├── .gitignore
├── .travis.yml
├── Dockerfile
├── LICENSE
├── README.md
├── ocyara
├── __init__.py
└── ocyara.py
├── requirements.txt
├── setup.py
└── tests
├── Example.pdf
├── SSN-example-png-as.jpg
├── SSN-example-png-as.txt
├── SSN-example.bmp
├── SSN-example.gif
├── SSN-example.jpg
├── SSN-example.png
├── SSN-example.tif
├── ascii-file-as.jpg
├── example.yara
├── test_example_pdf.py
├── test_logging.py
├── test_magic.py
└── test_path.py
/.gitignore:
--------------------------------------------------------------------------------
1 | .idea
2 | *.pyc
3 |
--------------------------------------------------------------------------------
/.travis.yml:
--------------------------------------------------------------------------------
1 | sudo: required
2 | dist: trusty
3 | language: python
4 | services:
5 | - docker
6 | env:
7 | - PYTHON_VERSION=3.5
8 | - PYTHON_VERSION=3.6
9 | install:
10 | - docker pull bandrel/ocyara:latest
11 | - docker run --name travis -dt bandrel/ocyara:latest
12 | - docker cp /home/travis/build/bandrel/OCyara travis:/home # need to move this directory into the docker image for testing
13 |
14 | script:
15 | - docker exec travis bash -c "source /home/${PYTHON_VERSION}/bin/activate && cd /home/OCyara && python -m pytest"
16 |
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/Dockerfile:
--------------------------------------------------------------------------------
1 | FROM ubuntu:16.10
2 |
3 | RUN apt-get update
4 | RUN apt-get install -y apt-utils
5 | RUN apt-get install -y python3-dev
6 | RUN apt-get install -y tesseract-ocr libtesseract-dev libleptonica-dev libpng-dev libjpeg-dev libtiff5-dev zlib1g-dev
7 | RUN apt-get install -y python3-pip
8 | RUN apt-get install -y python-pip
9 | RUN apt-get install -y python3
10 | RUN apt-get install -y virtualenv
11 | RUN apt-get install -y git
12 | RUN pip3 install --upgrade pip
13 | RUN apt-get install -y wget
14 | RUN pip3 install cython
15 | RUN wget -O requirements.txt https://raw.githubusercontent.com/bandrel/OCyara/master/requirements.txt && pip3 install -r requirements.txt
16 | RUN pip3 install pytest
17 | RUN git clone https://github.com/bandrel/OCyara.git
18 |
--------------------------------------------------------------------------------
/LICENSE:
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--------------------------------------------------------------------------------
/README.md:
--------------------------------------------------------------------------------
1 | # OCyara
2 | [](https://travis-ci.org/bandrel/OCyara)
3 |
4 | [](https://pypi.python.org/pypi/OCyara/)
5 |
6 | The OCyara module performs OCR (Optical Character Recognition) on image
7 | files and scans them for matches to Yara rules. OCyara also can process
8 | images embedded in PDF files. For more information about Yara, visit
9 | https://virustotal.github.io/yara/.
10 |
11 | ## Installation
12 | ### Operating System Requirements
13 |
14 | - **Python 3.5+**
15 | - **Debian-based Linux distros** are currently the only supported
16 | operating systems. Installation has only been tested on Kali
17 | Rolling and Ubuntu 16.10. (Other Debian-based distros may work as
18 | well, but may require manual compilation of Tesseract and/or Leptonica
19 | to get support for all image types. GIF, and TIFF library support
20 | seems to be troublesome with some Ubuntu LTS installations.)
21 | - **Tesseract OCR API**
22 | To install Tesseract:
23 |
24 | 1. `apt-get update`
25 | 1. Install python3 header files: `apt-get install python3-dev`
26 | 2. Install Tesseract and its required libraries:
27 | `apt-get install tesseract-ocr libtesseract-dev libleptonica-dev
28 | libpng12-dev libjpeg62-dev libtiff5-dev zlib1g-dev`
29 |
30 |
31 |
32 | ### Install Procedure
33 | The easiest way to install OCyara is through the use of pip:
34 |
35 | 1. Ensure all the Operating System Requirements listed above have been
36 | met
37 | 3. Run `pip install cython` (has to be installed separate like this
38 | due to tesserocr currently lacking an "install_requires")
39 | 2. Run `pip install ocyara`
40 |
41 | Along with OCyara, the following other packages will be automatically
42 | installed:
43 | - **cython** (>=0.25.2) A compiler for writing C extensions for the
44 | Python language. Used by the tesserocr python module.
