import os.path import re import sqlite3 import sys from random import randint def dict_gen(curs: sqlite3.Cursor): """ Generates a dictionary of a sqlite3.Cursor object by fetching the query's results. Taken from Python Essential Reference by David Beazley. """ field_names = [d[0] for d in curs.description] while True: rows = curs.fetchmany() if not rows: return for row in rows: yield dict(zip(field_names, row)) class StatsDatabase: def __init__(self, db_path: str): """ Creates a new StatsDatabase. :param db_path: The path to the database file """ self.existing_db = os.path.exists(db_path) self.database = sqlite3.connect(db_path) self.cursor = self.database.cursor() # If DB not existing, create a new DB scheme if self.existing_db: print('Located statistics database at: ', db_path) else: print('Statistics database not found. Creating new database at: ', db_path) def get_file_info(self): """ Retrieves general file statistics from the database. This includes: - packetCount : Number of packets in the PCAP file - captureDuration : Duration of the packet capture in seconds - timestampFirstPacket : Timestamp of the first captured packet - timestampLastPacket : Timestamp of the last captured packet - avgPacketRate : Average packet rate - avgPacketSize : Average packet size - avgPacketsSentPerHost : Average number of packets sent per host - avgBandwidthIn : Average incoming bandwidth - avgBandwidthOut : Average outgoing bandwidth :return: a dictionary of keys (see above) and their respective values """ return [r for r in dict_gen( self.cursor.execute('SELECT * FROM file_statistics'))][0] def get_db_exists(self): """ :return: True if the database was already existent, otherwise False """ return self.existing_db @staticmethod def _get_selector_keywords(): """ :return: a list of selector keywords """ return ['most_used', 'least_used', 'avg', 'all'] @staticmethod def _get_parametrized_selector_keywords(): """ :return: a list of parameterizable selector keywords """ return ['ipaddress', 'macaddress'] @staticmethod def _get_extractor_keywords(): """ :return: a list of extractor keywords """ return ['random', 'first', 'last'] def get_all_named_query_keywords(self): """ :return: a list of all named query keywords, used to identify named queries """ return ( self._get_selector_keywords() + self._get_parametrized_selector_keywords() + self._get_extractor_keywords()) @staticmethod def get_all_sql_query_keywords(): """ :return: a list of all supported SQL keywords, used to identify SQL queries """ return ["select", "insert"] def _process_user_defined_query(self, query_string: str, query_parameters: tuple = None): """ Takes as input a SQL query query_string and optional a tuple of parameters which are marked by '?' in the query and later substituted. :param query_string: The query to execute :param query_parameters: The tuple of parameters to inject into the query :return: the results of the query """ if query_parameters is not None: self.cursor.execute(query_string, query_parameters) else: self.cursor.execute(query_string) self.database.commit() return self.cursor.fetchall() def get_field_types(self, *table_names): """ Creates a dictionary whose keys are the fields of the given table(s) and whose values are the appropriate field types, like TEXT for strings and REAL for float numbers. :param table_names: The name of table(s) :return: a dictionary of {field_name : field_type} for fields of all tables """ dic = {} for table in table_names: self.cursor.execute("PRAGMA table_info('%s')" % table) results = self.cursor.fetchall() for field in results: dic[field[1].lower()] = field[2] return dic def named_query_parameterized(self, keyword: str, param_op_val: list): """ Executes a parameterizable named query. :param keyword: The query to be executed, like ipaddress or macadress :param param_op_val: A list consisting of triples with (parameter, operator, value) :return: the results of the executed query """ named_queries = { "ipaddress": "SELECT DISTINCT ip_statistics.ipAddress from ip_statistics INNER JOIN ip_mac, ip_ttl, ip_ports, ip_protocols ON ip_statistics.ipAddress=ip_mac.ipAddress AND ip_statistics.ipAddress=ip_ttl.ipAddress AND ip_statistics.ipAddress=ip_ports.ipAddress AND ip_statistics.ipAddress=ip_protocols.ipAddress WHERE ", "macaddress": "SELECT DISTINCT macAddress from ip_mac WHERE "} query = named_queries.get(keyword) field_types = self.get_field_types('ip_mac', 'ip_ttl', 'ip_ports', 'ip_protocols', 'ip_statistics', 'ip_mac') conditions = [] for key, op, value in param_op_val: # this makes sure that TEXT fields are queried by