Skip to main content

prefetch2es

MIT License PyPI version pytest

prefetch2es logo

A command-line tool for parsing Windows Prefetch files and importing the results into Elasticsearch.

prefetch2es is built on pyscca and converts Windows Prefetch artifacts into Elasticsearch-friendly records.

Features

  • Parse Windows Prefetch (.pf) files using pyscca
  • Process a single file, multiple files, or a directory of .pf files
  • Import parsed records into Elasticsearch (prefetch2es)
  • Export parsed records as JSON or JSONL (prefetch2json)
  • Generate timeline-oriented records for forensic analysis (--timeline)

Installation

From PyPI

$ pip install prefetch2es

From GitHub Releases

Standalone binaries built with Nuitka are available from GitHub Releases.

$ chmod +x ./prefetch2es
$ ./prefetch2es {{options...}}
> prefetch2es.exe {{options...}}

Usage

prefetch2es can be executed from the command line or incorporated into a Python script.

$ prefetch2es /path/to/your/file.pf
from prefetch2es import prefetch2es
prefetch2es("/path/to/your/file.pf")

Arguments

prefetch2es can process multiple files at once.

$ prefetch2es file1.pf file2.pf file3.pf

prefetch2es can recursively process all .pf files under a specified directory.

$ tree .
pffiles/
  ├── file1.pf
  ├── file2.pf
  ├── file3.pf
  └── subdirectory/
    ├── file4.pf
    └── subsubdirectory/
      ├── file5.pf
      └── file6.pf

$ prefetch2es /pffiles/ # The path is recursively expanded to all .pf files.

Options

--version, -v

--help, -h

--quiet, -q
  Suppress standard output
  (default: False)

--multiprocess, -m:
  Enable multiprocessing for faster processing.
  (default: False)

--size:
  Number of files to process per chunk (default: 500)

--host:
  Elasticsearch host address (default: localhost)

--port:
  Elasticsearch port number (default: 9200)

--index:
  Destination index name (default: prefetch2es)

--scheme:
  Protocol scheme to use (http or https) (default: http)

--pipeline:
  Elasticsearch ingest pipeline to use (default: )

--timeline:
  Enable timeline analysis mode for forensic investigation
  (default: False)

--tags:
  Comma-separated tags to add to each record for identification
  (e.g., hostname, domain name) (default: )

--login:
  Username for Elasticsearch authentication

--pwd:
  Password for Elasticsearch authentication

--no-verify-certs:
  Disable TLS certificate verification (default: False)

--ca-certs:
  Path to a CA certificate bundle for TLS verification (default: None)

Examples

When using from the command line:

$ prefetch2es /path/to/your/file.pf --host=localhost --port=9200 --index=foobar --size=500

When using from a Python script:

if __name__ == '__main__':
    prefetch2es('/path/to/your/file.pf', host='localhost', port=9200, index='foobar', size=500)

With Elasticsearch authentication:

$ prefetch2es /path/to/your/file.pf --host=localhost --port=9200 --index=foobar --login=elastic --pwd=******

With timeline analysis mode:

$ prefetch2es /path/to/your/file.pf --timeline --index=prefetch-timeline

With custom tags for system identification:

# Single tag
$ prefetch2es /path/to/your/file.pf --timeline --tags="WORKSTATION-01" --index=prefetch-timeline

# Multiple tags (comma-separated)
$ prefetch2es /path/to/your/file.pf --timeline --tags="WORKSTATION-01,FOO,BAR" --index=prefetch-timeline

Appendix

prefetch2json

prefetch2json converts Windows Prefetch files to JSON.

$ prefetch2json /path/to/your/file.pf -o /path/to/output/target.json

prefetch2json also supports line-delimited output. --format jsonl (or ndjson) writes one record per line without holding the entire dataset in memory. When no output path is specified, the default extension is .jsonl:

$ prefetch2json /path/to/your/file.pf --format jsonl

You can also convert Windows Prefetch files directly into a Python list[dict]:

from prefetch2es import prefetch2json

if __name__ == '__main__':
    filepath = '/path/to/your/file.pf'
    result: list[dict] = prefetch2json(filepath)

With timeline analysis and custom tags:

$ prefetch2json /path/to/your/file.pf --timeline --tags="WORKSTATION-01,FINANCE" -o output.json

Timeline Analysis

prefetch2es supports timeline analysis mode that creates specialized timeline records for forensic investigation.