45 | https://pypi.python.org/pypi/Cython/
46 | - **tesserocr** (>=2.1.3) A Python wrapper for the tesseract-ocr API
47 | https://github.com/sirfz/tesserocr
48 | - **yara-python** (>=3.5.0) The Python interface for YARA
49 | https://github.com/VirusTotal/yara-python
50 | - **pillow** (>=4.0.0) Python Imaging Library fork
51 | https://github.com/python-pillow/Pillow
52 | - **tqdm** A fast, extensible progress bar for Python and CLI
53 | https://github.com/tqdm/tqdm
54 | - **colorlog**
55 | A colored formatter for the python logging module
56 | http://pypi.python.org/pypi/colorlog
57 |
58 |
59 | ## Usage
60 |
61 |
62 | ### OCyara Class Usage Examples
63 |
64 | ```python
65 | # Scan the current directory recursively for files that match rules in
66 | # "rulefile.yara"
67 |
68 | from ocyara import OCyara
69 |
70 | ocy = OCyara('./', recursive=True)
71 | ocy.run('rulefile.yara', file_magic=True)
72 | print(ocy.list_matches())
73 | ```
74 |
75 | Returns:
76 | ```
77 | Visa tests/Example.pdf
78 | SSN tests/Example.pdf
79 | American_Express tests/Example.pdf
80 | Diners_Club tests/Example.pdf
81 | JCB tests/Example.pdf
82 | Discover tests/Example.pdf
83 | credit_card tests/Example.pdf
84 | MasterCard tests/Example.pdf
85 | card tests/Example.pdf
86 | ```
87 |
88 | Each line printed has the rule that was matched and the file that
89 | matched it.
90 |
91 | ### CLI usage Example
92 | OCyara is not primarily intended to be used from the command line, but
93 | basic cli capablilities have been implemented to allow for
94 | easily-approachable testing of the library's core functionality.
95 |
96 | ```
97 | usage: ocyara.py [-h] YARA_RULES_FILE TARGET_FILE/S`
98 |
99 | positional arguments:
100 |
101 | YARA_RULES_FILE Path of file containing yara rules
102 | TARGET_FILE/S Directory or file name of images to scan.
103 |
104 | optional arguments:
105 | -h, --help show this help message and exit
106 | ```
107 |
108 | ### OCyara Class Structure
109 |
110 | ```
111 | class OCyara(builtins.object)
112 | | Performs OCR (Optical Character Recognition) on image files and scans for matches to Yara rules.
113 | |
114 | | OCyara also can process images embedded in PDF files.
115 | |
116 | | Methods defined here:
117 | |
118 | | __call__(self)
119 | | Default call which outputs the results with the same output standard as the regular yara program
120 | |
121 | | __init__(self, path:str, recursive=False, worker_count=6, verbose=0) -> None
122 | | Create an OCyara object that can scan the specified directory or file and store the results.
123 | |
124 | | Arguments:
125 | | path -- File or directory to be processed
126 | |
127 | | Keyword Arguments:
128 | | recursive -- Whether the specified path should be recursivly searched for images (default False)
129 | | worker_count -- The number of worker processes that should be spawned when
130 | | run() is executed (default available CPU cores * 2)
131 | | verbose -- An int() from 0-2 that sets the verbosity level.
132 | | 0 is default, 1 is information and 2 is debug
133 | |
134 | | join(self, showprogress=True)
135 | |
136 | | list_matched_rules(self) -> set
137 | | Process the matchedfiles dictionary and return a list of rules that were matched.
138 | |
139 | | list_matches(self, rules=None) -> typing.Dict
140 | | List matched files and thier contexts (if available) in dictionary form.
141 | |
142 | | Keyword Arguments:
143 | |
144 | | rules -- Accepts a string or list of strings indicating specific rules.
145 | | Only matches pertaining to the specified rule/s will be returned. If no
146 | | rules are specified, all matches will be returned.
147 | |
148 | | run(self, yara_rule:str, auto_join=True, file_magic=False, save_context=False) -> None
149 | | Begin multithreaded processing of path files with the specified rule file.
150 | |
151 | | Arguments:
152 | | yara_rule -- A string file path of a Yara rule file
153 | |
154 | | Keyword Arguments:
155 | | auto_join -- If set to True, the main process will stall until all the
156 | | worker processes have completed their work. If set to False, join()
157 | | must be manually called following run() to ensure the queue is
158 | | cleared and all workers have terminated.
159 | |
160 | | show_progress -- Display a progress bar when join() is used.
161 | |
162 | | file_magic -- If file_magic is enabled, ocyara will examine the contents
163 | | of the target files to determine if they are an eligible image file
164 | | type. For example, a JPEG file named 'picture.txt' will be processed by
165 | | the OCR engine. file_magic uses the Linux "file" command.
166 | |
167 | | save_context -- If True, when a file matches a yara rule, the returned
168 | | results dictionary will also include the full ocr text of the matched
169 | | file. This text can be further processed by the user if needed.
170 | |
171 | | show_progress(self) -> None
172 | | Generate a progress bar based on the number of items remaining in queue.
