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Diffstat (limited to '')
| -rw-r--r-- | lualib/rspamadm/clickhouse.lua | 528 |
1 files changed, 528 insertions, 0 deletions
diff --git a/lualib/rspamadm/clickhouse.lua b/lualib/rspamadm/clickhouse.lua new file mode 100644 index 0000000..b22d800 --- /dev/null +++ b/lualib/rspamadm/clickhouse.lua @@ -0,0 +1,528 @@ +--[[ +Copyright (c) 2022, Vsevolod Stakhov <vsevolod@rspamd.com> + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +]]-- + +local argparse = require "argparse" +local lua_clickhouse = require "lua_clickhouse" +local lua_util = require "lua_util" +local rspamd_http = require "rspamd_http" +local rspamd_upstream_list = require "rspamd_upstream_list" +local rspamd_logger = require "rspamd_logger" +local ucl = require "ucl" + +local E = {} + +-- Define command line options +local parser = argparse() + :name 'rspamadm clickhouse' + :description 'Retrieve information from Clickhouse' + :help_description_margin(30) + :command_target('command') + :require_command(true) + +parser:option '-c --config' + :description 'Path to config file' + :argname('config_file') + :default(rspamd_paths['CONFDIR'] .. '/rspamd.conf') +parser:option '-d --database' + :description 'Name of Clickhouse database to use' + :argname('database') + :default('default') +parser:flag '--no-ssl-verify' + :description 'Disable SSL verification' + :argname('no_ssl_verify') +parser:mutex( + parser:option '-p --password' + :description 'Password to use for Clickhouse' + :argname('password'), + parser:flag '-a --ask-password' + :description 'Ask password from the terminal' + :argname('ask_password') +) +parser:option '-s --server' + :description 'Address[:port] to connect to Clickhouse with' + :argname('server') +parser:option '-u --user' + :description 'Username to use for Clickhouse' + :argname('user') +parser:option '--use-gzip' + :description 'Use Gzip with Clickhouse' + :argname('use_gzip') + :default(true) +parser:flag '--use-https' + :description 'Use HTTPS with Clickhouse' + :argname('use_https') + +local neural_profile = parser:command 'neural_profile' + :description 'Generate symbols profile using data from Clickhouse' +neural_profile:option '-w --where' + :description 'WHERE clause for Clickhouse query' + :argname('where') +neural_profile:flag '-j --json' + :description 'Write output as JSON' + :argname('json') +neural_profile:option '--days' + :description 'Number of days to collect stats for' + :argname('days') + :default('7') +neural_profile:option '--limit -l' + :description 'Maximum rows to fetch per day' + :argname('limit') +neural_profile:option '--settings-id' + :description 'Settings ID to query' + :argname('settings_id') + :default('') + +local neural_train = parser:command 'neural_train' + :description 'Train neural using data from Clickhouse' +neural_train:option '--days' + :description 'Number of days to query data for' + :argname('days') + :default('7') +neural_train:option '--column-name-digest' + :description 'Name of neural profile digest column in Clickhouse' + :argname('column_name_digest') + :default('NeuralDigest') +neural_train:option '--column-name-vector' + :description 'Name of neural training vector column in Clickhouse' + :argname('column_name_vector') + :default('NeuralMpack') +neural_train:option '--limit -l' + :description 'Maximum rows to fetch per day' + :argname('limit') +neural_train:option '--profile -p' + :description 'Profile to use for training' + :argname('profile') + :default('default') +neural_train:option '--rule -r' + :description 'Rule to train' + :argname('rule') + :default('default') +neural_train:option '--spam -s' + :description 'WHERE clause to use for spam' + :argname('spam') + :default("Action == 'reject'") +neural_train:option '--ham -h' + :description 'WHERE clause to use for ham' + :argname('ham') + :default('Score < 0') +neural_train:option '--url -u' + :description 'URL to use for training' + :argname('url') + :default('http://127.0.0.1:11334/plugins/neural/learn') + +local http_params = { + config = rspamd_config, + ev_base = rspamadm_ev_base, + session = rspamadm_session, + resolver = rspamadm_dns_resolver, +} + +local function load_config(config_file) + local _r, err = rspamd_config:load_ucl(config_file) + + if not _r then + rspamd_logger.errx('cannot load %s: %s', config_file, err) + os.exit(1) + end + + _r, err = rspamd_config:parse_rcl({ 'logging', 'worker' }) + if not _r then + rspamd_logger.errx('cannot process %s: %s', config_file, err) + os.exit(1) + end + + if not rspamd_config:init_modules() then + rspamd_logger.errx('cannot init modules when parsing %s', config_file) + os.exit(1) + end + + rspamd_config:init_subsystem('symcache') +end + +local function days_list(days) + -- Create list of days to query starting with yesterday + local query_days = {} + local previous_date = os.time() - 86400 + local num_days = tonumber(days) + for _ = 1, num_days do + table.insert(query_days, os.date('%Y-%m-%d', previous_date)) + previous_date = previous_date - 86400 + end + return query_days +end + +local function get_excluded_symbols(known_symbols, correlations, seen_total) + -- Walk results once to collect all symbols & count occurrences + + local remove = {} + local known_symbols_list = {} + local composites = rspamd_config:get_all_opt('composites') + local all_symbols = rspamd_config:get_symbols() + local skip_flags = { + nostat = true, + skip = true, + idempotent = true, + composite = true, + } + for k, v in pairs(known_symbols) do + local lower_count, higher_count + if v.seen_spam > v.seen_ham then + lower_count = v.seen_ham + higher_count = v.seen_spam + else + lower_count = v.seen_spam + higher_count = v.seen_ham + end + + if composites[k] then + remove[k] = 'composite symbol' + elseif lower_count / higher_count >= 0.95 then + remove[k] = 'weak ham/spam correlation' + elseif v.seen / seen_total >= 0.9 then + remove[k] = 'omnipresent symbol' + elseif not all_symbols[k] then + remove[k] = 'nonexistent symbol' + else + for fl, _ in pairs(all_symbols[k].flags or {}) do + if skip_flags[fl] then + remove[k] = fl .. ' symbol' + break + end + end + end + known_symbols_list[v.id] = { + seen = v.seen, + name = k, + } + end + + -- Walk correlation matrix and check total counts + for sym_id, row in pairs(correlations) do + for inner_sym_id, count in pairs(row) do + local known = known_symbols_list[sym_id] + local inner = known_symbols_list[inner_sym_id] + if known and count == known.seen and not remove[inner.name] and not remove[known.name] then + remove[known.name] = string.format("overlapped by %s", + known_symbols_list[inner_sym_id].name) + end + end + end + + return remove +end + +local function handle_neural_profile(args) + + local known_symbols, correlations = {}, {} + local symbols_count, seen_total = 0, 0 + + local function process_row(r) + local is_spam = true + if r['Action'] == 'no action' or r['Action'] == 'greylist' then + is_spam = false + end + seen_total = seen_total + 1 + + local nsym = #r['Symbols.Names'] + + for i = 1, nsym do + local sym = r['Symbols.Names'][i] + local t = known_symbols[sym] + if not t then + local spam_count, ham_count = 0, 0 + if is_spam then + spam_count = spam_count + 1 + else + ham_count = ham_count + 1 + end + known_symbols[sym] = { + id = symbols_count, + seen = 1, + seen_ham = ham_count, + seen_spam = spam_count, + } + symbols_count = symbols_count + 1 + else + known_symbols[sym].seen = known_symbols[sym].seen + 1 + if is_spam then + known_symbols[sym].seen_spam = known_symbols[sym].seen_spam + 1 + else + known_symbols[sym].seen_ham = known_symbols[sym].seen_ham + 1 + end + end + end + + -- Fill correlations + for i = 1, nsym do + for