Description
The CSI Linux Certified Computer Forensic Investigator course and certification is designed to teach investigators how to identify, preserve, analyze, validate, correlate, and defend digital evidence in a structured and court ready manner. It covers the lifecycle of a computer forensics investigation, from foundational concepts and legal authority through evidence handling, workstation preparation, file systems, deleted data, timeline and log analysis, operating system artifacts, internet evidence, memory, mobile, cloud, network attribution, malware, expert testimony, and final case reconstruction. Its purpose is not merely to teach tool use. Its purpose is to teach how to build a defensible forensic case that can withstand technical scrutiny, legal challenge, and courtroom examination.
This course is useful because computer forensic investigations are judged not only by whether evidence is found, but by whether it was acquired, interpreted, preserved, and reported correctly. For digital forensic examiners, investigators, law enforcement, incident responders, and related professionals, the course provides a disciplined framework for evidence integrity, attribution, reconstruction, reporting, and courtroom readiness. It is built to move investigators from foundational understanding to practical capability while preserving scientific thinking, documentation discipline, and operational rigor.
Phase 1. Foundations of Computer Forensics and Investigative Thinking
• Module 1. Introduction to Computer Forensics: Opens the course and frames the purpose, scope, and value of computer forensics in modern investigations.
• Module 2. What is Cyber Forensics? Defines cyber forensics and places it in the broader investigative and evidentiary context.
• Module 3. The Investigation Mindset: Builds the disciplined reasoning and analytical posture required for defensible forensic work.
• Module 4. The Investigation Process: Establishes the overall workflow from allegation through acquisition, analysis, reporting, and testimony.
• Module 5. Digital Evidence, Proof, and Attribution: Explains the relationship between artifacts, evidentiary value, and attribution limits.
• Module 6. Scientific Foundations of Digital Evidence: Connects forensic work to validation, reliability, repeatability, and scientific discipline.
• Module 7. Laws and Ethics: Covers legal authority, ethics, scope, privacy, and the responsibilities of the forensic examiner.
Phase 2. Documentation, Reporting, and Laboratory Readiness
• Module 8. Common Documents in Computer Forensics: Introduces the core documents used to support forensic casework.
• Module 9. Documentation and Case Management: Covers structured recordkeeping, case tracking, and disciplined case file management.
• Module 10. Report Writing: Teaches how to communicate findings clearly, accurately, and defensibly.
• Module 11. Creating a Digital Forensic Workstation: Covers workstation planning, configuration, and readiness for forensic use.
• Module 12. CSI Linux as your Forensic Workstation: Applies workstation principles specifically to CSI Linux as a forensic platform.
• Module 13. Working with Pre-Imaged Evidence: Prepares investigators to work from prepared images in a controlled and repeatable way.
• Module 14. E-Discovery: Connects forensic process to discovery, review, and broader evidentiary production workflows.
Phase 3. Storage, File Systems, and Low-Level Evidence Foundations
• Module 15. How data is written to a drive: Explains how storage behavior affects forensic recovery and interpretation.
• Module 16. File System: Introduces file system structure and forensic relevance.
• Module 17. Slack Space: Covers residual data in slack space and its investigative value.
• Module 18. Deleted Files: Teaches the recovery and interpretation of deleted content.
• Module 19. String/HEX Searching and Regex: Provides practical search techniques for identifying evidence in raw and structured data.
• Module 20. File Analysis: Covers file triage, interpretation, and artifact value assessment.
• Module 21. Timeline Analysis: Teaches time-based correlation of activity across artifacts.
• Module 22. Log Files: Explains the collection and interpretation of logs as forensic evidence.
Phase 4. Evidence Acquisition, Integrity, and Control
• Module 23. Acquiring, Transporting, and Storing Evidence: Covers safe handling and movement of digital evidence.
• Module 24. Forensic Imaging: Teaches image acquisition methods and their evidentiary significance.
• Module 25. Evidence Integrity & Validation: Reinforces validation, hashing, and integrity controls.
• Module 26. Chain of Custody and Evidence Control: Covers documentation and control measures that preserve admissibility.
Phase 5. Operating System and User Environment Artifacts
• Module 27. Windows OS Artifacts: Examines common Windows sources of forensic value.
• Module 28. Windows Registry Forensics: Focuses on registry-based evidence and interpretation.
• Module 29. MAC OS Artifacts: Covers forensic artifacts specific to macOS environments.
• Module 30. Linux OS Artifacts: Covers forensic artifacts specific to Linux systems.
• Module 31. Internet Evidence: Teaches how browser, web, and internet related artifacts support investigations.
• Module 32. Graphics and Image Analysis: Covers the evidentiary and analytical value of image artifacts.
• Module 33. Memory Forensics: Introduces volatile memory acquisition and analysis.
Phase 6. Concealment, Devices, and Modern Technical Environments
• Module 34. Methods of Hiding Data: Surveys concealment techniques used to obscure evidence.
• Module 35. Encryption: Covers encryption in relation to access, interpretation, and forensic limitations.
• Module 36. Anti-Forensics and Evasion: Addresses adversary efforts to frustrate forensic recovery and interpretation.
• Module 37. Mobile Devices: Introduces mobile device evidence and acquisition considerations.
• Module 38. IoT, IIoT, ICS, and SCADA Forensics: Covers emerging and specialized device environments.
• Module 39. Virtualization and Containers: Explains how virtual and containerized environments affect forensic work.
• Module 40. Cloud Forensics: Covers cloud hosted evidence and related acquisition and attribution issues.
Phase 7. Attribution, Correlation, and Advanced Investigative Reconstruction
• Module 41. Network and Account Attribution: Focuses on linking activity to accounts, infrastructure, and actors.
• Module 42. OSINT for Digital Forensics: Connects open-source intelligence methods to forensic case support.
• Module 43. Evidence Correlation and Case Reconstruction: Teaches how to combine artifacts into a defensible case theory.
• Module 44. Timeline Reconstruction and Event Sequencing: Builds event sequencing across systems, artifacts, and timelines.
• Module 45. Hacking and Malware Forensics: Covers malicious activity and malware related forensic artifacts.
• Module 46. Threat Actor Tradecraft and MITRE ATT&CK for Examiners: Connects observed evidence to adversary tradecraft and behavior frameworks.
• Module 47. AI in Computer Forensics: Examines the role, value, and risks of AI in forensic workflows.
Phase 8. Courtroom Readiness, Professional Discipline, and Capstone Application
• Module 48. Expert Testimony and Courtroom Readiness: Prepares investigators to explain methods, findings, and limitations under challenge.
• Module 49. Operational Discipline for Examiners: Reinforces the habits that keep forensic work controlled, reproducible, and defensible.
• Module 50. Capstone Lab: Operation NightWing, The Trade at Hollow Pine: Applies the course in a full case based practical scenario.
