linux-forensic-disk-timeline-plaso-forensic
Linux Forensic Disk Timeline Plaso Forensic.
- License 许可
- MIT
- 最近更新
- 2026-09-01
- Stars
- ★ 0
- Forks
- 0
01 前言 Front Matter
- name
- linux-forensic-disk-timeline-plaso-forensic
- domain
- cybersecurity
- description
- Linux Forensic Disk Timeline Plaso Forensic.
02 资源文件 1
- 参考文档index.json572 B
03 SKILL.md 正文
| | log2timeline (Plaso) | Primary timeline generation engine parsing 100+ artifact types | | psort | Plaso output filtering, sorting, and export utility | | Timesketch | Web-based collaborative forensic timeline analysis platform | | Timeline Explorer | Eric Zimmerman's Windows GUI for CSV timeline analysis | | KAPE | Automated triage collection feeding into Plaso processing | | mactime (TSK) | Simpler timeline generation from Sleuth Kit bodyfiles | | Excel/Sheets | Manual timeline review for small filtered datasets | | Elastic/Kibana | Alternative visualization platform for JSONL timeline data |
Common Scenarios
Scenario 1: Ransomware Attack Reconstruction Process the full disk image with Plaso, filter to the week before encryption was discovered, identify the initial access vector from browser history and event logs, trace privilege escalation through registry and Prefetch, map lateral movement from network logon events, pinpoint encryption start from MFT timestamps showing mass file modifications.
Scenario 2: Data Theft Investigation Create super-timeline from suspect's workstation, filter for USB device connection events, file access timestamps, and cloud storage browser activity, build a narrative showing data staging, compression, and exfiltration, present timeline to legal team with tagged evidence points.
Scenario 3: Multi-System Breach Analysis Process disk images from all affected systems into a single Plaso storage file, import into Timesketch for collaborative analysis, search for lateral movement patterns across system timelines, identify the patient-zero system and initial compromise vector, map the full attack chain across the environment.
Scenario 4: Insider Threat After-Hours Activity Filter timeline to non-business hours only, identify file access patterns outside normal working times, correlate with authentication events (badge access, VPN logon), search for data access to sensitive directories during these periods, build evidence package for HR/legal.
Output Format
Timeline Reconstruction Summary:
Evidence Sources:
Disk Image: evidence.dd (500 GB, NTFS)
Plaso Storage: evidence.plaso (2.3 GB)
Processing Statistics:
Total events extracted: 4,567,890
Parsers used: 45 (winevtx, prefetch, mft, usnjrnl, lnk, chrome, firefox, winreg, ...)
Processing time: 3h 45m
Incident Window (2024-01-15 to 2024-01-20):
Events in window: 234,567
Event Sources:
MFT: 89,234
Event Logs: 45,678
USN Journal: 56,789
Registry: 23,456
Prefetch: 1,234
Browser: 5,678
LNK Files: 2,345
Other: 10,153
Key Timeline Events:
2024-01-15 14:32 - Phishing email opened (browser)
2024-01-15 14:33 - Malicious document downloaded
2024-01-15 14:35 - PowerShell executed (Prefetch + Event Log)
2024-01-15 14:36 - C2 connection established (Registry + Event Log)
2024-01-16 02:30 - Mimikatz execution (Prefetch)
2024-01-16 02:45 - Lateral movement to DC (Event Log)
2024-01-17 03:00 - Data exfiltration (MFT + USN Journal)
2024-01-18 03:00 - Log clearing (Event Log)
Exported Files:
Full Timeline: /timeline/full_timeline.csv (4.5M rows)
Incident Window: /timeline/incident_window.csv (234K rows)
Timesketch Import: /timeline/timeline.jsonl
04 同仓库更多 Skills
services-wmi-persistence-detect
Detect WMI event subscription persistence by enumerating ActiveScriptEventConsumer, CommandLineEventConsumer, and permanent subscriptions in the WMI repository.
services-wmi-exec-exploit
Perform lateral movement across Windows networks using WMI-based remote execution techniques including Impacket wmiexec.py, CrackMapExec, and native WMI commands for stealthy post-exploitation during red team engagements.
registry-artifact-extract
Extract and analyze Windows Registry hives to uncover user activity, installed software, autostart entries, and evidence of system compromise.
processes-token-impersonate-detect
Detect Windows token impersonation and privilege abuse including SeImpersonatePrivilege exploitation via Potato attacks and token stealing techniques.
processes-thread-injection-detect
Detect Windows thread injection techniques including CreateRemoteThread, QueueUserAPC, NtCreateThreadEx, and thread hijacking via process memory analysis.
processes-hollow-technique-detect
Detect process hollowing (RunPE) by identifying processes with mismatched image paths between PEB and VAD tree, or unmapped PE headers in memory.