def ConvertJsonDataFile(schema, master_key, table_id, infile, outfile):
"""Encrypts data in a json file based on schema provided.
Arguments:
schema: User defined values and types.
master_key: Key to provide ciphers.
table_id: Used to unique key for each table.
infile: File to be encrypted.
outfile: Location of encrypted file to outputted.
"""
prob_cipher = ecrypto.ProbabilisticCipher(
ecrypto.GenerateProbabilisticCipherKey(master_key, table_id))
pseudonym_cipher = ecrypto.PseudonymCipher(
ecrypto.GeneratePseudonymCipherKey(master_key, table_id))
# TODO(user): ciphers and hash should not use the same key.
string_hasher = ecrypto.StringHash(
ecrypto.GenerateStringHashKey(master_key, table_id))
homomorphic_int_cipher = ecrypto.HomomorphicIntCipher(
ecrypto.GenerateHomomorphicCipherKey(master_key, table_id))
homomorphic_float_cipher = ecrypto.HomomorphicFloatCipher(
ecrypto.GenerateHomomorphicCipherKey(master_key, table_id))
_ValidateJsonDataFile(schema, infile)
with open(infile, 'rb') as in_file:
with open(outfile, 'wb') as out_file:
for line in in_file:
data = json.loads(line)
data = _StrToUnicode(data)
rewritten_data = _ConvertJsonField(
data, schema, prob_cipher, pseudonym_cipher, string_hasher,
homomorphic_int_cipher, homomorphic_float_cipher)
rewritten_data = json.dumps(rewritten_data)
out_file.write(rewritten_data + '\n')
def testDecryptGroupConcatValues(self):
cars_schema = test_util.GetCarsSchema()
jobs_schema = test_util.GetJobsSchema()
master_key = test_util.GetMasterKey()
query = 'GROUP_CONCAT(%sModel)' % util.PROBABILISTIC_PREFIX
cipher = ecrypto.ProbabilisticCipher(master_key)
ciphers = {util.PROBABILISTIC_PREFIX: cipher}
unencrypted_values = ([['A', 'B', 'C', 'D'], ['1', '2', '3', '4'],
['Hello', 'Bye']])
table = []
for values in unencrypted_values:
encrypted_values = []
for token in values:
encrypted_values.append(cipher.Encrypt(unicode(token)))
table.append([','.join(encrypted_values), random.random()])
table.insert(0, [None, None])
column = encrypted_bigquery_client._DecryptGroupConcatValues(
query, table, 0, ciphers, cars_schema, util.PROBABILISTIC_PREFIX)
self.assertEqual(column, [
util.LiteralToken('null', None),
util.StringLiteralToken('"A,B,C,D"'),
util.StringLiteralToken('"1,2,3,4"'),
util.StringLiteralToken('"Hello,Bye"')
])
query = (
'GROUP_CONCAT(citiesLived.job.%sposition) within citiesLived.job' %
util.PSEUDONYM_PREFIX)
cipher = ecrypto.PseudonymCipher(master_key)
ciphers = {util.PSEUDONYM_PREFIX: cipher}
table = []
for values in unencrypted_values:
encrypted_values = []
for token in values:
encrypted_values.append(cipher.Encrypt(unicode(token)))
table.append([','.join(encrypted_values)])
column = encrypted_bigquery_client._DecryptGroupConcatValues(
query, table, 0, ciphers, jobs_schema, util.PSEUDONYM_PREFIX)
self.assertEqual(column, [
util.StringLiteralToken('"A,B,C,D"'),
util.StringLiteralToken('"1,2,3,4"'),
util.StringLiteralToken('"Hello,Bye"')
])
query = '%sModel' % util.PROBABILISTIC_PREFIX
self.assertRaises(ValueError,
encrypted_bigquery_client._DecryptGroupConcatValues,
query, table, 0, ciphers, cars_schema,
util.PROBABILISTIC_PREFIX)
query = (
'GROUP_CONCAT(citiesLived.%snumberOfYears) within citiesLived' %
util.HOMOMORPHIC_FLOAT_PREFIX)
self.assertRaises(bigquery_client.BigqueryInvalidQueryError,
encrypted_bigquery_client._DecryptGroupConcatValues,
query, table, 0, ciphers, jobs_schema,
util.HOMOMORPHIC_FLOAT_PREFIX)
def Query(self, query, **kwds):
"""Execute the given query, returning the created job and info for print.
