<Extensions>h;hpp;h++;hxx;hm;inl;inc;xsd</Extensions>
      </Filter>
      <Filter Include="Resource Files">
        <Extensions>rc;ico;cur;bmp;dlg;rc2;rct;bin;rgs;gif;jpg;jpeg;jpe;resx;tiff;tif;png;wav</Extensions>
      </Filter>
    </ItemGroup>
    <ItemGroup Label="Sources"/>
    <ItemGroup Label="Headers"/>

        Node resourceFiles = itemGroup('Filters').Filter.find({it.'@Include' == 'Resource Files'}) as Node
        resourceFiles.Extensions[0].text() == 'rc;ico;cur;bmp;dlg;rc2;rct;bin;rgs;gif;jpg;jpeg;jpe;resx;tiff;tif;png;wav'

        and:
        itemGroup('Sources').children().isEmpty()
        itemGroup('Headers').children().isEmpty()
    }

    def "adds sources and header files"() {
        when:

have different security properties and provide different levels of confidence
when dealing with untrusted data. Based on the security history of these
libraries we consider that it is safe to work with untrusted inputs for PNG,
BMP, GIF, WAV, RAW, RAW\_PADDED, CSV and PROTO formats. All other input formats,
including tensorflow-io should be sandboxed if used to process untrusted data.

For example, if an attacker were to upload a malicious video file, they could