OSM Changeset Analyser,
osmcha, is a Python package to detect suspicious OSM changesets.
It was designed to be used with osmcha-django,
but also can be used standalone or in other projects.
You can report issues or request new features in the the osmcha-frontend repository.
pip install osmcha
You can read a replication changeset file directly from the web:
c = ChangesetList('https://planet.openstreetmap.org/replication/changesets/002/236/374.osm.gz')
or from your local filesystem.
c = ChangesetList('tests/245.osm.gz')
c.changesets will return a list containing data of all the changesets listed in the file.
You can filter the changesets passing a GeoJSON file with a polygon with your interest area to ChangesetList as the second argument.
Finally, to analyse an especific changeset, do:
ch = Analyse(changeset_id) ch.full_analysis()
Customizing Detection Rules
You can customize the detection rules by defining your prefered values when
Analyze class. See below the default values.
ch = Analyse(changeset_id, create_threshold=200, modify_threshold=200, delete_threshold=30, percentage=0.7, top_threshold=1000, suspect_words=[...], illegal_sources=[...], excluded_words=[...])
Command Line Interface
The command line interface can be used to verify an especific changeset directly from the terminal.
osmcha works by analysing how many map features the changeset created, modified
or deleted, and by verifying the presence of some suspect words in the
imagery_used fields of the changeset. Furthermore, we also
consider if the software editor used allows to import data or to do mass edits.
powerfull editors: JOSM, Merkaartor, level0, QGIS and ArcGis.
Usage section, you can see how to customize some of these detection rules.
We tag a changeset as a
possible import if the number of created elements is
greater than 70% of the sum of elements created, modified and deleted and if it
creates more than 1000 elements or 200 elements case it used one of the
We consider a changeset as a
mass modification if the number of modified elements
is greater than 70% of the sum of elements created, modified and deleted and if it
modifies more than 200 elements.
All changesets that delete more than 1000 elements are considered a
If the changeset deletes between 200 and 1000 elements and the number of deleted
elements is greater than 70% of the sum of elements created, modified and deleted
it's also tagged as a
The suspect words are loaded from a yaml file. You can customize the words by setting another default file with a environment variable:
or pass a list of words to the
Analyse class, more information on the section
Customizing Detection Rules. We use a list of illegal sources to analyse the
imagery_used fields and another more general list to examine
the comment field. We have also a list of excluded words to avoid false positives.
Verify if the user has less than 5 edits or less than 5 mapping days.
User has multiple blocks
Changesets created by users that has received more than one block will be flagged.
Unknown iD instance
If you deploy an iD instance for an organization, please let us know so we can whitelist it.
To run the tests on osmcha:
git clone https://github.com/willemarcel/osmcha.git cd osmcha pip install -e .[test] py.test -v
Check CHANGELOG for the version history.
- osmcha-django - backend and API
- osmcha-frontend - frontend of the OSMCha application
- osm-compare - library that analyse OSM features to input it to OSMCha