Arguments:
query: Query to execute.
**kwds: Passed on to BigqueryClient.ExecuteJob.
Returns:
The resulting job info and other info necessary for printing.
"""
self._CheckKeyfileFlag()
master_key = load_lib.ReadMasterKeyFile(self.master_key_filename)
try:
clauses = parser.ParseQuery(query)
except ParseException as e:
raise bigquery_client.BigqueryInvalidQueryError(
e, None, None, None)
if clauses['FROM']:
table_id = '%s_%s' % (clauses['FROM'][0],
self._GetTableCreationTime(
clauses['FROM'][0]))
hashed_table_key, table_version, table_schema = self._GetEBQTableInfo(
clauses['FROM'][0])
hashed_master_key = hashlib.sha1(master_key)
# pylint: disable=too-many-function-args
hashed_master_key = base64.b64encode(hashed_master_key.digest())
if hashed_master_key != hashed_table_key:
raise bigquery_client.BigqueryAccessDeniedError(
'Invalid master key for this table.', None, None, None)
if table_version != util.EBQ_TABLE_VERSION:
raise bigquery_client.BigqueryNotFoundError(
'Invalid table version.', None, None, None)
cipher = ecrypto.ProbabilisticCipher(master_key)
orig_schema = zlib.decompress(
cipher.Decrypt(base64.b64decode(table_schema), raw=True))
orig_schema = json.loads(orig_schema.decode('utf-8'))
else:
table_id = None
orig_schema = []
manifest = query_lib.QueryManifest.Generate()
rewritten_query, print_args = query_lib.RewriteQuery(
clauses, orig_schema, master_key, table_id, manifest)
job = super(EncryptedBigqueryClient,
self).Query(rewritten_query, **kwds)
self._LoadJobStatistics(manifest, job)
printer = EncryptedTablePrinter(**print_args)
bq.Factory.ClientTablePrinter.SetTablePrinter(printer)
return job
def CreateTable(self,
reference,
ignore_existing=False,
schema=None,
description=None,
friendly_name=None,
expiration=None):
"""Create a table corresponding to TableReference.
Arguments:
reference: the TableReference to create.
ignore_existing: (boolean, default False) If False, raise an exception if
the dataset already exists.
schema: An required schema (also requires a master key).
description: an optional table description.
friendly_name: an optional friendly name for the table.
expiration: optional expiration time in milliseconds since the epoch.
Raises:
TypeError: if reference is not a TableReference.
BigqueryDuplicateError: if reference exists and ignore_existing
is False.
"""
if schema is None:
raise bigquery_client.BigqueryNotFoundError(
'A schema must be specified when making a table.', None, None,
None)
self._CheckKeyfileFlag()
schema = load_lib.ReadSchemaFile(schema)
master_key = load_lib.ReadMasterKeyFile(self.master_key_filename, True)
# pylint: disable=too-many-function-args
hashed_key = base64.b64encode(hashlib.sha1(master_key).digest())
cipher = ecrypto.ProbabilisticCipher(master_key)
pretty_schema = json.dumps(schema)
pretty_schema = pretty_schema.encode('utf-8')
pretty_schema = zlib.compress(pretty_schema)
encrypted_schema = base64.b64encode(cipher.Encrypt(pretty_schema))
if description is None:
description = ''
new_description = util.ConstructTableDescription(
description, hashed_key, util.EBQ_TABLE_VERSION, encrypted_schema)
new_schema = load_lib.RewriteSchema(schema)
super(EncryptedBigqueryClient,
self).CreateTable(reference, ignore_existing, new_schema,
new_description, friendly_name, expiration)
def UpdateTable(self,
reference,
schema=None,
description=None,
friendly_name=None,
expiration=None):
"""Updates a table.
Arguments:
reference: the DatasetReference to update.
schema: an optional schema.
description: an optional table description.
friendly_name: an optional friendly name for the table.
expiration: optional expiration time in milliseconds since the epoch.