173 | |
174 | | ----------------------------------------------------------------------
175 | | Static methods defined here:
176 | |
177 | | check_file_type(path:str) -> str
178 | | Use the Linux "file" command to determine a file's type based on contents
179 | | instead of file extension.
180 | |
181 | | Arguments:
182 | | path -- A string file path to be processed
183 | |
184 | | ----------------------------------------------------------------------
185 | | Data descriptors defined here:
186 | |
187 | | __dict__
188 | | dictionary for instance variables (if defined)
189 | |
190 | | __weakref__
191 | | list of weak references to the object (if defined)
192 | |
193 | | yara_output
194 | | Returns the same output format as the standard yara program:
195 | | RuleName FileName, FileName
196 | | RuleName FileName...
197 | |
198 | | Where:
199 | | RuleName is the name of the rule that was matched
200 | | FileName is the name of the file in which the match was found
201 | ```
202 |
--------------------------------------------------------------------------------
/ocyara/__init__.py:
--------------------------------------------------------------------------------
1 | from .ocyara import OCyara
2 |
--------------------------------------------------------------------------------
/ocyara/ocyara.py:
--------------------------------------------------------------------------------
1 | #!/usr/bin/env python3
2 | import argparse
3 | import glob
4 | import io
5 | import os
6 | import tempfile
7 | import tesserocr
8 | import yara
9 | from multiprocessing import Process, JoinableQueue, Lock, Manager, cpu_count
10 | from queue import Empty
11 | from time import sleep
12 |
13 | import colorlog
14 | from PIL import Image
15 | from tqdm import tqdm
16 | import subprocess
17 | from typing import Dict, Set, Tuple, Union
18 |
19 |
20 | class OCyara:
21 | """
22 | Performs OCR (Optical Character Recognition) on image files and scans for matches to Yara rules.
23 |
24 | OCyara also can process images embedded in PDF files.
25 | """
26 |
27 | def __init__(self, path: str, recursive=False, worker_count=cpu_count() * 2, verbose=0) -> None:
28 | """
29 | Create an OCyara object that can scan the specified directory or file and store the results.
30 |
31 | Arguments:
32 | path -- File or directory to be processed
33 |
34 | Keyword Arguments:
35 | recursive -- Whether the specified path should be recursivly searched for images (default False)
36 | worker_count -- The number of worker processes that should be spawned when
37 | run() is executed (default available CPU cores * 2)
38 | verbose -- An int() from 0-2 that sets the verbosity level.
39 | 0 is default, 1 is information and 2 is debug
40 | """
41 | self.path = path
42 | self.recursive = recursive
43 | self.q = JoinableQueue()
44 | self.results = {}
45 | self.threads = worker_count
46 | self.lock = Lock()
47 | self.workers = []
48 | if os.path.isdir(self.path):
49 | if self.path[-1] is '/':
50 | self.path += '*'
51 | else:
52 | self.path += '/*'
53 | self.manager = Manager()
54 | self.matchedfiles = None
55 | self.total_items_to_queue = None
56 | self.total_added_to_queue = None
57 | self.queue_items_completed = None
58 | self.tempdir = tempfile.TemporaryDirectory()
59 | handler = colorlog.StreamHandler()
60 | handler.setFormatter(colorlog.ColoredFormatter(
61 | '%(log_color)s%(levelname)s:%(name)s:%(message)s'))
62 | self.logger = colorlog.getLogger('OCyara')
63 | self.logger.addHandler(handler)
64 | if verbose == 1:
65 | self.logger.setLevel('INFO')
66 | elif verbose > 1:
67 | self.logger.setLevel('DEBUG')
68 | else:
69 | self.logger.setLevel('WARN')
70 |
71 | def run(self, yara_rule: str, auto_join=True, show_progress=True, file_magic=False, save_context=False) -> None:
72 | """
73 | Begin multithreaded processing of path files with the specified rule file.
74 |
75 | Arguments:
76 | yara_rule -- A string file path of a Yara rule file
77 |
78 | Keyword Arguments:
79 | auto_join -- If set to True, the main process will stall until all the
80 | worker processes have completed their work. If set to False, join()
81 | must be manually called following run() to ensure the queue is
82 | cleared and all workers have terminated.
83 |
84 | show_progress -- Display a progress bar when join() is used.
85 |
86 | file_magic -- If file_magic is enabled, ocyara will examine the contents
87 | of the target files to determine if they are an eligible image file
88 | type. For example, a JPEG file named 'picture.txt' will be processed by
89 | the OCR engine. file_magic uses the Linux "file" command.
90 |
91 | save_context -- If True, when a file matches a yara rule, the returned
92 | results dictionary will also include the full ocr text of the matched
93 | file. This text can be further processed by the user if needed.
