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sarif-extract-tables: initial version, reproduces known output as table
Reproduce the
file:line:col:line:col: message
output from
../../bin/sarif-results-summary results.sarif | grep size
as test/example.
Original sample output is
RESULT: static/js/fileuploader.js:1214:13:1214:17: Unused variable size.
RESULT: static/js/tinymce/jscripts/tiny_mce/plugins/media/js/media.js:438:30:438:34: Unused variable size.
The table result here is
0:$ ../../bin/sarif-extract-tables results.sarif | grep size
0,static/js/fileuploader.js,1214,13,1214,17,Unused variable size.
34,static/js/tinymce/jscripts/tiny_mce/plugins/media/js/media.js,438,30,438,34,Unused variable size.
This commit is contained in:
Michael Hohn
committed by
=Michael Hohn
=Michael Hohn
parent
f5e73e90ba
commit
ec9a0b5590
@@ -6,7 +6,6 @@ import json
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from sarif_cli import signature
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from sarif_cli import typegraph
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import sys
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from pprint import pprint
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from collections import defaultdict
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import pandas as pd
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@@ -15,9 +14,10 @@ import pandas as pd
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#
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parser = argparse.ArgumentParser(description='Read a sarif file and produce tabular output.')
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parser.add_argument('file', metavar='sarif-file', type=str, help='input file, - for stdin')
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# XX
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# parser.add_argument('-t', '--typedef-signatures', action="store_true",
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# help='Give every object signature a type and report by types')
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parser.add_argument('-f', '--output-format', metavar='format', type=str, default="csv",
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help='Output format for table. Currently just csv; '
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' other formats supported by pandas can be added.')
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args = parser.parse_args()
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#
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@@ -44,265 +44,107 @@ sarif_struct = signature.fillsig(args, sarif_struct, context)
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tgraph = typegraph.Typegraph(typegraph.struct_graph_2022_02_01)
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typegraph.destructure(tgraph, typegraph.start_node_2022_02_01, sarif_struct)
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if 0:
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import IPython
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IPython.embed(header="""
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---------------------------------
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ipython repl for
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tgraph = typegraph.Typegraph(typegraph.struct_graph_2022_02_01)
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---------------------------------
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Sanity checks:
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In [4]: tgraph.fields
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Out[4]:
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{'String': None,
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'Int': None,
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'Bool': None,
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...
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}
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In [6]: tgraph.instances['String']
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Out[6]: []
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In [7]: tgraph.instances['Int']
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Out[7]: []
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In [8]: tgraph.instances['Bool']
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Out[8]: []
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Select value checks:
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In [9]: tgraph.instances['Struct6787']
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Out[9]:
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[(4358601472,
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'https://raw.githubusercontent.com/oasis-tcs/sarif-spec/master/Schemata/sarif-schema-2.1.0.json',
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4362190016,
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'2.1.0')]
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In [10]: tgraph.fields['Struct6787']
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Out[10]: ['$schema', 'runs', 'version']
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In [5]: tgraph.instances['Array0177']
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Out[5]:
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[(4337396800, 0, 'Struct3388', 4337396928),
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(4337396800, 1, 'Struct3388', 4337397056)]
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In [12]: tgraph.fields['Array0177']
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Out[12]: [0]
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In [9]: tgraph.instances['Array7069'][0:5]
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Out[9]:
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[(4337397248, 0, 'String', '\r\n'),
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(4337397248, 1, 'String', '\n'),
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(4337397248, 2, 'String', '\u2028'),
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(4337397248, 3, 'String', '\u2029'),
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(4339863424, 0, 'String', 'maintainability')]
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In [10]: tgraph.instances['Struct6299'][:3]
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Out[10]:
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[(4315110720, 17, 1214, 13, 1214),
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(4315111232, -1, -1, 1, -1),
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(4315124096, 30, 847, 17, 847)]
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In [11]: tgraph.fields['Struct6299']
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Out[11]: ['endColumn', 'endLine', 'startColumn', 'startLine']
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""")
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#
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# Form output tables
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#
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typegraph.attach_tables(tgraph)
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import IPython
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IPython.embed(header="""
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---------------------------------
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ipython repl for tables
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---------------------------------
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tgraph.dataframes
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In [7]: sorted(tgraph.dataframes.keys())
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Out[7]:
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['Array0177',
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'Array0350',
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'Array1075',...]