"""
if schema:
self._CheckKeyfileFlag()
if description:
hashed_table_key, table_version, table_schema = (
self._GetEBQTableInfo(str(reference)))
if schema:
master_key = load_lib.ReadMasterKeyFile(
self.master_key_filename)
# pylint: disable=too-many-function-args
hashed_key = base64.b64encode(
hashlib.sha1(master_key).digest())
if hashed_key != hashed_table_key:
raise bigquery_client.BigqueryAccessDeniedError(
'Invalid master key for this table.', None, None, None)
cipher = ecrypto.ProbabilisticCipher(master_key)
real_schema = json.dumps(load_lib.RewriteSchema(schema))
real_schema = str.encode('utf-8')
table_schema = base64.b64encode(
cipher.Encrypt(zlib.compress(real_schema)))
description = util.ConstructTableDescription(
description, hashed_table_key, table_version, table_schema)
# Rewrite the schema if the schema is to be updated.
if schema:
schema = load_lib.RewriteSchema(schema)
super(EncryptedBigqueryClient,
self).UpdateTable(reference, schema, description, friendly_name,
expiration)
def ConvertJsonDataFile(schema, master_key, table_id, infile, outfile):
"""Encrypts data in a json file based on schema provided.
Arguments:
schema: User defined values and types.
master_key: Key to provide ciphers.
table_id: Used to unique key for each table.
infile: File to be encrypted.
outfile: Location of encrypted file to outputted.
"""
prob_cipher = ecrypto.ProbabilisticCipher(
ecrypto.GenerateProbabilisticCipherKey(master_key, table_id))
pseudonym_cipher = ecrypto.PseudonymCipher(
ecrypto.GeneratePseudonymCipherKey(master_key, table_id))
# TODO(user): ciphers and hash should not use the same key.
string_hasher = ecrypto.StringHash(
ecrypto.GenerateStringHashKey(master_key, table_id))
homomorphic_int_cipher = ecrypto.HomomorphicIntCipher(
ecrypto.GenerateHomomorphicCipherKey(master_key, table_id))
homomorphic_float_cipher = ecrypto.HomomorphicFloatCipher(
ecrypto.GenerateHomomorphicCipherKey(master_key, table_id))
_ValidateJsonDataFile(schema, infile)
with open(infile, 'rb') as in_file:
with open(outfile, 'wb') as out_file:
for line in in_file:
data = json.loads(line)
data = _StrToUnicode(data)
rewritten_data = _ConvertJsonField(data, schema, prob_cipher,
pseudonym_cipher,
string_hasher,
homomorphic_int_cipher,
homomorphic_float_cipher)
# When python prints unicode strings, it uses single quotes and
# prepends a u before the string (such as u'Hello'). Json does
# understand this and will only allow strings of double quotes
# without any prefixes, therefore we must substitute to fit
# the criteria.
rewritten_data = str(rewritten_data).replace('u\'', '"')
rewritten_data = rewritten_data.replace('\'', '"')
out_file.write(rewritten_data + '\n')
def setUp(self):
"""Run once for each test in the class."""
self.cipher = ecrypto.ProbabilisticCipher(_KEY1)
def ConvertCsvDataFile(schema, master_key, table_id, infile, outfile):
"""Reads utf8 csv data, encrypts and stores into a new csv utf8 data file."""
prob_cipher = ecrypto.ProbabilisticCipher(
ecrypto.GenerateProbabilisticCipherKey(master_key, table_id))
pseudonym_cipher = ecrypto.PseudonymCipher(
ecrypto.GeneratePseudonymCipherKey(master_key, table_id))