j = 1, nsym do + if i ~= j then + local sym = r['Symbols.Names'][i] + local inner_sym_name = r['Symbols.Names'][j] + local known_sym = known_symbols[sym] + local inner_sym = known_symbols[inner_sym_name] + if known_sym and inner_sym then + if not correlations[known_sym.id] then + correlations[known_sym.id] = {} + end + local n = correlations[known_sym.id][inner_sym.id] or 0 + n = n + 1 + correlations[known_sym.id][inner_sym.id] = n + end + end + end + end + end + + local query_days = days_list(args.days) + local conditions = {} + table.insert(conditions, string.format("SettingsId = '%s'", args.settings_id)) + local limit = '' + local num_limit = tonumber(args.limit) + if num_limit then + limit = string.format(' LIMIT %d', num_limit) -- Contains leading space + end + if args.where then + table.insert(conditions, args.where) + end + + local query_fmt = 'SELECT Action, Symbols.Names FROM rspamd WHERE %s%s' + for _, query_day in ipairs(query_days) do + -- Date should be the last condition + table.insert(conditions, string.format("Date = '%s'", query_day)) + local query = string.format(query_fmt, table.concat(conditions, ' AND '), limit) + local upstream = args.upstream:get_upstream_round_robin() + local err = lua_clickhouse.select_sync(upstream, args, http_params, query, process_row) + if err ~= nil then + io.stderr:write(string.format('Error querying Clickhouse: %s\n', err)) + os.exit(1) + end + conditions[#conditions] = nil -- remove Date condition + end + + local remove = get_excluded_symbols(known_symbols, correlations, seen_total) + if not args.json then + for k in pairs(known_symbols) do + if not remove[k] then + io.stdout:write(string.format('%s\n', k)) + end + end + os.exit(0) + end + + local json_output = { + all_symbols = {}, + removed_symbols = {}, + used_symbols = {}, + } + for k in pairs(known_symbols) do + table.insert(json_output.all_symbols, k) + local why_removed = remove[k] + if why_removed then + json_output.removed_symbols[k] = why_removed + else + table.insert(json_output.used_symbols, k) + end + end + io.stdout:write(ucl.to_format(json_output, 'json')) +end + +local function post_neural_training(url, rule, spam_rows, ham_rows) + -- Prepare JSON payload + local payload = ucl.to_format( + { + ham_vec = ham_rows, + rule = rule, + spam_vec = spam_rows, + }, 'json') + + -- POST the payload + local err, response = rspamd_http.request({ + body = payload, + config = rspamd_config, + ev_base = rspamadm_ev_base, + log_obj = rspamd_config, + resolver = rspamadm_dns_resolver, + session = rspamadm_session, + url = url, + }) + + if err then + io.stderr:write(string.format('HTTP error: %s\n', err)) + os.exit(1) + end + if response.code ~= 200 then + io.stderr:write(string.format('bad HTTP code: %d\n', response.code)) + os.exit(1) + end + io.stdout:write(string.format('%s\n', response.content)) +end + +local function handle_neural_train(args) + + local this_where -- which class of messages are we collecting data for + local ham_rows, spam_rows = {}, {} + local want_spam, want_ham = true, true -- keep collecting while true + + -- Try find profile in config + local neural_opts = rspamd_config:get_all_opt('neural') + local symbols_profile = ((((neural_opts or E).rules or E)[args.rule] or E).profile or E)[args.profile] + if not symbols_profile then + io.stderr:write(string.format("Couldn't find profile %s in rule %s\n", args.profile, args.rule)) + os.exit(1) + end + -- Try find max_trains + local max_trains = (neural_opts.rules[args.rule].train or E).max_trains or 1000 + + -- Callback used to process rows from Clickhouse + local function process_row(r) + local destination -- which table to collect this information in + if this_where == args.ham then + destination = ham_rows + if #destination >= max_trains then + want_ham = false + return + end + else + destination = spam_rows + if #destination >= max_trains then + want_spam = false + return + end + end + local ucl_parser = ucl.parser() + local ok, err = ucl_parser:parse_string(r[args.column_name_vector], 'msgpack') + if not ok then + io.stderr:write(string.format("Couldn't parse [%s]: %s", r[args.column_name_vector], err)) + os.exit(1) + end + table.insert(destination, ucl_parser:get_object()) + end + + -- Generate symbols digest + table.sort(symbols_profile) + local symbols_digest = lua_util.table_digest(symbols_profile) + -- Create list of days to query data for + local query_days = days_list(args.days) + -- Set value for limit + local limit = '' + local num_limit = tonumber(args.limit) + if num_limit then + limit = string.format(' LIMIT %d', num_limit) -- Contains leading space + end + -- Prepare query elements + local conditions = { string.format("%s = '%s'", args.column_name_digest, symbols_digest) } + local query_fmt = 'SELECT %s FROM rspamd WHERE %s%s' + + -- Run queries + for _, the_where in ipairs({ args.ham, args.spam }) do + -- Inform callback which group of vectors we're collecting + this_where = the_where + table.insert(conditions, the_where) -- should be 2nd from last condition + -- Loop over days and try collect data + for _, query_day in ipairs(query_days) do + -- Break the loop if we have enough data already + if this_where == args.ham then + if not want_ham then + break + end + else + if not want_spam then + break + end + end + -- Date should be the last condition + table.insert(conditions, string.format("Date = '%s'", query_day)) + local query = string.format(query_fmt, args.column_name_vector, table.concat(conditions, ' AND '), limit) + local upstream = args.upstream:get_upstream_round_robin() + local err = lua_clickhouse.select_sync(upstream, args, http_params, query, process_row) + if err ~= nil then + io.stderr:write(string.format('Error querying Clickhouse: %s\n', err)) + os.exit(1) + end + conditions[#conditions] = nil -- remove Date condition + end + conditions[#conditions] = nil -- remove spam/ham condition + end + + -- Make sure we collected enough data for training + if #ham_rows < max_trains then + io.stderr:write(string.format('Insufficient ham rows: %d/%d\n', #ham_rows, max_trains)) + os.exit(1) + end + if #spam_rows < max_trains then + io.stderr:write(string.format('Insufficient spam rows: %d/%d\n', #spam_rows, max_trains)) + os.exit(1) + end + + return post_neural_training(args.url, args.rule, spam_rows, ham_rows) +end + +local command_handlers = { + neural_profile = handle_neural_profile, + neural_train = handle_neural_train, +} + +local function handler(args) + local cmd_opts = parser:parse(args) + + load_config(cmd_opts.config_file) + local cfg_opts = rspamd_config:get_all_opt('clickhouse') + + if cmd_opts.ask_password then + local rspamd_util = require "rspamd_util" + + io.write('Password: ') + cmd_opts.password = rspamd_util.readpassphrase() + end + + local function override_settings(params) + for _, which in ipairs(params) do + if cmd_opts[which] == nil then + cmd_opts[which] = cfg_opts[which] + end + end + end + + override_settings({ + 'database', 'no_ssl_verify', 'password', 'server', + 'use_gzip', 'use_https', 'user', + }) + + local servers = cmd_opts['server'] or cmd_opts['servers'] + if not servers then + parser:error("server(s) unspecified & couldn't be fetched from config") + end + + cmd_opts.upstream = rspamd_upstream_list.create(rspamd_config, servers, 8123) + + if not cmd_opts.upstream then + io.stderr:write(string.format("can't parse clickhouse address: %s\n", servers)) + os.exit(1) + end + + local f = command_handlers[cmd_opts.command] + if not f then + parser:error(string.format("command isn't implemented: %s", + cmd_opts.command)) + end + f(cmd_opts) +end + +return { + handler = handler, + description = parser._description, + name = 'clickhouse' +} |