Timeline Analysis
Building a chronological, normalised view of activity by combining timestamps from many sources -- filesystem metadata, event logs, registry keys, browser history, application artefacts and network telemetry -- into one ordered sequence. A super timeline in tooling such as Plaso and log2timeline is the usual output. It is how an investigation establishes what happened in what order, and it is central to GCFA, GNFA, CHFI and incident-response work.
Why It Matters
In practice timeline analysis is where an incident narrative is actually constructed, and the discipline that makes it reliable is timezone and clock handling: sources record in local time, UTC or epoch, hosts drift, and one mishandled offset can invert cause and effect and produce a confidently wrong story. Standard practice normalises everything to UTC and records each source's observed clock skew. The other key idea is that different timestamps mean different things -- on NTFS, the MFT holds both Standard Information and Filename attributes, and a mismatch between them is a strong timestomping signal, because tampering tools commonly update one and not the other. Corroboration across independent sources is what makes a timeline defensible: a single artefact can be forged or misinterpreted, while agreement between event logs, filesystem metadata and network records is hard to fake. On exams such as GCFA, expect questions on normalisation and on detecting manipulated timestamps.
Practice this topic
Test your knowledge of Timeline Analysis concepts with exam-style practice questions.
Related Forensics terms
Digital Forensics
The scientific examination, collection, preservation, and analysis of digital evidence from computers, networks, mobile devices, and cloud environments for use in legal proceedings, incident response, or investigations. The forensic process follows strict procedures: identification, preservation (maintaining chain of custody), collection (creating forensic images), examination, analysis, and reporting. Key principles include working from forensic copies (never the original), documenting every action, and maintaining evidence integrity through cryptographic hashing. Tools include EnCase, FTK, Autopsy, and Volatility. Digital forensics is the focus of CHFI, GCFA, and GNFA certifications and is covered in CISSP Domain 7.
Chain of Custody
The documented and unbroken process of maintaining and controlling evidence to preserve its integrity and admissibility from the moment of collection through presentation in court. Every person who handles the evidence must be documented with dates, times, actions taken, and the reason for access. Any gap or irregularity in the chain of custody can cause evidence to be deemed inadmissible. In digital forensics, chain of custody includes hash verification at each transfer point, write-blocking during acquisition, and tamper-evident storage. This concept is critical for forensic examiners and is tested in CHFI, GCFA, and CISSP Domain 7 certifications.
Volatile Memory
Computer memory (RAM) that loses its contents when power is removed, making it a time-critical source of forensic evidence that must be captured before a system is shut down. Volatile memory contains running processes, open network connections, encryption keys, clipboard contents, logged-in users, and malware that may exist only in memory (fileless malware). Memory acquisition tools include FTK Imager, WinPmem, and LiME (Linux Memory Extractor), while analysis is performed with Volatility Framework or Rekall. The order of volatility (RFC 3227) dictates that RAM should be captured before disk, network, or other evidence. Memory forensics is a key skill in GCFA, CHFI, and incident response certifications.
Log Analysis
The examination of system, application, network, and security logs to identify security events, anomalies, policy violations, or evidence of attacks. Logs are generated by operating systems, firewalls, web servers, authentication systems, databases, and cloud services. Effective log analysis involves centralization (forwarding logs to a SIEM), normalization (standardizing formats), correlation (linking related events across sources), and alerting on suspicious patterns. Key log sources include Windows Event Logs, syslog, Apache/Nginx access logs, and cloud audit trails (AWS CloudTrail, Azure Activity Log). Log analysis is a core skill for SOC analysts and is tested in CySA+, CISSP, and GCIH certifications.
Memory Forensics
The forensic analysis of volatile memory (RAM) to extract evidence of malware, network connections, running processes, encryption keys, and other artifacts that may not be preserved on disk. Memory analysis can reveal malware that exists only in memory, decrypt encrypted volumes using keys in memory, and recover recently accessed data. Tools like Volatility, Rekall, and commercial memory analysis platforms enable automated analysis of memory dumps. Memory forensics is particularly valuable for analyzing advanced malware and rootkits that hide from traditional disk-based analysis.
Order of Volatility
The principle that digital evidence must be collected from most to least perishable, because acquiring one source can destroy another. The conventional order runs CPU registers and cache, then RAM, then network state and running processes, then temporary files, then disk, then remote logging and archival media. It governs live acquisition decisions in incident response and is examined in GCFA, GNFA, CHFI and CySA+ forensics domains.