What Plaso is

log2timeline started as a Perl tool, which the project now lists as legacy. Plaso is its Python successor, hosted under the log2timeline organisation on GitHub and released under the Apache 2.0 licence. The name is an Icelandic phrase that the project translates as the wish to collect everything, and the project's own tagline is super timeline all the things. Five command line tools make up the suite. log2timeline extracts events from a file, a directory such as a mount point, a storage media image or a device and writes them to a Plaso storage file. psort filters, sorts and runs analysis on a storage file and writes the output. psteal does both in one run. pinfo describes what a storage file contains. image_export copies files out of an image by extension, path, signature or creation date range.

A typical job starts with log2timeline run against a forensic image with a chosen parser preset. On a large image this takes hours, because every recognised file type is parsed: file system metadata, registry hives, event logs, browser databases, prefetch, Linux and macOS logs and many application files. psort then narrows the result to a date window and writes CSV or sends it to Timesketch. The storage file also keeps collection metadata, tags from analysis plugins and reports. Two things catch newcomers. Time zones: a parser records what it finds and the examiner must know which zone each source used. Coverage: an artefact Plaso has no parser for is simply absent from the timeline, which is not evidence that nothing happened. The user guide offers Docker images for Linux, macOS and Windows and packaged releases for Fedora, macOS and Ubuntu.

Primary applications

Where it is used

  • Building a super timeline from a disk image
  • Producing a narrow timeline for a known date window
  • Correlating registry, log and file system events from one machine
  • Exporting files from an image by signature or date before deeper analysis
  • Feeding Timesketch so a team can work on the timeline together
  • Timelining a folder of artefacts collected by KAPE or Velociraptor

Who uses it

  • Digital forensic examiners
  • Incident responders building host timelines
  • Researchers working with many systems
  • Students learning timeline analysis

Capabilities and limits

Major capabilities

  • Extraction from files, directories, mounted images, storage media images and devices
  • Parsers for file system metadata, Windows registry and event logs, browser data and many application formats
  • Parser presets to limit extraction to what a case needs
  • A single storage file holding events, metadata, tags and analysis reports
  • Filtering, sorting and analysis plugins in psort
  • Output to CSV and other formats and direct export to Timesketch
  • image_export for pulling files out of an image by filter
  • Docker images and packaged releases for the main desktop operating systems

Technical limitations

  • Slow on large images because everything recognised is parsed
  • A timeline contains only what the parsers know. Gaps are not evidence of absence
  • Time zone and clock skew handling is the examiner's job
  • Millions of events need filtering before a person can read them
  • Some artefacts are parsed more fully by single-purpose tools such as Eric Zimmerman's
  • Storage file formats change between releases, so a file may need the version that wrote it

Learning with DFRTI

Independent professional education covering the principles and workflows of Plaso. DFRTI is not a vendor training centre and its courses are not vendor certifications.

Before you learn it

  • File systems and the meaning of their timestamps
  • Windows, Linux and macOS artefacts at a working level
  • Command line use and time zone arithmetic

Disciplines

Courses that cover this tool

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Go deeper with DFRTI

Free pages explain the ground. Structured courses, lab work and a mentor take you from knowing about it to doing it on a case.