# TODO(user): ciphers and hash should not use the same key.
string_hasher = ecrypto.StringHash(
ecrypto.GenerateStringHashKey(master_key, table_id))
homomorphic_int_cipher = ecrypto.HomomorphicIntCipher(
ecrypto.GenerateHomomorphicCipherKey(master_key, table_id))
homomorphic_float_cipher = ecrypto.HomomorphicFloatCipher(
ecrypto.GenerateHomomorphicCipherKey(master_key, table_id))
with open(infile, 'rb') as in_file:
with open(outfile, 'wb') as out_file:
num_columns = len(schema)
csv_writer = csv.writer(out_file)
_ValidateCsvDataFile(schema, infile)
csv_reader = _Utf8CsvReader(in_file, csv_writer)
for row in csv_reader:
new_row = []
if len(row) != num_columns:
raise EncryptConvertError(
'Number of fields in schema do not match '
'in row: %s' % row)
for i in xrange(num_columns):
encrypt_mode = schema[i]['encrypt']
if encrypt_mode == 'none':
new_row.append(row[i].encode('utf-8'))
elif encrypt_mode == 'probabilistic':
new_row.append(
prob_cipher.Encrypt(row[i]).encode('utf-8'))
elif encrypt_mode == 'pseudonym':
new_row.append(
pseudonym_cipher.Encrypt(row[i]).encode('utf-8'))
elif encrypt_mode == 'homomorphic' and schema[i][
'type'] == 'integer':
new_row.append(
homomorphic_int_cipher.Encrypt(long(
row[i])).encode('utf-8'))
elif encrypt_mode == 'homomorphic' and schema[i][
'type'] == 'float':
new_row.append(
homomorphic_float_cipher.Encrypt(float(
row[i])).encode('utf-8'))
elif encrypt_mode == 'searchwords':
if 'searchwords_separator' in schema[i]:
searchwords_separator = schema[i][
'searchwords_separator']
else:
searchwords_separator = None
if 'max_word_sequence' in schema[i]:
max_word_sequence = schema[i]['max_word_sequence']
else:
max_word_sequence = 5
new_row.append(
string_hasher.GetHashesForWordSubsequencesWithIv(
util.SEARCHWORDS_PREFIX + schema[i]['name'],
row[i],
separator=searchwords_separator,
max_sequence_len=max_word_sequence).encode(
'utf-8'))
elif encrypt_mode == 'probabilistic_searchwords':
if 'searchwords_separator' in schema[i]:
searchwords_separator = schema[i][
'searchwords_separator']
else:
searchwords_separator = None
if 'max_word_sequence' in schema[i]:
max_word_sequence = schema[i]['max_word_sequence']
else:
max_word_sequence = 5
new_row.append(
string_hasher.GetHashesForWordSubsequencesWithIv(
util.SEARCHWORDS_PREFIX + schema[i]['name'],
row[i],
separator=searchwords_separator,
max_sequence_len=max_word_sequence).encode(
'utf-8'))
new_row.append(
prob_cipher.Encrypt(row[i]).encode('utf-8'))
csv_writer.writerow(new_row)
def _DecryptRows(fields,
rows,
master_key,
table_id,
schema,
query_list,
aggregation_query_list,
unencrypted_query_list,
manifest=None):
"""Decrypts all values in rows.
Arguments:
fields: Column names.
rows: Table values.
master_key: Key to get ciphers.
table_id: Used to generate keys.
schema: Represents information about fields.
query_list: List of fields that were queried.
aggregation_query_list: List of aggregations of fields that were queried.
unencrypted_query_list: List of unencrypted expressions.
manifest: optional, query_lib.QueryManifest instance.
Returns:
A dictionary that returns for each query, a list of decrypted values.
Raises:
bigquery_client.BigqueryInvalidQueryError: User trying to query for a
SEARCHWORD encrypted field. SEARCHWORD encrypted fields cannot be decrypted.
"""
# create ciphers for decryption
prob_cipher = ecrypto.ProbabilisticCipher(
ecrypto.GenerateProbabilisticCipherKey(master_key, table_id))
pseudonym_cipher = ecrypto.PseudonymCipher(
ecrypto.GeneratePseudonymCipherKey(master_key, table_id))
homomorphic_int_cipher = ecrypto.HomomorphicIntCipher(
ecrypto.GenerateHomomorphicCipherKey(master_key, table_id))
homomorphic_float_cipher = ecrypto.HomomorphicFloatCipher(
ecrypto.GenerateHomomorphicCipherKey(master_key, table_id))
ciphers = {
util.PROBABILISTIC_PREFIX: prob_cipher,
util.PSEUDONYM_PREFIX: pseudonym_cipher,
util.HOMOMORPHIC_INT_PREFIX: homomorphic_int_cipher,
util.HOMOMORPHIC_FLOAT_PREFIX: homomorphic_float_cipher,
}
queried_values = {}
for query in query_list:
if len(query.split(' ')) >= 3 and query.split(' ')[-2] == 'AS':
queried_values[' '.join(query.split(' ')[:-2])] = []
else:
queried_values[query] = []
for query in aggregation_query_list:
queried_values[query] = []
for i in xrange(len(unencrypted_query_list)):
queried_values['%s%d_' % (util.UNENCRYPTED_ALIAS_PREFIX, i)] = []
# If a manifest is supplied rewrite the column names according to any
# computed aliases that were used. Otherwise, resort to the old scheme
# of substituting the '.' in multidimensional schemas in/out.
if manifest is not None:
for i in xrange(len(fields)):
# TODO(user): This is a hash lookup on every column name.
# The lookup is efficient and the column names are sufficiently random
# as compared to likely human language column names such that false
# hits should not be possible. However this may need future revision.
n = manifest.GetColumnNameForAlias(fields[i]['name'])
if n is not None:
fields[i]['name'] = n
else:
for i in xrange(len(fields)):
fields[i]['name'] = fields[i]['name'].replace(
util.PERIOD_REPLACEMENT, '.')
