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fact_pdf_report
Commit a8623c58 by amateyna
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latex code generation init

parent 8d773384
Showing with 212 additions and 0 deletions
src/latex_code_generation/code_generation.py 0 → 100644
import jinja2
from pathlib import Path
def generate_code(analysis_dict, output_path):
jinja_env = _set_jinja_env()
def _set_jinja_env(templates_to_use='default'):
template_directory = Path(Path(__file__).parent.parent, 'templates', templates_to_use)
return jinja2.Environment(
block_start_string='\BLOCK{',
block_end_string='}',
variable_start_string='\VAR{',
variable_end_string='}',
comment_start_string='\#{',
comment_end_string='}',
line_statement_prefix='%%',
line_comment_prefix='%#',
trim_blocks=True,
autoescape=False,
loader=jinja2.FileSystemLoader(str(template_directory))
)
def _render_template(data, jinja_env, template):
output = jinja_env.get_template('{}.tex'.format(template))
return output.render(analysis=data['analysis'], meta_data=data['meta_data'])
def _write_file(raw_data, file_path):
with open(file_path, 'w') as fp:
fp.write(raw_data)
src/templates/test/render_test.tex 0 → 100644
Test \VAR{meta_data} - \VAR{analysis}
\ No newline at end of file
src/test/acceptance/test_main.py 0 → 100644
from common_helper_process.fail_safe_subprocess import execute_shell_command_get_return_code
import os
import pytest
SRC_DIR = os.path.dirname(os.path.abspath(__file__)) + '/../../pdf_generator.py'
@pytest.mark.parametrize('arguments, expected_output, expected_return_code', [
('-V', 'FACT', 0),
('-h', 'usag', 0)
])
def test_main_program(arguments, expected_output, expected_return_code):
command_line = SRC_DIR + ' ' + arguments
output, return_code = execute_shell_command_get_return_code(command_line)
assert output[0:4] == expected_output
assert return_code == expected_return_code
src/test/data/test_dict.py 0 → 100644
test_dict = {
"firmware": {
"analysis": {
"binwalk": {
"analysis_date": 1548333205.871766,
"entropy_analysis_graph": "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",
"plugin_version": "0.5.2",
"signature_analysis": "\nDECIMAL HEXADECIMAL DESCRIPTION\n--------------------------------------------------------------------------------\n0 0x0 Zip archive data, at least v2.0 to extract, name: get_files_test/\n45 0x2D Zip archive data, at least v2.0 to extract, name: get_files_test/generic folder/\n105 0x69 Zip archive data, at least v1.0 to extract, compressed size: 20, uncompressed size: 20, name: get_files_test/generic folder/test file 3_.txt\n201 0xC9 Zip archive data, at least v2.0 to extract, compressed size: 59, uncompressed size: 62, name: get_files_test/testfile1\n314 0x13A Zip archive data, at least v1.0 to extract, compressed size: 28, uncompressed size: 28, name: get_files_test/testfile2\n765 0x2FD End of Zip archive, footer length: 22\n\n",
"summary": {
"End of Zip archive": [
"418a54d78550e8584291c96e5d6168133621f352bfc1d43cf84e81187fef4962_787"
],
"Zip archive data": [
"418a54d78550e8584291c96e5d6168133621f352bfc1d43cf84e81187fef4962_787"
]
}
},
"file_hashes": {
"analysis_date": 1548333208.4131176,
"imphash": None,
"md5": "743692a4121ff9f0c492c14a8371a32e",
"plugin_version": "1.0",
"ripemd160": "6cb1094fd083fe21c5ebba5426e3863f77f85d11",
"sha1": "105bc9f473fa46553bc256521b9b0c5e29213d69",
"sha256": "418a54d78550e8584291c96e5d6168133621f352bfc1d43cf84e81187fef4962",
"sha512": "bf9fa25242fecaa8e2b58d01758e5d7d9779487594cbb43ec9665d1df5ae967faabc625764715296bb663a88e6c01cca3b862c33e9d093df79e595b47fa68255",
"ssdeep": "12:5DJhWmNJAx9DV1JzAkVTDL4EZFJhudt6JA1uL33k9S/OgRI:ThWm7Ax9DVLAe4EZhueAk3k9SWf",
"summary": None,
"whirlpool": "fdb19c4ed557ce8c1e5d7972008c9e83a5c82501a1057f9dbae083762a653b264e0ddeec25a6933f00fe7273e80bf8066904425119a544ea2161ef8ec9c3ecc0"
},
"file_type": {
"analysis_date": 1548333203.6747785,
"full": "Zip archive data, at least v2.0 to extract",
"mime": "application/zip",