94 | """
95 |
96 | # Populate the queue with work
97 | if type(self.path) == str:
98 | self.logger.debug('Input file detected as a path')
99 | if self.recursive:
100 | self.path = self.path.rstrip('/') + '/**'
101 | all_files = glob.glob(self.path, recursive=self.recursive)
102 | handled_file_extensions = ['png', 'jpg', 'jpeg', 'pdf', 'gif', 'bmp']
103 | handled_mime_types = [
104 | 'image/png', 'image/jpeg', 'application/pdf', 'image/gif', 'image/x-ms-bmp'
105 | ]
106 | # Intialize counters to 0 and create an empty matchedfiles dict
107 | self.total_items_to_queue = self.manager.list([0])
108 | self.total_added_to_queue = self.manager.list([0])
109 | self.queue_items_completed = self.manager.list([0])
110 | self.matchedfiles = self.manager.list()
111 | self.matchedfiles.append({})
112 |
113 | # Determine the number of items that will be queued so workers can exit only after queuing is completed
114 | if file_magic:
115 | # Queue files base on file contents
116 | items_to_queue = [
117 | filepath for filepath in all_files if self.check_file_type(filepath) in handled_mime_types
118 | ]
119 | else:
120 | # Queue files based on extension
121 | items_to_queue = [
122 | filepath for filepath in all_files if filepath.split('.')[-1] in handled_file_extensions
123 | ]
124 | self.total_items_to_queue[0] = len(items_to_queue)
125 | self.logger.info('{0} items detected and will be added to the Queue'.format(self.total_items_to_queue[0]))
126 | # Create and run the workers
127 | self.logger.info('{0} worker processes being generated to process images. from the '
128 | 'queue'.format(self.threads))
129 | for i in range(self.threads):
130 | p = Process(target=self._process_image, args=(yara_rule, save_context))
131 | self.workers.append(p)
132 | p.start()
133 | # Add items to queue for processing
134 | for filepath in items_to_queue:
135 | # Strip jpegs from PDF files and add them to the queue
136 | if filepath.split('.')[-1].upper() == 'PDF':
137 | self._pdf_extract(filepath)
138 | for jpg_file in glob.glob(self.tempdir.name+'/*.jpg'):
139 | self.total_items_to_queue[0] += 1
140 | self.q.put([Image.open(jpg_file), filepath])
141 | self.total_added_to_queue[0] += 1
142 | self.total_items_to_queue[0] -= 1 # Negate PNG file itself (vs jpegs) being added earlier
143 | else:
144 | try:
145 | self.q.put([Image.open(filepath), filepath])
146 | self.total_added_to_queue[0] += 1
147 | except OSError:
148 | self.logger.warning('Warning: {0} is not a proper image file'.format(filepath))
149 | self.total_items_to_queue[0] -= 1
150 | elif type(self.path) == io.BufferedReader:
151 | self.q.put(Image.open(self.path))
152 | self.total_added_to_queue[0] += 1
153 | if auto_join:
154 | self.join(show_progress)
155 |
156 | def show_progress(self) -> None:
157 | """Generate a progress bar based on the number of items remaining in queue."""
158 | previous_queue_items_completed = 0
159 | with tqdm(total=self.total_added_to_queue[0], desc='Processing Images', unit='Image') as progressbar:
160 | while True:
161 | difference = self.queue_items_completed[0] - previous_queue_items_completed
162 | previous_queue_items_completed = self.queue_items_completed[0]
163 | progressbar.update(difference)
164 | if self.queue_items_completed[0] == self.total_added_to_queue[0]:
165 | break
166 | sleep(.25)
167 |
168 | def join(self, showprogress=True):
169 | if showprogress:
170 | self.show_progress()
171 | self.q.join()
172 | for worker in self.workers:
173 | worker.join()
174 |
175 | def list_matches(self, rules_matched=None) -> Dict[str, Set[Tuple[str, Union[str, None]]]]:
176 | """
177 | List matched files and thier contexts (if available) in dictionary form.
178 |
179 | Keyword Arguments:
180 |
181 | rules -- Accepts a string or list of strings indicating specific rules.
182 | Only matches pertaining to the specified rule/s will be returned. If no
183 | rules are specified, all matches will be returned.
184 | """
185 | matches_to_return = {}
186 | if type(rules_matched) is str:
187 | rules_matched = [rules_matched]
188 | if rules_matched is None:
189 | rules_matched = self.list_matched_rules()
190 | # Step through each matched file and see if they matched any of the rules we're interested in.
191 | for filepath, matchedrules_with_contexts in self.matchedfiles[0].items():
192 | for matchedrulename, context in matchedrules_with_contexts:
193 | for rulename in rules_matched:
194 | if matchedrulename == rulename:
195 | try:
196 | matches_to_return[rulename].add((filepath, context))
197 | except KeyError:
198 | matches_to_return[rulename] = {(filepath, context)}
199 | return matches_to_return
200 |
201 | def list_matched_rules(self) -> set:
202 | """Process the matchedfiles dictionary and return a list of rules that were matched."""