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sorted(tgraph.dataframes.keys())
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tgraph.dataframes['Array0177']
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tgraph.dataframes['Struct3388']
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tgraph.signature_graph['Struct3388']
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XX: reproduce the
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"""
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Reproduce the
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file:line:col:line:col: message
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output from
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../../bin/sarif-results-summary results.sarif | less
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../../bin/sarif-results-summary results.sarif | grep size
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as test. Sample:
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as test/example. Sample output is
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RESULT: static/js/fileuploader.js:1214:13:1214:17: Unused variable size.
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RESULT: static/js/tinymce/jscripts/tiny_mce/plugins/media/js/media.js:438:30:438:34: Unused variable size.
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Collect typedef/fields via typegraph.pdf:
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The tree paths that match up .startLine with .text and .uri are
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- .results > .[] > .message > .text
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- .results > .[] > .locations > .[] > .physicalLocation > .region > .startLine
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- .results > .[] > .locations > .[] > .physicalLocation > .artifactLocation > .uri
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static/js/fileuploader.js
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Struct2685/uri
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Note that this IGNORES the path
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- .results > .[] > .relatedLocations > .[] > .physicalLocation > .text
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In [22]: d1 = tgraph.dataframes['Struct2685']
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In [24]: d1[d1.uri == "static/js/fileuploader.js"]
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Out[24]:
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struct_id index uri uriBaseId
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0 4856718656 0 static/js/fileuploader.js %SRCROOT%
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77 4856758336 0 static/js/fileuploader.js %SRCROOT%
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...
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We need appropriate table joins to replicate those tree paths; following the edges
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in typegraph.pdf is the most direct way to find relevant tables and keys.
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:1214:13:1214:17:
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Struct6299/startLine/startColumn/endLine/endColumn
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We only care about .message with matching .startLine, so left joins should
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work without losing any data. Here are the tree paths and their corresponding
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tables; the tree paths are from left to right and the joins can be done in the
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same order.
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Unused variable size.
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Struct2774/message
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d1 = tgraph.dataframes['Struct2774']
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In [31]: d1[d1.text.str.contains("Unused variable size")]
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Out[31]:
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struct_id text
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1 4856749504 Unused variable size.
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103 4856879296 Unused variable size.
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Using ../notes/typegraph.pdf, we find these:
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Follow the edges in typegraph.pdf to find joining typedefs and paths.
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|------------+----------+---------+-------------------+-------------------+------------|
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| .locations | | .[] | .physicalLocation | .artifactLocation | .uri |
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| sf(4055) | | af(350) | sf(2683) | sf(4963) | sf(2685) |
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|------------+----------+---------+-------------------+-------------------+------------|
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| .locations | | .[] | .physicalLocation | .region | .startLine |
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| sf(4055) | | af(350) | sf(2683) | sf(4963) | sf(6299) |
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|------------+----------+---------+-------------------+-------------------+------------|
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| .message | .text | | | | |
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| sf(4055) | sf(2774) | | | | |
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|------------+----------+---------+-------------------+-------------------+------------|
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Struct4963
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Struct2683
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""")
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"""
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#
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# Access convenience functions
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#
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sf = lambda num: tgraph.dataframes['Struct' + str(num)]
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af = lambda num: tgraph.dataframes['Array' + str(num)]
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#
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# These merges are for reconstructing ../../bin/sarif-results-summary output, but
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# they also form the "bottom right" dataframe on the type graph (see the .pdf) and
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# can be used for other result-oriented output.