"plugin_version": "1.0",
"summary": {
"application/zip": [
"418a54d78550e8584291c96e5d6168133621f352bfc1d43cf84e81187fef4962_787"
],
"text/plain": [
"d558c9339cb967341d701e3184f863d3928973fccdc1d96042583730b5c7b76a_62",
"faa11db49f32a90b51dfc3f0254f9fd7a7b46d0b570abd47e1943b86d554447a_28",
"289b5a050a83837f192d7129e4c4e02570b94b4924e50159fad5ed1067cfbfeb_20"
]
}
},
"known_vulnerabilities": {
"analysis_date": 1548333209.475375,
"plugin_version": "0.2",
"summary": {},
"system_version": "3.7.1_1548244221"
},
"malware_scanner": {
"analysis_date": 1548333207.3892179,
"md5": "743692a4121ff9f0c492c14a8371a32e",
"number_of_scanners": 1,
"plugin_version": "0.3.1",
"positives": 0,
"scanners": [
"ClamAV"
],
"scans": {
"ClamAV": {
"detected": False,
"result": "clean",
"version": "ClamAV 0.100.2/25326/Thu Jan 24 03:30:43 2019\n"
}
},
"summary": {},
"system_version": "0.2.6"
},
"printable_strings": {
"analysis_date": 1548333208.388212,
"plugin_version": "0.3.4",
"skipped": "blacklisted file type",
"summary": {}
},
"software_components": {
"analysis_date": 1548333204.2639465,
"plugin_version": "0.3.2",
"summary": {
"Test Software 1.2.3": [
"d558c9339cb967341d701e3184f863d3928973fccdc1d96042583730b5c7b76a_62"
]
},
"system_version": "3.7.1_1548244221"
},
"unpacker": {
"analysis_date": 1548333203.557019,
"entropy": 0.5789618884873324,
"number_of_unpacked_files": 3,
"output": "\n7-Zip [64] 16.02 : Copyright (c) 1999-2016 Igor Pavlov : 2016-05-21\np7zip Version 16.02 (locale=en_US.UTF-8,Utf16=on,HugeFiles=on,64 bits,8 CPUs x64)\n\nScanning the drive for archives:\n1 file, 787 bytes (1 KiB)\n\nExtracting archive: /media/data/fact_fw_data/41/418a54d78550e8584291c96e5d6168133621f352bfc1d43cf84e81187fef4962_787\n--\nPath = /media/data/fact_fw_data/41/418a54d78550e8584291c96e5d6168133621f352bfc1d43cf84e81187fef4962_787\nType = zip\nPhysical Size = 787\n\nEverything is Ok\n\nFolders: 2\nFiles: 3\nSize: 110\nCompressed: 787\n",
"plugin_used": "7z",
"plugin_version": "0.7",
"size packed -> unpacked": "459.00 Byte -> 110.00 Byte",
"summary": {
"data lost": [
"418a54d78550e8584291c96e5d6168133621f352bfc1d43cf84e81187fef4962_787"
],
"unpacked": [
"d558c9339cb967341d701e3184f863d3928973fccdc1d96042583730b5c7b76a_62",
"faa11db49f32a90b51dfc3f0254f9fd7a7b46d0b570abd47e1943b86d554447a_28",
"289b5a050a83837f192d7129e4c4e02570b94b4924e50159fad5ed1067cfbfeb_20"
]
}
},
"users_and_passwords": {
"analysis_date": 1548333206.30962,
"plugin_version": "0.4.1",
"summary": {}
}
},
"meta_data": {
"device_class": "Test-Data",
"device_name": "test_container",
"device_part": "",
"hid": "Frauhhofer FKIE test_container v. 0.1",
"number_of_files": 3,
"release_date": "2019-01-24",
"size": 787,
"vendor": "Frauhhofer FKIE",
"version": "0.1"
}
},
"request": {
"uid": "418a54d78550e8584291c96e5d6168133621f352bfc1d43cf84e81187fef4962_787"
},
"request_resource": "/rest/firmware",
"status": 0,
"timestamp": 1548333492
}
src/test/integration/test_latex_code_generation.py 0 → 100644
from tempfile import TemporaryDirectory
from pathlib import Path
from ..data.test_dict import test_dict
from latex_code_generation.code_generation import generate_code
def test_latex_code_generation():
output_dir = TemporaryDirectory()
main_tex_path = Path(output_dir.name, 'main.tex')
generate_code(test_dict, Path(output_dir.name))
assert main_tex_path.exists()
src/test/unit/test_generate_code.py 0 → 100644
from tempfile import TemporaryDirectory
from pathlib import Path
from latex_code_generation.code_generation import _set_jinja_env, _render_template, _write_file
def test_render_template():
test_data = {'meta_data': '123', 'analysis': '456'}
jinja_env = _set_jinja_env(templates_to_use='test')
output = _render_template(test_data, jinja_env, 'render_test')
assert output == 'Test 123 - 456'
def test_write_file():
tmp_dir = TemporaryDirectory()
file_path = Path(tmp_dir.name, 'test.tex')
_write_file('test', file_path)
assert file_path.exists()
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