203 | rules = set()
204 | for filepath, matchedrules in self.matchedfiles[0].items():
205 | [rules.add(matchedrule[0]) for matchedrule in matchedrules]
206 | return rules
207 |
208 | def _process_image(self, yara_rule: str, save_context: bool) -> None:
209 | """
210 | Perform OCR and yara rule matching as a worker.
211 |
212 | process_image() is used by the run() method to create multiple worker processes for
213 | parallel execution. process_image normally will not be called directly.
214 |
215 | Arguments:
216 | yara_rule -- File path pointing to a Yara rule file
217 | """
218 | context = None
219 | handler = colorlog.StreamHandler()
220 | handler.setFormatter(colorlog.ColoredFormatter(
221 | '%(log_color)s%(levelname)s:%(name)s:%(message)s'))
222 | # Creates a logger object for the individual workers that contains the PID as part of the message header
223 | worker_logger = colorlog.getLogger('worker_'+str(os.getpid()))
224 | worker_logger.addHandler(handler)
225 | worker_logger.setLevel(self.logger.level)
226 | worker_logger.info('PID {0} created to process queue'.format(str(os.getpid())))
227 | while True:
228 | try:
229 | image, filepath = self.q.get(timeout=.25)
230 | except Empty:
231 | if self.total_added_to_queue[0] == self.total_items_to_queue[0]:
232 | worker_logger.debug('Queue Empty PID %d exiting' % os.getpid())
233 | return
234 | else:
235 | worker_logger.debug('Queue still loading')
236 | continue
237 | ocrtext = tesserocr.image_to_text(image)
238 | try:
239 | rules = yara.compile(yara_rule)
240 | except yara.Error:
241 | worker_logger.error('Invalid rule file/rule file not found: {0}'.format(yara_rule))
242 | matches = rules.match(data=ocrtext)
243 | # If there is a match, store the filename and the rule in a dictionary local to this process.
244 | # Create an editable copy of the master manager dict.
245 | with self.lock:
246 | local_results_dict = self.matchedfiles[0]
247 | if matches:
248 | if save_context:
249 | context = ocrtext
250 | for x in matches:
251 | try:
252 | local_results_dict[filepath].append((x.rule, context))
253 | except KeyError:
254 | local_results_dict[filepath] = [(x.rule, context)]
255 | self.matchedfiles[0] = local_results_dict
256 | self.queue_items_completed[0] += 1
257 | self.q.task_done()
258 |
259 | def _pdf_extract(self, pdffile: str) -> None:
260 | """
261 | Extract jpg images from pdf files and save them to temp directory.
262 |
263 | pdf_extract is used by the run() method and not be called directly in most
264 | circumstances.
265 |
266 | Arguments:
267 | pdffile -- A string file path pointing to a PDF
268 | """
269 | self.logger.info('Opening %s and extracting JPG images' % pdffile)
270 | with open(pdffile, "rb") as file:
271 | pdf = file.read()
272 |
273 | startmark = b"\xff\xd8"
274 | startfix = 0
275 | endmark = b"\xff\xd9"
276 | endfix = 2
277 | i = 0
278 | njpg = 0
279 | while True:
280 | istream = pdf.find(b"stream", i)
281 | if istream < 0:
282 | break
283 | istart = pdf.find(startmark, istream, istream + 20)
284 | if istart < 0:
285 | i = istream + 20
286 | continue
287 | iend = pdf.find(b"endstream", istart)
288 | if iend < 0:
289 | raise Exception("Didn't find end of stream!")
290 | iend = pdf.find(endmark, iend - 20)
291 | if iend < 0:
292 | raise Exception("Didn't find end of JPG!")
293 |
294 | istart += startfix
295 | iend += endfix
296 | jpg = pdf[istart:iend]
297 | self.logger.debug('Creating temporary file ' + self.tempdir.name + "/jpg%d.jpg" % njpg)
298 | with open(self.tempdir.name + "/jpg%d.jpg" % njpg, "wb") as jpgfile:
299 | jpgfile.write(jpg)
300 | njpg += 1
301 | i = iend
302 |
303 | @staticmethod
304 | def check_file_type(path: str) -> str:
305 | """
306 | Use the Linux "file" command to determine a file's type based on contents
307 | instead of file extension.
308 |
309 | Arguments:
310 | path -- A string file path to be processed
311 | """
312 | process = subprocess.run(['file', '--mime-type', '-b', path], stdout=subprocess.PIPE)
313 | filemimetype = process.stdout.decode("utf-8").strip()
314 | return filemimetype
315 |
316 | def __call__(self):
317 | """Default call which outputs the results with the same output standard as the regular yara program """
318 | print(ocy.yara_output)
319 |
320 | @property
321 | def yara_output(self) -> str:
322 | """
323 | Returns the same output format as the standard yara program:
324 | RuleName FileName, FileName
325 | RuleName FileName...