Standard mode creates one record per Prefetch file. Timeline mode creates one record per recorded execution timestamp.

$ prefetch2es /path/to/your/file.pf --timeline --index=prefetch-timeline

This mode creates records optimized for temporal analysis of application execution patterns, making it easier to investigate system activity over time.

Tags for System Identification

Use the --tags option to add custom tags for better organization and filtering:

# Identify source system and department
$ prefetch2es /path/to/prefetch/ --timeline --tags="WORKSTATION-01" --index=prefetch-timeline

# Add criticality level
$ prefetch2es /path/to/prefetch/ --timeline --tags="SERVER-02,FOO,BAR" --index=prefetch-timeline

Output Format Examples

Standard Mode

[
  {
    "name": "CMD.EXE",
    "filenames": [
      "\\VOLUME{01d1217a9c4c6779-8c9f49ec}\\WINDOWS\\SYSTEM32\\DISKPART.EXE",
      "\\VOLUME{01d12173f395296c-66f451bc}\\CMDER129\\VENDOR\\CLINK\\CLINK_DLL_X64.DLL",
      "\\VOLUME{01d1217a9c4c6779-8c9f49ec}\\WINDOWS\\SYSTEM32\\NTDLL.DLL",
      "\\VOLUME{01d1217a9c4c6779-8c9f49ec}\\WINDOWS\\SYSTEM32\\CMD.EXE",
      ...
    ],
    "exec_count": 55,
    "last_exec_times": [
      "2016-01-12T20:07:03.981069Z",
      "2016-01-10T02:29:02.788726Z",
      "2016-01-04T23:27:28.405869Z",
      "2016-01-04T23:27:28.726891Z",
      "2016-01-04T18:38:10.935655Z",
      "2016-01-04T18:38:11.344163Z",
      "2015-12-31T21:42:29.667018Z",
      "2015-12-17T22:34:21.579861Z"
    ],
    "format_version": 30,
    "prefetch_hash": "D269B812",
    "number_of_volumes": 2,
    "number_of_filenames": 62,
    "number_of_file_metrics_entries": 62,
    "metrics": [
      {
        "filename": "\\VOLUME{01d1217a9c4c6779-8c9f49ec}\\WINDOWS\\SYSTEM32\\DISKPART.EXE",
        "file_reference": "0X1000000009EF4"
      },
      {
        "filename": "\\VOLUME{01d12173f395296c-66f451bc}\\CMDER129\\VENDOR\\CLINK\\CLINK_DLL_X64.DLL",
        "file_reference": "0X100000000B5A6"
      },
      {
        "filename": "\\VOLUME{01d1217a9c4c6779-8c9f49ec}\\WINDOWS\\SYSTEM32\\NTDLL.DLL",
        "file_reference": "0X10000000575F4"
      },
      {
        "filename": "\\VOLUME{01d1217a9c4c6779-8c9f49ec}\\WINDOWS\\SYSTEM32\\CMD.EXE",
        "file_reference": "0X1000000009CA8"
      },
      ...
    ],
    "volumes": [
      {
        "path": "\\VOLUME{01d12173f395296c-66f451bc}",
        "creation_time": "2015-11-17T20:10:06.204964Z",
        "serial_number": "66F451BC"
      },
      {
        "path": "\\VOLUME{01d1217a9c4c6779-8c9f49ec}",
        "creation_time": "2015-11-17T20:57:46.243468Z",
        "serial_number": "8C9F49EC"
      }
    ],
    "source_file": "/workspace/tests/cache/CMD.EXE-D269B812.pf",
    "tags": [
      "prefetch"
    ]
  },
  ...
]

