A script to convert a Cellebrite UFDR to it’s original file and directory structure.


Cellebrite Reader files (.ufdr) are processed mobile device images. They are compressed (zip) files that contain a report.xml file in the root, and files sorted into directories by category.

The ufdr has the original subject data, but does not keep the original file path structure. This means that tools such as ALEAPP have poor results over the package.

UFDR2DIR converts the categorized data back into the original directory structure. This will allow tools that do not support UFDR to load the data as a directory.

Install and Run

Make sure you have Python 3 installed. Download the repository.
From a command prompt run:

pip3 install -r requirements.txt
python3 ufdr2dir.py filename.ufdr

This will create an output folder in the current working directory. You can specify where you want to output to with -o [OUTDIR].

The output directory will mirror what was recorded in report.xml. You can point tools like ALEAPP directly at the resulting folder.


Cellebrite apparently does some deleted data recovery. These files are currently not being extracted if they lack path information.

Most UFDR are probably going to be from Android and iOS. Windows, however, has a lot of illegal file path characters. If you extract the UFDR on Windows/NTFS, illegal characters will be stripped from the file path. Be aware that some paths may be slightly different from original on Windows.

Example: com.facebook.katana:dash <– “:” is an illegal path character in NTFS (thanks, alternate data streams!). As such, UFDR2DIR extracts it as com.facebook.katanadash on Windows. Linux and MacOS are unaffected.

Bug reports and suggestions

Pull requests considered! Otherwise create an issue or message me on Twitter if you find any bugs or have some recommendations.


Tested on:

  • Linux Mint 20.3
  • (light testing) Windows 11

If you have issues or experience on other platforms, please let me know how it went.

Thank you

Thanks to Josh Hickman for the public data sets that this script was tested on.


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