326 |
327 | Where:
328 | RuleName is the name of the rule that was matched
329 | FileName is the name of the file in which the match was found
330 | """
331 | output_text = ''
332 | for rule, matched_files_and_contexts in self.list_matches().items():
333 | for matched_file_and_context in matched_files_and_contexts:
334 | output_text += rule + ' ' + matched_file_and_context[0] + '\n'
335 | return output_text
336 |
337 |
338 | if __name__ == '__main__':
339 | parser = argparse.ArgumentParser(description='OCyara performs OCR (Optical Character Recognition) on image '
340 | 'files and scans them for matches to Yara rules '
341 | '(https://virustotal.github.io/yara/). OCyara also can process images '
342 | 'embedded in PDF files.')
343 | parser.add_argument('YARA_RULES_FILE', type=str, help='Path of file containing yara rules')
344 | parser.add_argument('TARGET_FILES', type=str, help='Directory or file name of images to scan.')
345 | parser.add_argument('-v', action='count', help='Enables verbose output, -v for verbose or -vv for very verbose',
346 | default=0)
347 | args = parser.parse_args()
348 | ocy = OCyara(args.TARGET_FILES, verbose=args.v)
349 | ocy.run(args.YARA_RULES_FILE)
350 | ocy()
351 |
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/requirements.txt:
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1 | ocyara
2 | Pillow>=4.0.0
3 | tqdm
4 | Cython>=0.25.2
5 | tesserocr>=2.1.3
6 | yara-python>=3.5.0
7 | colorlog
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/setup.py:
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1 | from setuptools import setup, find_packages
2 |
3 | setup(
4 | name='OCyara',
5 | version='1.0.1',
6 | packages=find_packages(),
7 | url='https://github.com/bandrel/OCyara',
8 | license='GPL v3',
9 | author='Bandrel & ryman1',
10 | author_email='example@example.com',
11 | description='A Yara rule engine that scans images for matches using Optical Character Recognition (OCR). '
12 | 'See the Github page for more information about the Cython, Tesseract, and Leptonica prerequsites.',
13 | install_requires=['Pillow>=4.0.0', 'tqdm', 'Cython>=0.25.2', 'tesserocr>=2.1.3', 'yara-python>=3.5.0', 'colorlog']
14 | )
15 |
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/tests/Example.pdf:
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https://raw.githubusercontent.com/bandrel/OCyara/4dfd5bd1c586f4b4bfa01572ef511e3f19039dd9/tests/Example.pdf
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/tests/SSN-example-png-as.jpg:
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https://raw.githubusercontent.com/bandrel/OCyara/4dfd5bd1c586f4b4bfa01572ef511e3f19039dd9/tests/SSN-example-png-as.jpg
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/tests/SSN-example-png-as.txt:
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https://raw.githubusercontent.com/bandrel/OCyara/4dfd5bd1c586f4b4bfa01572ef511e3f19039dd9/tests/SSN-example-png-as.txt
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/tests/SSN-example.bmp:
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https://raw.githubusercontent.com/bandrel/OCyara/4dfd5bd1c586f4b4bfa01572ef511e3f19039dd9/tests/SSN-example.bmp
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/tests/SSN-example.gif:
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https://raw.githubusercontent.com/bandrel/OCyara/4dfd5bd1c586f4b4bfa01572ef511e3f19039dd9/tests/SSN-example.gif
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/tests/SSN-example.jpg:
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https://raw.githubusercontent.com/bandrel/OCyara/4dfd5bd1c586f4b4bfa01572ef511e3f19039dd9/tests/SSN-example.jpg
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/tests/SSN-example.png:
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https://raw.githubusercontent.com/bandrel/OCyara/4dfd5bd1c586f4b4bfa01572ef511e3f19039dd9/tests/SSN-example.png
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/tests/SSN-example.tif:
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https://raw.githubusercontent.com/bandrel/OCyara/4dfd5bd1c586f4b4bfa01572ef511e3f19039dd9/tests/SSN-example.tif