Timeline Mode

[
  {
    "@timestamp": "2016-01-12T20:07:03.981069Z",
    "event": {
      "action": "prefetch-executed",
      "category": [
        "process"
      ],
      "type": [
        "start"
      ],
      "kind": "event",
      "provider": "prefetch",
      "module": "windows",
      "dataset": "windows.prefetch"
    },
    "process": {
      "name": "CMD.EXE",
      "start": "2016-01-12T20:07:03.981069Z"
    },
    "windows": {
      "prefetch": {
        "exec_count": 55,
        "hash": {
          "prefetch": "D269B812"
        },
        "format_version": 30,
        "volumes": [
          {
            "path": "\\VOLUME{01d12173f395296c-66f451bc}",
            "creation_time": "2015-11-17T20:10:06.204964Z",
            "serial_number": "66F451BC"
          },
          {
            "path": "\\VOLUME{01d1217a9c4c6779-8c9f49ec}",
            "creation_time": "2015-11-17T20:57:46.243468Z",
            "serial_number": "8C9F49EC"
          }
        ],
        "metrics": [
          {
            "filename": "\\VOLUME{01d1217a9c4c6779-8c9f49ec}\\WINDOWS\\SYSTEM32\\DISKPART.EXE",
            "file_reference": "0X1000000009EF4"
          },
          {
            "filename": "\\VOLUME{01d12173f395296c-66f451bc}\\CMDER129\\VENDOR\\CLINK\\CLINK_DLL_X64.DLL",
            "file_reference": "0X100000000B5A6"
          },
          {
            "filename": "\\VOLUME{01d1217a9c4c6779-8c9f49ec}\\WINDOWS\\SYSTEM32\\NTDLL.DLL",
            "file_reference": "0X10000000575F4"
          },
          {
            "filename": "\\VOLUME{01d1217a9c4c6779-8c9f49ec}\\WINDOWS\\SYSTEM32\\CMD.EXE",
            "file_reference": "0X1000000009CA8"
          },
          ...
        ]
      }
    },
    "log": {
      "file": {
        "path": "/workspace/tests/cache/CMD.EXE-D269B812.pf"
      }
    },
    "tags": [
      "prefetch"
    ]
  },
  ...
]

Supported Prefetch versions

  • Windows XP
  • Windows 2003
  • Windows Vista (SP0)
  • Windows 7 (SP0)
  • Windows 8.1
  • Windows 10 1809
  • Windows 10 1903
  • Windows 11 24H2

For more information, please visit libscca.

Contributing

The source code for prefetch2es is hosted on GitHub. You can download, fork, and review it from this repository: https://github.com/sumeshi/prefetch2es. Please report issues and feature requests. 🍣 🍣 🍣

License

prefetch2es is released under the MIT License.

Third-party licenses

The standalone binaries distributed via GitHub Releases bundle libscca / pyscca, which is licensed under the GNU Lesser General Public License v3.0 or later (LGPL-3.0-or-later).

You may obtain, modify, and rebuild libscca from the upstream source above in accordance with the LGPL.

Metadata

Release files for prefetch2es 2.5.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for prefetch2es 2.5.0
File Size Uploaded
prefetch2es-2.5.0.tar.gz 46.3 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for prefetch2es 2.5.0
File Interpreter ABI Platform
prefetch2es-2.5.0-py3-none-any.whl Python 3 none any Details

Total release size: 63.3 kB

Release files / prefetch2es-2.5.0.tar.gz

Download URL prefetch2es-2.5.0.tar.gz
Size 46.3 kB
Tags Source
SHA-256 checksum
How to use checksums
2fe0895f8a92b1d0bbb7a86bf40f2967e507ec6f07fae659a08cee1c5a7e51de
BLAKE2b-256 checksum
How to use checksums
0157de8640ba381e2ea1abfe01e5f8ae50d9aa0c9af93c658f49fb0e0f7f218d
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via uv/0.12.15 {"installer":{"name":"uv","version":"0.12.15","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

Release files / prefetch2es-2.5.0-py3-none-any.whl

Download URL prefetch2es-2.5.0-py3-none-any.whl
Size 17.0 kB
Tags Python 3
SHA-256 checksum
How to use checksums
abf0499e580aa18c5fb465cdf057fcb944543c3f3b1bd14e8082a7b91a91122e
BLAKE2b-256 checksum
How to use checksums
95adc7d4763e617822dde62a5760843d4ffa434e58bef0ad24105d35f1adb1a6
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via uv/0.12.15 {"installer":{"name":"uv","version":"0.12.15","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

Release history Release notifications | RSS feed

2.7.1

2 release files

2.7.0

2 release files

2.6.0

2 release files

2.5.1

2 release files

This release

2.5.0 This release

2 release files

2.4.1

2 release files

2.4.0

2 release files

2.3.0

2 release files

2.2.2

2 release files

2.2.1

2 release files

2.2.0

2 release files

2.1.0

2 release files

2.0.0

2 release files

1.3.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page