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Editing: clustering.lua
--[[ Copyright (c) 2018, Vsevolod Stakhov 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. ]]-- -- Plugin for finding patterns in email flows local N = 'clustering' local rspamd_logger = require "rspamd_logger" local lua_util = require "lua_util" local lua_verdict = require "lua_verdict" local lua_redis = require "lua_redis" local lua_selectors = require "lua_selectors" local T = require "lua_shape.core" local PluginSchema = require "lua_shape.plugin_schema" local redis_params local rules = {} -- Rules placement local default_rule = { max_elts = 100, -- Maximum elements in a cluster expire = 3600, -- Expire for a bucket when limit is not reached expire_overflow = 36000, -- Expire for a bucket when limit is reached spam_mult = 1.0, -- Increase on spam hit junk_mult = 0.5, -- Increase on junk ham_mult = -0.1, -- Increase on ham size_mult = 0.01, -- Reaches 1.0 on `max_elts` score_mult = 0.1, } local rule_schema = T.table({ max_elts = T.one_of({ T.number(), T.transform(T.string(), tonumber) }):doc({ summary = "Maximum elements in a cluster" }), expire = T.one_of({ T.number(), T.transform(T.string(), lua_util.parse_time_interval) }):doc({ summary = "Expire time for bucket (seconds)" }), expire_overflow = T.one_of({ T.number(), T.transform(T.string(), lua_util.parse_time_interval) }):doc({ summary = "Expire time when limit is reached (seconds)" }), spam_mult = T.number():doc({ summary = "Score multiplier for spam" }), junk_mult = T.number():doc({ summary = "Score multiplier for junk" }), ham_mult = T.number():doc({ summary = "Score multiplier for ham" }), size_mult = T.number():doc({ summary = "Size-based score multiplier" }), score_mult = T.number():doc({ summary = "Cluster score multiplier" }), source_selector = T.string():doc({ summary = "Selector for cluster source" }), cluster_selector = T.string():doc({ summary = "Selector for cluster grouping" }), symbol = T.string():optional():doc({ summary = "Symbol name" }), prefix = T.string():optional():doc({ summary = "Redis key prefix" }), }):doc({ summary = "Clustering rule configuration" }) local config_schema = lua_redis.enrich_schema({ enabled = T.boolean():optional():doc({ summary = "Enable the plugin" }), rules = T.table({}, { open = true, extra = rule_schema }):doc({ summary = "Clustering rules keyed by name" }) }):doc({ summary = "Clustering plugin configuration" }) PluginSchema.register("plugins.clustering", config_schema) if confighelp then return end -- Redis scripts -- Queries for a cluster's data -- Arguments: -- 1. Source selector (string) -- 2. Cluster selector (string) -- Returns: {cur_elts, total_score, element_score} local query_cluster_script = [[ local sz = redis.call('HLEN', KEYS[1]) if not sz or not tonumber(sz) then -- New bucket, will update on idempotent phase return {0, '0', '0'} end local total_score = redis.call('HGET', KEYS[1], '__s') total_score = tonumber(total_score) or 0 local score = redis.call('HGET', KEYS[1], KEYS[2]) if not score or not tonumber(score) then return {sz, tostring(total_score), '0'} end return {sz, tostring(total_score), tostring(score)} ]] local query_cluster_id -- Updates cluster's data -- Arguments: -- 1. Source selector (string) -- 2. Cluster selector (string) -- 3. Score (number) -- 4. Max buckets (number) -- 5. Expire (number) -- 6. Expire overflow (number) -- Returns: nothing local update_cluster_script = [[ local sz = redis.call('HLEN', KEYS[1]) if not sz or not tonumber(sz) then -- Create bucket redis.call('HSET', KEYS[1], KEYS[2], math.abs(KEYS[3])) redis.call('HSET', KEYS[1], '__s', KEYS[3]) redis.call('EXPIRE', KEYS[1], KEYS[5]) return end sz = tonumber(sz) local lim = tonumber(KEYS[4]) if sz > lim then if k then -- Existing key redis.call('HINCRBYFLOAT', KEYS[1], KEYS[2], math.abs(KEYS[3])) end else redis.call('HINCRBYFLOAT', KEYS[1], KEYS[2], math.abs(KEYS[3])) redis.call('EXPIRE', KEYS[1], KEYS[6]) end redis.call('HINCRBYFLOAT', KEYS[1], '__s', KEYS[3]) redis.call('EXPIRE', KEYS[1], KEYS[5]) ]] local update_cluster_id -- Callbacks and logic local function clusterting_filter_cb(task, rule) local source_selector = rule.source_selector(task) local cluster_selector if source_selector then cluster_selector = rule.cluster_selector(task) end if not cluster_selector or not source_selector then lua_util.debugm(N, task, 'skip rule %s, selectors: source="%s", cluster="%s"', rule.name, source_selector, cluster_selector) return end local function combine_scores(cur_elts, total_score, element_score) local final_score local size_score = cur_elts * rule.size_mult local cluster_score = total_score * rule.score_mult if element_score > 0 then -- We have seen this element mostly in junk/spam final_score = math.min(1.0, size_score + cluster_score) else -- We have seen this element in ham mostly, so subtract average it from the size score final_score = math.min(1.0, size_score - cluster_score / cur_elts) end lua_util.debugm(N, task, 'processed rule %s, selectors: source="%s", cluster="%s"; data: %s elts, %s score, %s elt score', rule.name, source_selector, cluster_selector, cur_elts, total_score, element_score) if final_score > 0.1 then task:insert_result(rule.symbol, final_score, { source_selector, tostring(size_score), tostring(cluster_score) }) end end local function redis_get_cb(err, data) if data then if type(data) == 'table' then combine_scores(tonumber(data[1]), tonumber(data[2]), tonumber(data[3])) else rspamd_logger.errx(task, 'invalid type while getting clustering keys %s: %s', source_selector, type(data)) end elseif err then rspamd_logger.errx(task, 'got error while getting clustering keys %s: %s', source_selector, err) else rspamd_logger.errx(task, 'got error while getting clustering keys %s: %s', source_selector, "unknown error") end end lua_redis.exec_redis_script(query_cluster_id, { task = task, is_write = false, key = source_selector }, redis_get_cb, { source_selector, cluster_selector }) end local function clusterting_idempotent_cb(task, rule) if task:has_flag('skip') then return end if not rule.allow_local and lua_util.is_rspamc_or_controller(task) then return end local verdict = lua_verdict.get_specific_verdict(N, task) local score if verdict == 'ham' then score = rule.ham_mult elseif verdict == 'spam' then score = rule.spam_mult elseif verdict == 'junk' then score = rule.junk_mult else lua_util.debugm(N, task, 'skip rule %s, verdict=%s', rule.name, verdict) return end local source_selector = rule.source_selector(task) local cluster_selector if source_selector then cluster_selector = rule.cluster_selector(task) end if not cluster_selector or not source_selector then lua_util.debugm(N, task, 'skip rule %s, selectors: source="%s", cluster="%s"', rule.name, source_selector, cluster_selector) return end local function redis_set_cb(err, data) if err then rspamd_logger.errx(task, 'got error while getting clustering keys %s: %s', source_selector, err) else lua_util.debugm(N, task, 'set clustering key for %s: %s{%s} = %s', source_selector, "unknown error") end end lua_redis.exec_redis_script(update_cluster_id, { task = task, is_write = true, key = source_selector }, redis_set_cb, { source_selector, cluster_selector, tostring(score), tostring(rule.max_elts), tostring(rule.expire), tostring(rule.expire_overflow) } ) end -- Init part local opts = rspamd_config:get_all_opt("clustering") -- Initialization part if not (opts and type(opts) == 'table') then lua_util.disable_module(N, "config") return end local cfg, cfg_err = config_schema:transform(opts) if not cfg then rspamd_logger.errx(rspamd_config, 'invalid clustering config: %s', cfg_err) lua_util.disable_module(N, "config") return end opts = cfg redis_params = lua_redis.parse_redis_server('clustering', opts) if not redis_params then lua_util.disable_module(N, "redis") return end if opts['rules'] then for k, v in pairs(opts['rules']) do local raw_rule = lua_util.override_defaults(default_rule, v) local rule, err = rule_schema:transform(raw_rule) if not rule then rspamd_logger.errx(rspamd_config, 'invalid clustering rule %s: %s', k, err) else if not rule.symbol then rule.symbol = k end if not rule.prefix then rule.prefix = k .. "_" end rule.source_selector = lua_selectors.create_selector_closure(rspamd_config, rule.source_selector, '') rule.cluster_selector = lua_selectors.create_selector_closure(rspamd_config, rule.cluster_selector, '') if rule.source_selector and rule.cluster_selector then rule.name = k table.insert(rules, rule) end end end if #rules > 0 then query_cluster_id = lua_redis.add_redis_script(query_cluster_script, redis_params) update_cluster_id = lua_redis.add_redis_script(update_cluster_script, redis_params) local function callback_gen(f, rule) return function(task) return f(task, rule) end end for _, rule in ipairs(rules) do rspamd_config:register_symbol { name = rule.symbol, type = 'normal', callback = callback_gen(clusterting_filter_cb, rule), } rspamd_config:register_symbol { name = rule.symbol .. '_STORE', type = 'idempotent', flags = 'empty,explicit_disable,ignore_passthrough', callback = callback_gen(clusterting_idempotent_cb, rule), augmentations = { string.format("timeout=%f", redis_params.timeout or 0.0) } } end else lua_util.disable_module(N, "config") end else lua_util.disable_module(N, "config") end
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