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/tests/ascii-file-as.jpg:
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1 | 123-45-6789
2 |
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/tests/example.yara:
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1 | rule SSN
2 | {
3 | strings:
4 | $a = /\d{3}-?\d{2}-?\d{4}/
5 | condition:
6 | $a
7 | }
8 |
9 | rule credit_card
10 | {
11 | strings:
12 | $a = /\d{16}/
13 | condition:
14 | $a
15 | }
16 |
17 | rule card
18 | {
19 | strings:
20 | $a = /[Cc]ard/
21 | condition:
22 | $a
23 | }
24 | rule Visa
25 | {
26 | strings:
27 | $visa = /\b4[0-9]{12}([0-9]{3})?\b/
28 | condition:
29 | $visa
30 | }
31 | rule MasterCard
32 | {
33 | strings:
34 | $mc = /\b(5[1-5][0-9]{2}|222[1-9]|22[3-9][0-9]|2[3-6][0-9]{2}|27[01][0-9]|2720)[0-9]{12}\b/
35 | condition:
36 | $mc
37 | }
38 | rule American_Express
39 | {
40 | strings:
41 | $amex = /\b3[47][0-9]{13}\b/
42 | condition:
43 | $amex
44 | }
45 | rule Diners_Club
46 | {
47 | strings:
48 | $diners = /\b3(0[0-5]|[68][0-9])[0-9]{11}\b/
49 | condition:
50 | $diners
51 | }
52 | rule Discover
53 | {
54 | strings:
55 | $discover = /\b6(011|5[0-9]{2})[0-9]{12}\b/
56 | condition:
57 | $discover
58 | }
59 | rule JCB
60 | {
61 | strings:
62 | $jcb = /\b(2131|1800|35\d{3})\d{11}\b/
63 | condition:
64 | $jcb
65 | }
66 |
67 | rule Bogus
68 | {
69 | strings:
70 | $elephant = "Elephant" // just an dummy rule, that should not match in the examples
71 | condition:
72 | $elephant
73 | }
74 |
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/tests/test_example_pdf.py:
--------------------------------------------------------------------------------
1 | #!/usr/env python3
2 | from ocyara import OCyara
3 |
4 |
5 | def num_unique_rule_matches():
6 | return len(ocy.list_matched_rules())
7 |
8 |
9 | def test_number_of_rules():
10 | assert num_unique_rule_matches() == 9
11 |
12 |
13 | def test_example_pdf_rules():
14 | assert ocy.list_matched_rules() == {'card',
15 | 'SSN',
16 | 'credit_card',
17 | 'JCB',
18 | 'Diners_Club',
19 | 'Visa',
20 | 'American_Express',
21 | 'MasterCard',
22 | 'Discover'
23 | }
24 |
25 |
26 | def test_dict_matches():
27 | assert ocy.matchedfiles[0] == {
28 | 'tests/Example.pdf': [('SSN', None), ('credit_card', None), ('card', None), ('Visa', None),
29 | ('MasterCard', None), ('American_Express', None), ('Diners_Club', None),
30 | ('Discover', None), ('JCB', None)]
31 | }
32 |
33 |
34 | ocy = OCyara('tests/Example.pdf')
35 | ocy.run('tests/example.yara')
36 |
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/tests/test_logging.py:
--------------------------------------------------------------------------------
1 | #!/usr/env python3
2 | from ocyara import OCyara
3 |
4 |
5 | def test_valid_log_levels():
6 | keywords = [0, 1, 2, 3, -1]
7 | for verbose_level in keywords:
8 | try:
9 | ocy = OCyara('tests/Example.pdf', verbose=verbose_level)
10 | except TypeError:
11 | assert False
12 |
13 |
14 | def test_invalid_log_levels():
15 | keywords = ['Foo', '', None]
16 | for verbose_level in keywords:
17 | try:
18 | ocy = OCyara('tests/Example.pdf', verbose=verbose_level)
19 | assert False
20 | except TypeError:
21 | continue
22 | assert True
23 |
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/tests/test_magic.py:
--------------------------------------------------------------------------------
1 | #!/usr/env python3
2 | from ocyara import OCyara
3 |
4 |
5 | def test_png():
6 | assert OCyara.check_file_type('tests/SSN-example.png') == 'image/png'
7 |
8 |
9 | def test_jpg():
10 | assert OCyara.check_file_type('tests/SSN-example.jpg') == 'image/jpeg'
11 |
12 |
13 | def test_pdf():
14 | assert OCyara.check_file_type('tests/Example.pdf') == 'application/pdf'
15 |
16 |
17 | def test_tiff():
18 | assert OCyara.check_file_type('tests/SSN-example.tif') == 'image/tiff'
19 |
20 |
21 | def test_gif():
22 | assert OCyara.check_file_type('tests/SSN-example.gif') == 'image/gif'
23 |
24 |
25 | def test_bmp():
26 | assert OCyara.check_file_type('tests/SSN-example.bmp') == 'image/x-ms-bmp'
27 |
28 |
29 | def test_png_as_txt():
30 | assert OCyara.check_file_type('tests/SSN-example-png-as.txt') == 'image/png'