for i in xrange(len(fields)):
encrypted_name = fields[i]['name'].split('.')[-1]
if fields[i]['type'] == 'TIMESTAMP':
queried_values[fields[i]['name']] = _GetTimestampValues(rows, i)
elif encrypted_name.startswith(util.PROBABILISTIC_PREFIX):
queried_values[fields[i]['name']] = (_DecryptValues(
fields[i]['name'], rows, i, ciphers, schema,
util.PROBABILISTIC_PREFIX))
elif encrypted_name.startswith(util.PSEUDONYM_PREFIX):
queried_values[fields[i]['name']] = (_DecryptValues(
fields[i]['name'], rows, i, ciphers, schema,
util.PSEUDONYM_PREFIX))
elif encrypted_name.startswith(util.SEARCHWORDS_PREFIX):
raise bigquery_client.BigqueryInvalidQueryError(
'Cannot decrypt searchwords encryption. Decryption of SEARCHWORDS '
'is limited to PROBABILISTIC_SEARCHWORDS encryption.', None,
None, None)
elif encrypted_name.startswith(util.HOMOMORPHIC_INT_PREFIX):
queried_values[fields[i]['name']] = (_DecryptValues(
fields[i]['name'], rows, i, ciphers, schema,
util.HOMOMORPHIC_INT_PREFIX))
elif encrypted_name.startswith(util.HOMOMORPHIC_FLOAT_PREFIX):
queried_values[fields[i]['name']] = (_DecryptValues(
fields[i]['name'], rows, i, ciphers, schema,
util.HOMOMORPHIC_FLOAT_PREFIX))
elif (encrypted_name.startswith(util.UNENCRYPTED_ALIAS_PREFIX)
and encrypted_name.endswith('_')):
queried_values[fields[i]['name']] = (_GetUnencryptedValuesWithType(
rows, i, fields[i]['type']))
elif encrypted_name.startswith('f') and encrypted_name.endswith('_'):
index = int(fields[i]['name'][1:-1])
original_fieldname = aggregation_query_list[index]
original_fieldname = original_fieldname.strip()
if (len(original_fieldname.split(' ')) >= 3
and original_fieldname.split(' ')[-2].lower() == 'within'):
actual_field = original_fieldname.split(' ')[:-2]
actual_field = ' '.join(actual_field)
else:
actual_field = original_fieldname
if original_fieldname.startswith(util.GROUP_CONCAT_PREFIX):
concat_field = actual_field.split(
util.GROUP_CONCAT_PREFIX)[1][:-1].strip()
encrypted_name = concat_field.split('.')[-1]
if encrypted_name.startswith(util.PROBABILISTIC_PREFIX):
queried_values[original_fieldname] = (
_DecryptGroupConcatValues(original_fieldname, rows, i,
ciphers, schema,
util.PROBABILISTIC_PREFIX))
elif encrypted_name.startswith(util.PSEUDONYM_PREFIX):
queried_values[original_fieldname] = (
_DecryptGroupConcatValues(original_fieldname, rows, i,
ciphers, schema,
util.PSEUDONYM_PREFIX))
elif (encrypted_name.startswith(util.HOMOMORPHIC_INT_PREFIX)
or encrypted_name.startswith(
util.HOMOMORPHIC_FLOAT_PREFIX)):
raise bigquery_client.BigqueryInvalidQueryError(
'GROUP_CONCAT only accepts string type.', None, None,
None)
elif encrypted_name.startswith(util.SEARCHWORDS_PREFIX):
raise bigquery_client.BigqueryInvalidQueryError(
'Invalid query, cannot recover searchwords encryption.',
None, None, None)
else:
for j in xrange(len(rows)):
queried_values[original_fieldname].append(rows[j][i])
elif (original_fieldname.startswith('COUNT(')
or original_fieldname.startswith('AVG(')
or original_fieldname.startswith('SUM(')):
queried_values[original_fieldname] = (
_GetUnencryptedValuesWithType(rows, i, fields[i]['type']))
elif original_fieldname.startswith('TOP('):
fieldname = actual_field.split('TOP(')[1][:-1].strip()
fieldname = fieldname.split(',')[0].strip()
if fieldname.split('.')[-1].startswith(util.PSEUDONYM_PREFIX):
queried_values[original_fieldname] = (_DecryptValues(
fieldname, rows, i, ciphers, schema,
util.PSEUDONYM_PREFIX))
else:
queried_values[original_fieldname] = (
_GetUnencryptedValues(original_fieldname, rows, i,
schema))
elif original_fieldname.startswith(util.PAILLIER_SUM_PREFIX):
sum_argument = original_fieldname.split(
util.PAILLIER_SUM_PREFIX)[1]
sum_argument = sum_argument.split(',')[0][:-1]
sum_argument = sum_argument.split('.')[-1]
real_fieldname = original_fieldname.split(
