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JIRA 3.1 and above should not suffer from this problem. Invalid characters are automatically stripped from imported data

In older versions of JIRA it was possible to cut & paste text containing control characters into JIRA issue fields. This causes problems, because JIRA's backup format is XML, and XML does not allow for the storage of most control characters .

When XML containing control characters is imported into JIRA, the import fails with an error:

To fix this, the control characters will need to be removed from the JIRA backup file. This can be done with the following:

  1. Download atlassian-xml-cleaner-0.1.jar
  2. Open a command prompt and locate the XML or ZIP backup file on your computer, ensuring that it is extracted if it's within a ZIP file. In this example, we will use entities.xml.
  3. Run the application with the below:

    $ java -jar atlassian-xml-cleaner-0.1.jar entities.xml > entities-clean.xml

    This will create a copy of entities.xml as entities-clean.xml with the invalid characters removed. 

  4. Copy the entities-clean.xml file into another directory, rename it back to entites.xml and create a new ZIP with and the activeobjects.xml file.
  5. Import the new ZIP file, ensuring that it contains both XML files.
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3 Comments

  1. This XML cleaner doesn't strip <ffff> characters. If, after running this XML cleaner you may still get the error:

    An invalid XML character (Unicode: 0xffff) was found in the CDATA section.

    On my system I was able to fix this with:

    perl -i -pe 's/\xef\xbf\xbf//g' entities.xml

    Note perl doesn't allow \x{FFFF} in regexps so you have to break it into bytes as above.

  2. I also faced that XML cleaner leaves invalid characters in the XML backup. Since it is not developed any further, it won't be fixed. Another method for the cleaning:

    • create the export.zip
    • create a test JIRA environment
    • import the export.zip into the test JIRA
    • log into the test JIRA, create an export.zip again, it will be clean, now you can run the anonymizer

  3. You can Use Notepad++ to clean them out (if file is not too big) using \uffff Search and Replace