31 |
32 |
33 | def test_png_as_jpg():
34 | assert OCyara.check_file_type('tests/SSN-example-png-as.jpg') == 'image/png'
35 |
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/tests/test_path.py:
--------------------------------------------------------------------------------
1 | #!/usr/env python3
2 | from ocyara import OCyara
3 |
4 |
5 | def num_unique_rule_matches():
6 | return len(ocy.list_matched_rules())
7 |
8 |
9 | def test_number_of_rules():
10 | assert num_unique_rule_matches() == 9
11 |
12 |
13 | def test_example_pdf_rules():
14 | assert ocy.list_matched_rules() == {
15 | 'card',
16 | 'SSN',
17 | 'credit_card',
18 | 'JCB',
19 | 'Diners_Club',
20 | 'Visa',
21 | 'American_Express',
22 | 'MasterCard',
23 | 'Discover'
24 | }
25 |
26 |
27 | def test_dict_matches():
28 | findings = list(map(ocy.matchedfiles[0].get, [
29 | 'tests/SSN-example.png', 'tests/SSN-example-png-as.jpg', 'tests/Example.pdf'
30 | ]))
31 |
32 | assert findings == [
33 | [('SSN', None)],
34 | [('SSN', None)],
35 | [
36 | ('SSN', None), ('credit_card', None), ('card', None), ('Visa', None), ('MasterCard', None),
37 | ('American_Express', None), ('Diners_Club', None), ('Discover', None), ('JCB', None)
38 | ]
39 | ]
40 |
41 |
42 | def test_list_files_matching_rules():
43 | ssn_matches = ocy.list_matches('SSN')
44 | mastercard_matches = ocy.list_matches('MasterCard')
45 | assert (ssn_matches['SSN'], mastercard_matches['MasterCard']) == (
46 | {
47 | ('tests/Example.pdf', None),
48 | ('tests/SSN-example.jpg', None),
49 | ('tests/SSN-example-png-as.jpg', None),
50 | ('tests/SSN-example.png', None),
51 | ('tests/SSN-example.bmp', None)
52 | },
53 | {
54 | ('tests/Example.pdf', None)
55 | }
56 | )
57 |
58 |
59 | def test_list_files_matching_rules_with_context():
60 | ocy2 = OCyara('tests/')
61 | ocy2.run('tests/example.yara', save_context=True)
62 | jcb_matches = ocy2.list_matches('JCB')
63 | assert jcb_matches['JCB'] == (
64 | {
65 | ('tests/Example.pdf', 'Testing1234\n'
66 | '0001273456\n'
67 | '000123456\n'
68 | '\n'
69 | 'Test credit card numbers\n'
70 | 'American Express\n'
71 | '\n'
72 | 'American Express\n'
73 | '\n'
74 | 'American Express Corporate\n'
75 | 'Australian BankCard\n'
76 | '\n'
77 | 'Diners Ciub\n'
78 | '\n'
79 | 'Diners Club\n'
80 | 'Discover\n'
81 | 'Discover\n'
82 | 'JCB\n'
83 | '\n'
84 | 'JCB\n'
85 | 'MasterCard\n'
86 | 'MasterCard\n'
87 | 'Visa\n'
88 | '\n'
89 | 'Visa\n'
90 | '\n'
91 | 'Visa\n'
92 | '\n'
93 | '378282246310005\n'
94 | '\n'
95 | '371449635398431\n'
96 | '\n'
97 | '378734493671000\n'
98 | '\n'
99 | '5610591081018250\n'
100 | '\n'
101 | '30569309025904\n'
102 | '\n'
103 | '38520000023237\n'
104 | '\n'
105 | '6011111111111117\n'
106 | '\n'
107 | '6011000990139424\n'
108 | '\n'
109 | '3530111333300000\n'
110 | '\n'
111 | '3566002020360505\n'
112 | '\n'
113 | '5555555555554444\n'
114 | '\n'
115 | '5105105105105100\n'
116 | '\n'
117 | '4111111111111111\n'
118 | '\n'
119 | '4012888888881881\n'
120 | '\n'
121 | '4222222222222\n'
122 | '\n'
123 | )
124 | }
125 | )
126 |
127 |
128 | def test_yara_output():
129 | assert sorted(ocy.yara_output.strip().split('\n')) == [
130 | 'American_Express tests/Example.pdf',
131 | 'Diners_Club tests/Example.pdf',
132 | 'Discover tests/Example.pdf',
133 | 'JCB tests/Example.pdf',
134 | 'MasterCard tests/Example.pdf',
135 | 'SSN tests/Example.pdf',
136 | 'SSN tests/SSN-example-png-as.jpg',
137 | 'SSN tests/SSN-example.bmp',
138 | 'SSN tests/SSN-example.jpg',
139 | 'SSN tests/SSN-example.png',
140 | 'Visa tests/Example.pdf',
141 | 'card tests/Example.pdf',
142 | 'credit_card tests/Example.pdf'
143 | ]
144 |
145 | ocy = OCyara('tests/')
146 | ocy.run('tests/example.yara')
147 |
148 |
149 | def test_ocyara_rerun():
150 | ocy_rerun_test = OCyara('tests/')
151 | ocy_rerun_test.run('tests/example.yara')
152 | ocy_rerun_test.run('tests/example.yara')
153 | assert ocy_rerun_test.list_matched_rules() == {
154 | 'card',
155 | 'SSN',
156 | 'credit_card',
157 | 'JCB',
158 | 'Diners_Club',
159 | 'Visa',
160 | 'American_Express',
161 | 'MasterCard',
162 | 'Discover'
163 | }
164 |
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