util.PAILLIER_SUM_PREFIX)[1]
real_fieldname = real_fieldname.split(',')[0][:-1]
if sum_argument.startswith(util.HOMOMORPHIC_INT_PREFIX):
queried_values[original_fieldname] = (_DecryptValues(
real_fieldname, rows, i, ciphers, schema,
util.HOMOMORPHIC_INT_PREFIX))
elif sum_argument.startswith(util.HOMOMORPHIC_FLOAT_PREFIX):
queried_values[original_fieldname] = (_DecryptValues(
real_fieldname, rows, i, ciphers, schema,
util.HOMOMORPHIC_FLOAT_PREFIX))
else:
queried_values[fields[i]['name']] = (
_GetUnencryptedValuesWithType(rows, i, fields[i]['type']))
else:
queried_values[fields[i]['name']] = (_GetUnencryptedValuesWithType(
rows, i, fields[i]['type']))
return queried_values
def Load(self, destination_table, source, schema=None, **kwds):
"""Encrypt the given data and then load it into BigQuery.
The job will execute synchronously if sync=True is provided as an
argument.
Args:
destination_table: TableReference to load data into.
source: String specifying source data to load.
schema: The schema that defines fields to be loaded.
**kwds: Passed on to self.ExecuteJob.
Returns:
The resulting job info.
"""
self._CheckKeyfileFlag()
self._CheckSchemaFile(schema)
# To make encrypting more secure, we use different keys for each table
# and cipher. To generate a different key for each table, we need a distinct
# table identifier for each table. A table name is not secure since a table
# can be deleted and created with the same name and, thus the same key. The
# only distinct identifier happens to be creation time. Therefore, we must
# construct a table if it does not exist so we can use the creation time
# to encrypt values.
try:
self.CreateTable(destination_table, schema=schema)
except bigquery_client.BigqueryDuplicateError:
pass # Table already exists.
temp_dir = tempfile.mkdtemp()
orig_schema = load_lib.ReadSchemaFile(schema)
new_schema = load_lib.RewriteSchema(orig_schema)
new_schema_file = '%s/schema.enc_schema' % temp_dir
# write the new schema as a json file
with open(new_schema_file, 'wt') as f:
json.dump(new_schema, f, indent=2)
new_source_file = '%s/data.enc_data' % temp_dir
# TODO(user): Put the filepath to the master key in .bigqueryrc file.
master_key = load_lib.ReadMasterKeyFile(self.master_key_filename, True)
table_name = str(destination_table).split(':')[-1]
table_id = '%s_%s' % (
table_name, self._GetTableCreationTime(str(destination_table)))
hashed_table_key, table_version, table_schema = self._GetEBQTableInfo(
str(destination_table))
hashed_master_key = hashlib.sha1(master_key)
# pylint: disable=too-many-function-args
hashed_master_key = base64.b64encode(hashed_master_key.digest())
if hashed_master_key != hashed_table_key:
raise bigquery_client.BigqueryAccessDeniedError(
'Invalid master key for this table.', None, None, None)
if table_version != util.EBQ_TABLE_VERSION:
raise bigquery_client.BigqueryNotFoundError(
'Invalid table version.', None, None, None)
# TODO(user): Generate a different key.
cipher = ecrypto.ProbabilisticCipher(master_key)
table_schema = cipher.Decrypt(base64.b64decode(table_schema), raw=True)
table_schema = zlib.decompress(table_schema)
table_schema = table_schema.decode('utf-8')
table_schema = json.loads(table_schema)
if table_schema != orig_schema:
raise bigquery_client.BigqueryAccessDeniedError(
'Invalid schema for this table.', None, None, None)
if kwds['source_format'] == 'NEWLINE_DELIMITED_JSON':
load_lib.ConvertJsonDataFile(orig_schema, master_key, table_id,
source, new_source_file)
elif kwds['source_format'] == 'CSV' or not kwds['source_format']:
load_lib.ConvertCsvDataFile(orig_schema, master_key, table_id,
source, new_source_file)
else:
raise app.UsageError(
'Currently, we do not allow loading from file types other than\n'
'NEWLINE_DELIMITED_JSON and CSV.')