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# Form the dataframe via joins
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#
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# original dataframes
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#
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# Struct2685/uri
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f2685 = odf_location = tgraph.dataframes['Struct2685']
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# Struct6299/startLine/startColumn/endLine/endColumn
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f6299 = odf_region = tgraph.dataframes['Struct6299']
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# Struct2774/message
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f2774 = odf_message = tgraph.dataframes['Struct2774']
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#
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# Linking dataframes
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#
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f4963 = ldf_physicalLocation = tgraph.dataframes['Struct4963']
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f2683 = tgraph.dataframes['Struct2683']
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# f4963 -> f6299
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m_f4963_f6299 = pd.merge(
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f4963,
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f6299,
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how="inner",
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on=None,
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left_on='region',
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right_on='struct_id',
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left_index=False,
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right_index=False,
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sort=True,
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suffixes=("_f4963", "_f6299"),
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copy=True,
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indicator=False,
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validate="1:m",
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)
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# m_f4963_f6299 -> f2685
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m_f4963_f6299_f2685 = pd.merge(
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m_f4963_f6299,
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f2685,
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how="inner",
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on=None,
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left_on='artifactLocation',
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right_on='struct_id',
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left_index=False,
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right_index=False,
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sort=True,
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suffixes=("_m_f4963_f6299", "_f2685"),
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copy=True,
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indicator=False,
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validate="1:m",
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d1 = (
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sf(4055)
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.merge(af('0350'), how="left", left_on='locations', right_on='array_id', validate="1:m")
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.drop(columns=['struct_id', 'locations', 'array_id', 'value_index', 'type_at_index'])
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.merge(sf(2683), how="left", left_on='id_or_value_at_index', right_on='struct_id',
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suffixes=("_4055", "_2683"), validate="1:m")
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.drop(columns=['struct_id', 'id_or_value_at_index'])
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.merge(sf(4963), how="left", left_on='physicalLocation', right_on='struct_id', validate="1:m")
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.drop(columns=['struct_id', 'physicalLocation'])
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.merge(sf(6299), how="left", left_on='region', right_on='struct_id', validate="1:m")
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.drop(columns=['struct_id', 'region'])
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.merge(sf(2685), how="left", left_on='artifactLocation', right_on='struct_id', validate="1:m")
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.drop(columns=['struct_id', 'artifactLocation'])
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.merge(sf(2774), how="left", left_on='message_4055', right_on='struct_id', validate="1:m")
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.drop(columns=['struct_id', 'message_4055'])
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.merge(sf(2774), how="left", left_on='message_2683', right_on='struct_id',
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suffixes=("_4055", "_2683"), validate="1:m")
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)
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#
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# As expected from the above note
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#
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# Note that this IGNORES the path
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# - .results > .[] > .relatedLocations > .[] > .physicalLocation > .text
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#
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# we have no text entries that table:
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#
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# In [88]: d1[d1.text_2683 != '']
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# Out[88]:
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# Empty DataFrame
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# f2683 -> m_f4963_f6299_f2685
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m_f2683_f4963_f6299_f2685 = pd.merge(
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f2683,
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m_f4963_f6299_f2685,
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how="inner",
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on=None,
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left_on='physicalLocation',
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right_on='struct_id_f4963',
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left_index=False,
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right_index=False,
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sort=True,
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suffixes=("_f2683", "_m_f4963_f6299_f2685"),
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copy=True,
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indicator=False,
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validate="1:m",
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)
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# m_f2683_f4963_f6299_f2685 -> f2774
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m_f2683_f4963_f6299_f2685_f2774 = pd.merge(
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m_f2683_f4963_f6299_f2685,
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f2774,
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how="inner",
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on=None,
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left_on='message',
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right_on='struct_id',
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left_index=False,
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right_index=False,
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sort=True,
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suffixes=("_m_f2683_f4963_f6299_f2685", "_f2774"),
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copy=True,
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indicator=False,
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validate="1:m",
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)
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#
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# Reproduce ALL `file:line:col:line:col: message` entries as a table
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#
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d2 = (d1[['uri', 'startLine', 'startColumn', 'endLine', 'endColumn', 'text_4055']]
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.rename({'text_4055': 'message'}, axis='columns'))
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#
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# Remove indexing columns. Note: each row corresponds to the fields of an
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# original table.
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# Write output
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#
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qdf = m_f2683_f4963_f6299_f2685_f2774[
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['id', 'message', 'physicalLocation',
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'artifactLocation', 'region',
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'endColumn', 'endLine', 'startColumn', 'startLine',
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'index', 'uri', 'uriBaseId',
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'text']]
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qdf[qdf.uri == "static/js/fileuploader.js"]
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qdf[qdf.text.str.contains("Unused variable size")]
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#
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#
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#
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if args.dot_output:
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signature._signature(args, sarif_struct, context)
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struct_graph = [(typedef, sig) for sig, typedef in context.sig_to_typedef.items()]
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signature.write_header(sys.stdout)
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for typedef, sig in struct_graph:
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signature.write_node(sys.stdout, typedef, sig)
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for typedef, sig in struct_graph:
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signature.write_edges(args, sys.stdout, typedef, sig)
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signature.write_footer(sys.stdout)
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elif args.typedef_signatures:
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signature._signature(args, sarif_struct, context)
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struct_graph = dict((typedef, sig) for sig,typedef in context.sig_to_typedef.items())
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pprint(struct_graph, sys.stdout, indent=4)
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if args.output_format == 'csv':
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d2.to_csv(sys.stdout, index_label='index')
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else:
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pprint(signature._signature(args, sarif_struct, context), sys.stdout, indent=2)
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sys.stderr.write("unknown output format")
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sys.exit(1)
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Block a user