic unpacking via snapshot-and-dump, mapping to ATT&CK for capability attribution.

Approach summary
I would preserve the volume, extract NTFS metadata, correlate artifacts (MFT, $USNJRNL, $LogFile, $MFTMirr) and recover file content from unallocated space to reconstruct deletion events and detect tampering.

Preservation

• Create a forensically sound bitstream image (write-block, E01/RAW) and record hash (SHA256).
• Work from the image; never modify original.

Artifact extraction & parsing

• Parse $MFT to enumerate records, noting File Reference Numbers (FRN), Sequence Numbers (SN), attribute list, timestamps (Created, Modified, MFT Changed, Accessed), and “In Use” flag.
• Parse $MFTMirr to validate MFT consistency; differences indicate corruption/partial overwrite.
• Parse $USNJRNL to get USN change records (create, delete, rename, data modification) with timestamps and parent FRNs.
• Parse $LogFile (NTFS transactional log) to reconstruct low-level metadata updates and order of operations (VSC records, redo/undo).
• Carve unallocated space and slack for file contents and attribute records (use bulk_extractor, scalpel, photorec, or TSK icat).

Correlation & reconstruction

• Map FRN + SN pair: a deleted file often shows same FRN with incremented SN when entry reused. Use SN to link previous incarnation.
• Cross-check MFT timestamps with USNJRNL entries and LogFile transactions to sequence events. USN entries provide event order; LogFile gives atomic operation details (e.g., file record deallocation).
• Use MFTMirr to detect partial MFT record overwrites and recover previous MFT record images (some attributes remain in records carved from slack).
• Recover file content by:
  • If attributes still resident or non-resident extents listed in MFT: extract directly.
  • If extents freed: locate clusters referenced by previous MFT records, or carve file signatures in unallocated space.
• Validate recovered file by hashing and comparing to any cached copies (Volume Shadow Copies, prefetch, application logs).

Tamper detection & indicators

• Timestamp inconsistencies: contradictory timestamp order across attributes, or improbable clock skew not consistent with system timezone.
• SN reuse without corresponding USNJRNL or $LogFile entries indicates possible manual MFT tampering or journal truncation.
• Gaps or truncation in $USNJRNL or incomplete $LogFile transactions suggest truncation or intentional wiping.
• MFTMirr differing from primary MFT indicates targeted MFT modifications or partial corruption.
• Presence of overwritten MFT records in unallocated/slack space = possible attempt to conceal.

Presentation of evidence

• Produce an event timeline: align MFT events, USNJRNL records, LogFile transactions, carved recoveries, and external logs (Windows Event, antivirus, network).
• For each action include: timestamp (UTC), source artifact, FRN/SN, operation type, hashes of recovered content, and confidence level.
• Visual aids: timeline charts and annotated MFT record extracts.
• Document acquisition chain-of-custody, tool versions, command parameters, and hashes for reproducibility.
• Explain limitations and alternative explanations (e.g., legitimate FRN reuse, delayed USN flush, system time changes).

Tools & commands (examples)

• MFT parsing: analyzeMFT, MFTECmd
• USN parsing: usnjrnl2csv, MFTECmd
• LogFile parsing: fls and logfileparse scripts, or commercial parsers
• Carving: scalpel, foremost, TSK (icat, blkcat)
• Validation: FTK/EnCase, Autopsy/Sleuth Kit, Rekall for memory if needed

Outcome

• Deliver a defensible report showing reconstructed deletion sequence, recovered file content (with hashes), and specific tamper indicators tied to NTFS artifacts, supporting incident response or legal action.

Definition & importance

A write blocker is a tool that prevents any write operations to storage media while allowing read access. In forensic disk imaging it preserves evidence integrity and ensures chain-of-custody by preventing accidental or malicious modification of original data.

Hardware vs Software

• Hardware write blockers

  • Inline physical device between host and target drive
  • OS-agnostic, robust against driver/firmware quirks
  • Preferred for live systems, unknown/unstable OS, courtroom evidence

• Software write-blocking methods

  • OS-level drivers, mount options (read-only), or forensic tools that enforce read-only
  • Easier to deploy, lower cost, but depend on host OS and can be bypassed by kernel bugs or malicious firmware
  • Suitable for controlled lab environments or when hardware blockers unavailable and risk is low

When to use which

• Use hardware blockers for initial seizure, courtroom-grade collections, unknown/hostile systems.
• Use software blockers for repeatable lab analysis, automation, or when imaging virtual disks where hardware blockers aren’t applicable.

Always verify block status and document hashes before/after imaging.

Role of a SIEM in forensics

A SIEM centralizes and normalizes logs, correlates events, and creates searchable timelines — providing the primary evidence store and investigator’s dashboard. It flags anomalies, links related events, and preserves context (user, host, process, network) needed for root-cause analysis.

How I use SIEM alerts and logs to prioritize investigations

• Triage by risk: prioritize alerts by severity, confidence, and business asset impact (critical systems first).
• Enrichment: add threat intel, asset owner, and vulnerability status to increase signal-to-noise.
• Correlation: follow correlated alerts (e.g., brute-force then lateral movement) rather than isolated noisy alerts.
• Time windows: focus on alerts with recent and sustained activity or those matching known IOCs.

Collecting supporting evidence

• Build a timeline: query normalized events (auth, process, network, file) around the alert window.
• Preserve sources: export raw logs and snapshots from endpoints, firewalls, and proxies; record hashes and timestamps.
• Reproducible queries: save search queries and correlation rules used.
• Chain of custody: document who accessed/exported evidence and when.
• Example: For a suspected compromised workstation, I pull endpoint process logs, authentication attempts from AD, DNS queries, and network flows from the SIEM, enrich with EDR alerts, isolate the host if malicious artifacts confirmed, and package exports with metadata for deeper forensic analysis.

This approach ensures efficient prioritization and forensically sound evidence collection.