job = super(EncryptedBigqueryClient, self).Load(destination_table,
new_source_file,
schema=new_schema_file,
**kwds)
try:
shutil.rmtree(temp_dir)
except OSError:
raise OSError('Temp file deleted by user before termination.')
return job
def _DecryptRows(fields, rows, master_key, table_id, schema, query_list,
aggregation_query_list, unencrypted_query_list):
"""Decrypts all values in rows.
Arguments:
fields: Column names.
rows: Table values.
master_key: Key to get ciphers.
table_id: Used to generate keys.
schema: Represents information about fields.
query_list: List of fields that were queried.
aggregation_query_list: List of aggregations of fields that were queried.
unencrypted_query_list: List of unencrypted expressions.
Returns:
A dictionary that returns for each query, a list of decrypted values.
Raises:
bigquery_client.BigqueryInvalidQueryError: User trying to query for a
SEARCHWORD encrypted field. SEARCHWORD encrypted fields cannot be decrypted.
"""
# create ciphers for decryption
prob_cipher = ecrypto.ProbabilisticCipher(
ecrypto.GenerateProbabilisticCipherKey(master_key, table_id))
pseudonym_cipher = ecrypto.PseudonymCipher(
ecrypto.GeneratePseudonymCipherKey(master_key, table_id))
homomorphic_int_cipher = ecrypto.HomomorphicIntCipher(
ecrypto.GenerateHomomorphicCipherKey(master_key, table_id))
homomorphic_float_cipher = ecrypto.HomomorphicFloatCipher(
ecrypto.GenerateHomomorphicCipherKey(master_key, table_id))
ciphers = {
util.PROBABILISTIC_PREFIX: prob_cipher,
util.PSEUDONYM_PREFIX: pseudonym_cipher,
util.HOMOMORPHIC_INT_PREFIX: homomorphic_int_cipher,
util.HOMOMORPHIC_FLOAT_PREFIX: homomorphic_float_cipher,
}
queried_values = {}
for query in query_list:
if len(query.split(' ')) >= 3 and query.split(' ')[-2] == 'AS':
queried_values[' '.join(query.split(' ')[:-2])] = []
else:
queried_values[query] = []
for query in aggregation_query_list:
queried_values[query] = []
for i in xrange(len(unencrypted_query_list)):
queried_values['%s%d_' % (util.UNENCRYPTED_ALIAS_PREFIX, i)] = []
for i in xrange(len(fields)):
fields[i]['name'] = fields[i]['name'].replace(util.PERIOD_REPLACEMENT,
'.')
encrypted_name = fields[i]['name'].split('.')[-1]
if fields[i]['type'] == 'TIMESTAMP':
queried_values[fields[i]['name']] = _GetTimestampValues(rows, i)
elif encrypted_name.startswith(util.PROBABILISTIC_PREFIX):
queried_values[fields[i]['name']] = (_DecryptValues(
fields[i]['name'], rows, i, ciphers, schema,
util.PROBABILISTIC_PREFIX))
elif encrypted_name.startswith(util.PSEUDONYM_PREFIX):
queried_values[fields[i]['name']] = (_DecryptValues(
fields[i]['name'], rows, i, ciphers, schema,
util.PSEUDONYM_PREFIX))
elif encrypted_name.startswith(util.SEARCHWORDS_PREFIX):
raise bigquery_client.BigqueryInvalidQueryError(
'Cannot decrypt searchwords encryption. Decryption of SEARCHWORDS '
'is limited to PROBABILISTIC_SEARCHWORDS encryption.', None,
None, None)
elif encrypted_name.startswith(util.HOMOMORPHIC_INT_PREFIX):
queried_values[fields[i]['name']] = (_DecryptValues(
fields[i]['name'], rows, i, ciphers, schema,
util.HOMOMORPHIC_INT_PREFIX))
elif encrypted_name.startswith(util.HOMOMORPHIC_FLOAT_PREFIX):
queried_values[fields[i]['name']] = (_DecryptValues(
fields[i]['name'], rows, i, ciphers, schema,
util.HOMOMORPHIC_FLOAT_PREFIX))
