def run(self, task):
# NOTE: used to allow processing of malformed images.
# With default settings they raise errors like "IOError: image file is truncated (0 bytes not processed)".
# See: http://stackoverflow.com/questions/9211719/python-pil-image-error-after-image-load
ImageFile.LOAD_TRUNCATED_IMAGES = True
# Check this kind of analysis should be run on this file type.
# It can be applied only on PNG and JPEG formats.
if "mime_type" in self.data and not (self.data["mime_type"] == "image/png" or self.data["mime_type"] == "image/jpeg"):
return self.results
# Create temporary file.
handle, resaved = tempfile.mkstemp()
tmp_file = str2temp_file(task.get_file_data)
# Open file and resave it.
try:
im = Image.open(tmp_file.name)
im.save(resaved, "JPEG", quality=95)
resaved_im = Image.open(resaved)
except IOError as e:
logger.warning("[Task {0}]: ELA error opening image: {1}".format(task.id, e))
return self.results
finally:
tmp_file.close()
os.close(handle)
os.remove(resaved)
# Trick to convert images like PNG to a format comparable with JPEG.
if im.mode != "RGB":
im = im.convert("RGB")
# Create ELA image.
try:
ela_im = ImageChops.difference(im, resaved_im)
except Exception as e:
logger.warning("[Task {0}]: Unable to calculate ELA difference: {0}".format(task.id, e))
return self.results
# Calculate difference
extrema = ela_im.getextrema()
max_diff = max([ex[1] for ex in extrema])
if not max_diff:
return self.results
scale = 255.0/max_diff
ela_im = ImageEnhance.Brightness(ela_im).enhance(scale)
self.results["ela"]["max_difference"] = max([ex[1] for ex in extrema])
# Resize image if it's too big.
width, height = ela_im.size
if width > 1800:
ela_im.thumbnail([1800, 1800], Image.ANTIALIAS)
# Save image.
try:
img = image2str(ela_im)
self.results["ela"]["ela_image"] = save_file(img, content_type="image/jpeg")
except Exception as e:
logger.warning("[Task {0}]: ELA error saving image: {0}".format(task.id, e))
finally:
return self.results
def run(self, task):
# Save task id for logging.
self.task_id = task.id
# Read metadata from a temp file.
try:
tmp_file = str2temp_file(task.get_file_data)
self.metadata = GExiv2.Metadata()
self.metadata.open_path(str(tmp_file.name))
except Exception as e:
logger.warning("[Task {0}]: Unable to read image metadata: {1}".format(task.id, e))
self.metadata = None
finally:
tmp_file.close()
# Run all analysis.
if self.metadata:
self._get_comment()
self._get_dimensions()
self._get_exif()
self._get_iptc()
self._get_xmp()
self._get_previews()
self._get_gps_data()
return self.results
def run(self, task):
# Read metadata from a temp file.
try:
tmp_file = str2temp_file(task.get_file_data)
self.metadata = GExiv2.Metadata()
self.metadata.open_path(str(tmp_file.name))
except Exception as e:
logger.warning("Unable to read image metadata: {0}".format(e))
self.metadata = None
finally:
tmp_file.close()
# Run all analysis.
if self.metadata:
self._get_comment()
self._get_dimensions()
self._get_exif()
self._get_iptc()
self._get_xmp()
self._get_previews()
self._get_gps_data()
return self.results
