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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.

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