Decode, encode, and identify forensic timestamps — ranked, scored, cited.
Project description
timeglyph
Decode, encode, and identify forensic timestamps — ranked, scored, and cited.
Python bindings for timeglyph, the Rust engine that reads a raw timestamp value every way a system might have written it and returns the results ranked by likelihood, each with the spec citation — honest about the ambiguity instead of guessing one answer. Built for DFIR work in notebooks, plaso, and Timesketch.
Install
pip install timeglyph
A single self-contained extension (stable-ABI wheel, CPython 3.9+). No system dependencies.
Use
import timeglyph
# One raw value → every plausible reading, ranked and cited:
for r in timeglyph.identify("133801920000000000"):
print(f'{r["score"]:.2f} {r["format_id"]:10} {r["rendered"]} ({r["citation"]})')
0.89 filetime 2025-01-01T08:00:00Z ([MS-DTYP] §2.3.3 FILETIME)
0.70 ...
Each reading is a dict: format_id, label, rendered, instant, score,
citation, assumptions, components, sentinel. A raw value is usually
underdetermined, so identify returns all confident readings (16 for the example
above) rather than a single verdict — you decide which fits the artifact.
Need the raw payload for a pipeline? timeglyph.identify_json(value) returns the same
result as a JSON string.
Learn more
- Docs & the browser playground: https://securityronin.github.io/timeglyph/
- Source, CLI, and the live GUI overlay: https://github.com/SecurityRonin/timeglyph
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