strings, # e.g. ipAddress=192.168.178.1 --is-converted-to--> ipAddress='192.168.178.1' if field_types.get(key) == 'TEXT': if not str(value).startswith("'") and not str(value).startswith('"'): value = "'" + value + "'" # this replacement is required to remove ambiguity in SQL query if key == 'ipAddress': key = 'ip_mac.ipAddress' conditions.append(key + op + str(value)) where_clause = " AND ".join(conditions) query += where_clause self.cursor.execute(query) return self.cursor.fetchall() def _process_named_query(self, query_param_list): """ Executes a named query. :param query_param_list: A query list consisting of (keyword, params), e.g. [(most_used, ipAddress), (random,)] :return: the result of the query """ # Definition of SQL queries associated to named queries named_queries = { "most_used.ipaddress": "SELECT ipAddress FROM ip_statistics WHERE (pktsSent+pktsReceived) == (SELECT MAX(pktsSent+pktsReceived) from ip_statistics) LIMIT 1", "most_used.macaddress": "SELECT * FROM (SELECT macAddress, COUNT(*) as occ from ip_mac GROUP BY macAddress ORDER BY occ DESC) WHERE occ=(SELECT COUNT(*) as occ from ip_mac GROUP BY macAddress ORDER BY occ DESC LIMIT 1)", "most_used.portnumber": "SELECT portNumber, COUNT(portNumber) as cntPort FROM ip_ports GROUP BY portNumber HAVING cntPort=(SELECT MAX(cntPort) from (SELECT portNumber, COUNT(portNumber) as cntPort FROM ip_ports GROUP BY portNumber))", "most_used.protocolname": "SELECT protocolName, COUNT(protocolCount) as countProtocols FROM ip_protocols GROUP BY protocolName HAVING countProtocols=(SELECT COUNT(protocolCount) as cnt FROM ip_protocols GROUP BY protocolName ORDER BY cnt DESC LIMIT 1)", "most_used.ttlvalue": "SELECT ttlValue FROM ip_ttl WHERE ttlCount == (SELECT MAX(ttlCount) FROM ip_ttl)", "least_used.ipaddress": "SELECT ipAddress FROM ip_statistics WHERE (pktsSent+pktsReceived) == (SELECT MIN(pktsSent+pktsReceived) from ip_statistics)", "least_used.macaddress": "SELECT * FROM (SELECT macAddress, COUNT(*) as occ from ip_mac GROUP BY macAddress ORDER BY occ ASC) WHERE occ=(SELECT COUNT(*) as occ from ip_mac GROUP BY macAddress ORDER BY occ ASC LIMIT 1)", "least_used.portnumber": "SELECT portNumber, COUNT(portNumber) as cntPort FROM ip_ports GROUP BY portNumber HAVING cntPort=(SELECT MIN(cntPort) from (SELECT portNumber, COUNT(portNumber) as cntPort FROM ip_ports GROUP BY portNumber))", "least_used.protocolname": "SELECT protocolName, COUNT(protocolCount) as countProtocols FROM ip_protocols GROUP BY protocolName HAVING countProtocols=(SELECT COUNT(protocolCount) as cnt FROM ip_protocols GROUP BY protocolName ORDER BY cnt ASC LIMIT 1)", "least_used.ttlvalue": "SELECT ttlValue FROM ip_ttl WHERE ttlCount == (SELECT MIN(ttlCount) FROM ip_ttl)", "avg.pktsreceived": "SELECT avg(pktsReceived) from ip_statistics", "avg.pktssent": "SELECT avg(pktsSent) from ip_statistics", "avg.kbytesreceived": "SELECT avg(kbytesReceived) from ip_statistics", "avg.kbytessent": "SELECT avg(kbytesSent) from ip_statistics", "avg.ttlvalue": "SELECT avg(ttlValue) from ip_ttl", "avg.mss": "SELECT avg(mss) from tcp_mss", "all.ipaddress": "SELECT ipAddress from ip_statistics", "all.ttlvalue": "SELECT DISTINCT ttlValue from ip_ttl", "all.mss": "SELECT DISTINCT mss from tcp_mss", "all.macaddress": "SELECT DISTINCT macAddress from ip_mac", "all.portnumber": "SELECT DISTINCT portNumber from ip_ports", "all.protocolname": "SELECT DISTINCT protocolName from ip_protocols"} # Retrieve values by selectors, if given, reduce results by extractor last_result = 0 for q in query_param_list: # if selector, like avg, ttl, is given if any(e in q[0] for e in self._get_selector_keywords()): (keyword, param) = q query = named_queries.get(keyword + "." + param) self.cursor.execute(str(query)) last_result = self.cursor.fetchall() # if selector is parametrized, i.e. ipAddress(mac=AA:BB:CC:DD:EE) or macAddress(ipAddress=192.168.178.1) elif any(e in q[0] for e in self._get_parametrized_selector_keywords()) and any( o in q[1] for o in ["<", "=", ">", "<=", ">="]): (keyword, param) = q # convert string 'paramName1paramValue1,paramName2paramValue2,...' into list of triples param_op_val = [(key, op, value) for (key, op, value) in [re.split("(<=|>=|>|<|=)", x) for x in param.split(",")]] last_result = self.named_query_parameterized(keyword, param_op_val) # if extractor, like random, first, last, is given elif any(e in q[0] for e in self._get_extractor_keywords()) and ( isinstance(last_result, list) or isinstance(last_result, tuple)): extractor = q[0] if extractor == 'random': index = randint(a=0, b=len(last_result) - 1) last_result = last_result[index] elif extractor == 'first': last_result = last_result[0] elif extractor == 'last': last_result = last_result[-1] return last_result def process_db_query(self, query_string_in: str, print_results=False, sql_query_parameters: tuple = None): """ Processes a database query. This can either be a standard SQL query or a named query (predefined query). :param query_string_in: The string containing the query :param print_results: Indicated whether the results should be printed to terminal (True) or not (False) :param sql_query_parameters: Parameters for the SQL query (optional) :return: the results of the query """ named_query_keywords = self.get_all_named_query_keywords() # Clean query_string query_string = query_string_in.lower().lstrip() # query_string is a user-defined SQL query result = None if sql_query_parameters is not None or query_string.startswith("select") or query_string.startswith("insert"): result = self._process_user_defined_query(query_string, sql_query_parameters) # query string is a named query -> parse it and pass it to statisticsDB elif any(k in query_string for k in named_query_keywords) and all(k in query_string for k in ['(', ')']): # Clean query_string query_string = query_string.replace(" ", "") # Validity check: Brackets brackets_open, brackets_closed = query_string.count("("), query_string.count(")") if not (brackets_open == brackets_closed): sys.stderr.write("Bracketing of given query '" + query_string + "' is incorrect.") # Parse query string into [ (query_keyword1, query_params1), ... ] delimiter_start, delimiter_end = "(", ")" kplist = [] current_word = "" for char in query_string: # process characters one-by-one # if char is no delimiter, add char to current_word if char != delimiter_end and char != delimiter_start: current_word += char # if a start delimiter was found and the current_word so far is a keyword, add it to kplist elif char == delimiter_start: if current_word in named_query_keywords: kplist.append((current_word,)) current_word = "" else: print("ERROR: Unrecognized keyword '" + current_word + "' found. Ignoring query.") return # else if characeter is end delimiter and there were no two directly following ending delimiters, # the current_word must be the parameters of an earlier given keyword elif char == delimiter_end and len(current_word) > 0: kplist[-1] += (current_word,) current_word = "" result = self._process_named_query(kplist[::-1]) else: sys.stderr.write( "Query invalid. Only named queries and SQL SELECT/INSERT allowed. Please check the query's syntax!\n") return # If result is tuple/list with single element, extract value from list requires_extraction = (isinstance(result, list) or isinstance(result, tuple)) and len(result) == 1 and \ (not isinstance(result[0], tuple) or len(result[0]) == 1) while requires_extraction: if isinstance(result, list) or isinstance(result, tuple): result = result[0] else: requires_extraction = False # If tuple of tuples or list of tuples, each consisting of single element is returned, # then convert it into list of values, because the returned colum is clearly specified by the given query if (isinstance(result, tuple) or isinstance(result, list)) and all(len(val) == 1 for val in result): result = [c for c in result for c in c] # Print results if option print_results is True if print_results: if len(result) == 1 and isinstance(result, list): result = result[0] print("Query returned 1 record:\n") for i in range(0, len(result)): print(str(self.cursor.description[i][0]) + ": " + str(result[i])) else: self._print_query_results(query_string_in, result) return result def _print_query_results(self, query_string_in: str, result): """ Prints the results of a query. Based on http://stackoverflow.com/a/20383011/3017719. :param query_string_in: The query the results belong to :param result: The results of the query """ # Print number of results according to type of result if isinstance(result, list): print("Query returned " + str(len(result)) + " records:\n") else: print("Query returned 1 record:\n") # Print query results if query_string_in.lstrip().upper().startswith( "SELECT") and result is not None and self.cursor.description is not None: widths = [] columns = [] tavnit = '|' separator = '+' for cd in self.cursor.description: widths.append(len(cd) + 10) columns.append(cd[0]) for w in widths: tavnit += " %-" + "%ss |" % (w,) separator += '-' * w + '--+' print(separator) print(tavnit % tuple(columns)) print(separator) if isinstance(result, list): for row in result: print(tavnit % row) else: print(tavnit % result) print(separator) else: print(result)