elif (encrypted_name.startswith(util.UNENCRYPTED_ALIAS_PREFIX)
and encrypted_name.endswith('_')):
queried_values[fields[i]['name']] = (_GetUnencryptedValuesWithType(
rows, i, fields[i]['type']))
elif encrypted_name.startswith('f') and encrypted_name.endswith('_'):
index = int(fields[i]['name'][1:-1])
original_fieldname = aggregation_query_list[index]
original_fieldname = original_fieldname.strip()
if (len(original_fieldname.split(' ')) >= 3
and original_fieldname.split(' ')[-2].lower() == 'within'):
actual_field = original_fieldname.split(' ')[:-2]
actual_field = ' '.join(actual_field)
else:
actual_field = original_fieldname
if original_fieldname.startswith(util.GROUP_CONCAT_PREFIX):
concat_field = actual_field.split(
util.GROUP_CONCAT_PREFIX)[1][:-1].strip()
encrypted_name = concat_field.split('.')[-1]
if encrypted_name.startswith(util.PROBABILISTIC_PREFIX):
queried_values[original_fieldname] = (
_DecryptGroupConcatValues(original_fieldname, rows, i,
ciphers, schema,
util.PROBABILISTIC_PREFIX))
elif encrypted_name.startswith(util.PSEUDONYM_PREFIX):
queried_values[original_fieldname] = (
_DecryptGroupConcatValues(original_fieldname, rows, i,
ciphers, schema,
util.PSEUDONYM_PREFIX))
elif (encrypted_name.startswith(util.HOMOMORPHIC_INT_PREFIX)
or encrypted_name.startswith(
util.HOMOMORPHIC_FLOAT_PREFIX)):
raise bigquery_client.BigqueryInvalidQueryError(
'GROUP_CONCAT only accepts string type.', None, None,
None)
elif encrypted_name.startswith(util.SEARCHWORDS_PREFIX):
raise bigquery_client.BigqueryInvalidQueryError(
'Invalid query, cannot recover searchwords encryption.',
None, None, None)
else:
for j in xrange(len(rows)):
queried_values[original_fieldname].append(rows[j][i])
elif (original_fieldname.startswith('COUNT(')
or original_fieldname.startswith('AVG(')
or original_fieldname.startswith('SUM(')):
queried_values[original_fieldname] = (
_GetUnencryptedValuesWithType(rows, i, fields[i]['type']))
elif original_fieldname.startswith('TOP('):
fieldname = actual_field.split('TOP(')[1][:-1].strip()
fieldname = fieldname.split(',')[0].strip()
if fieldname.split('.')[-1].startswith(util.PSEUDONYM_PREFIX):
queried_values[original_fieldname] = (_DecryptValues(
fieldname, rows, i, ciphers, schema,
util.PSEUDONYM_PREFIX))
else:
queried_values[original_fieldname] = (
_GetUnencryptedValues(original_fieldname, rows, i,
schema))
elif original_fieldname.startswith(util.PAILLIER_SUM_PREFIX):
sum_argument = original_fieldname.split(
util.PAILLIER_SUM_PREFIX)[1]
sum_argument = sum_argument.split(',')[0][:-1]
sum_argument = sum_argument.split('.')[-1]
real_fieldname = original_fieldname.split(
util.PAILLIER_SUM_PREFIX)[1]
real_fieldname = real_fieldname.split(',')[0][:-1]
if sum_argument.startswith(util.HOMOMORPHIC_INT_PREFIX):
queried_values[original_fieldname] = (_DecryptValues(
real_fieldname, rows, i, ciphers, schema,
util.HOMOMORPHIC_INT_PREFIX))
elif sum_argument.startswith(util.HOMOMORPHIC_FLOAT_PREFIX):
queried_values[original_fieldname] = (_DecryptValues(
real_fieldname, rows, i, ciphers, schema,
util.HOMOMORPHIC_FLOAT_PREFIX))
else:
queried_values[fields[i]['name']] = (
_GetUnencryptedValuesWithType(rows, i, fields[i]['type']))
else:
queried_values[fields[i]['name']] = (_GetUnencryptedValuesWithType(
rows, i, fields[i]['type']))
return queried_values
