研发背景
公司安全部目前针对内部系统的网络访问日志的安全审计,大部分都是T+1时效,每日当天,启动Python编写的定时任务,完成昨日的日志审计和检测,定时任务运行完成后,统一进行企业微信告警推送。这种方案在目前的网络环境和人员规模下,呈现两个痛点,一是面对日益频繁的网络攻击、钓鱼链接,T+1的定时任务,难以及时进行告警,因此也难以有效避免如关键信息泄露等问题,二是目前以Python为主的单机定时任务,针对不同场景的处理时效,从一小时到十几小时不等,效率低下。为解决以上问题,本人协助公司安全部同时对告警采集平台进行改造,由之前的python单机任务处理,切换到基于Flink集群的并行处理,且告警推送时效,由之前的T+1天,提升到秒级实时告警。本次改造涉及网络日志审计的多个常见场景,如端口扫描、黑名单统计、异常流量、连续恶意登录等。本次以一段时间内连续登录失败20次后,下一次登录成功场景来进行介绍。
场景描述
针对一个内部系统,如邮件系统,公司员工的访问行为日志,存放于kafka,我们希望对于一个用户账号在同一个IP下,任意的3分钟时间内,连续登录邮件系统20次失败,下一次登录成功,这种场景能够及时获取并推送到企业微信某个指定的安全接口人。kafka中的数据,能够通过某个关键字,区分当前网络访问是否一次登录事件,且有访问时间(也就是事件时间)。在解析到符合需求的用户账号之后,第一时间进行企业微信告警推送,并将其这段时间内的访问行为,写入下游ElasticSearch。
组件版本
- Flink-1.14.4
- Java8
- ElasticSearch-7.3.2
- Kafka-2.12_2.8.1
日志结构
IP和账号皆为测试使用。
{ "user": "wangxm", "client_ip": "110.68.6.182", "source": "login", "loginname": "[email protected]", "IP": "110.8.148.58", "timestamp": "17:58:12", "@timestamp": "2022-04-20T09:58:13.647Z", "ip": "110.7.231.25", "clienttype": "POP3", "result": "success", "@version": "1" }
技术方案
上述场景,可考虑使用FlinkCEP及Flink的滑动窗口进行实现。由于本人在采用FlinkCEP的方案进行代码编写调试后,发现并不能满足,因此改用滑动窗口进行实现。
关键代码
主入口类
主入口类,创建了flink环境、设置了基础参数,创建了kafkaSource,接入消息后,进行了映射、过滤,并设置了水位线,进行了分组,之后设置了滑动窗口,在窗口内进行了事件统计,将复合条件的事件收集返回并写入ElasticSearch。
针对map、filter、keyBy、window等算子,都单独进行了编写,后面会一一列出来。
package com.data.dev.flink.mailTopic.main; import com.data.dev.common.javabean.BaseBean; import com.data.dev.common.javabean.kafkaMailTopic.MailMsgAlarm; import com.data.dev.elasticsearch.ElasticSearchInfo; import com.data.dev.elasticsearch.SinkToEs; import com.data.dev.flink.FlinkEnv; import com.data.dev.flink.mailTopic.OperationForLoginFailCheck.*; import com.data.dev.kafka.KafkaSourceBuilder; import com.data.dev.key.ConfigurationKey; import com.data.dev.utils.TimeUtils; import lombok.extern.slf4j.Slf4j; import org.apache.flink.api.common.eventtime.WatermarkStrategy; import org.apache.flink.connector.kafka.source.KafkaSource; import org.apache.flink.streaming.api.datastream.DataStreamSource; import org.apache.flink.streaming.api.datastream.KeyedStream; import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator; import org.apache.flink.streaming.api.datastream.WindowedStream; import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment; import org.apache.flink.streaming.api.windowing.assigners.SlidingEventTimeWindows; import org.apache.flink.streaming.api.windowing.time.Time; import org.apache.flink.streaming.api.windowing.windows.TimeWindow; import java.time.Duration; /** * Flink处理在3分钟内连续登录失败20次后登录成功的场景 * 采用滑动窗口来实现 * @author wangxiaomin 2022-06-01 */ @Slf4j public class MailMsg extends BaseBean { /** * Flink作业名称 */ public static final String JobName = "告警采集平台——连续登录失败后登录成功告警"; /** * Kafka消息名 */ public static final String KafkaSourceName = "Kafka Source for AlarmPlatform About Mail Topic"; public MailMsg(){ log.info("初始化滑动窗口场景告警程序"); } /** * 执行逻辑统计场景,实现告警推送 */ public static void execute(){ //① 创建Flink执行环境并设置checkpoint等必要的参数 StreamExecutionEnvironment env = FlinkEnv.getFlinkEnv(); KafkaSourcekafkaSource = KafkaSourceBuilder.getKafkaSource(ConfigurationKey.KAFKA_MAIL_TOPIC_NAME,ConfigurationKey.KAFKA_MAIL_CONSUMER_GROUP_ID) ; DataStreamSource kafkaMailMsg = env.fromSource(kafkaSource, WatermarkStrategy.forBoundedOutOfOrderness(Duration.ofMillis(10)), KafkaSourceName); //② 筛选登录消息,创建初始登录事件流 SingleOutputStreamOperator loginMapDs = kafkaMailMsg.map(new MsgToBeanMapper()).name("Map算子加工"); SingleOutputStreamOperator loginFilterDs = loginMapDs.filter(new MailMsgForLoginFilter()).name("Filter算子加工"); //③ 设置水位线 WatermarkStrategy watermarkStrategy = WatermarkStrategy. forBoundedOutOfOrderness(Duration.ofMinutes(1)) .withTimestampAssigner((mailMsg, timestamp) -> TimeUtils.switchUTCToBeijingTimestamp(mailMsg.getTimestamp_datetime())); SingleOutputStreamOperator loginWmDs = loginFilterDs.assignTimestampsAndWatermarks(watermarkStrategy.withIdleness(Duration.ofMinutes(3))).name("增加水位线"); //④ 设置主键 KeyedStream loginKeyedDs = loginWmDs.keyBy(new LoginKeySelector()); //⑥ 转化为滑动窗口 WindowedStream loginWindowDs = loginKeyedDs.window(SlidingEventTimeWindows.of(Time.seconds(180L),Time.seconds(90L))); //⑦ 在窗口内进行逻辑统计 SingleOutputStreamOperator loginWindowsDealDs = loginWindowDs.process(new WindowProcessFuncImpl()).name("窗口处理逻辑"); //⑧ 将结果转化为通用DataStream 格式 SingleOutputStreamOperator resultDs = loginWindowsDealDs.map(new AlarmMsgToStringMapper()).name("窗口结果转化为标准格式"); //⑨ 将最终结果写入ES resultDs.addSink(SinkToEs.getEsSinkBuilder(ElasticSearchInfo.ES_LOGIN_FAIL_INDEX_NAME,ElasticSearchInfo.ES_INDEX_TYPE_DEFAULT).build()); //⑩ 提交Flink集群进行执行 FlinkEnv.envExec(env,JobName); } }
mapper算子
package com.data.dev.flink.mailTopic.OperationForLoginFailCheck; import com.alibaba.fastjson.JSON; import com.data.dev.common.javabean.BaseBean; import com.data.dev.common.javabean.kafkaMailTopic.MailMsgAlarm; import lombok.extern.slf4j.Slf4j; import org.apache.flink.api.common.functions.MapFunction; /** * 逻辑统计场景告警推送ES消息体 * @author wangxiaoming-ghq 2022-06-01 */ @Slf4j public class AlarmMsgToStringMapper extends BaseBean implements MapFunction{ @Override public String map(MailMsgAlarm mailMsgAlarm) throws Exception { return JSON.toJSONString(mailMsgAlarm); } }
filter算子
package com.data.dev.flink.mailTopic.OperationForLoginFailCheck; import com.data.dev.common.javabean.BaseBean; import com.data.dev.common.javabean.kafkaMailTopic.MailMsg; import lombok.extern.slf4j.Slf4j; import org.apache.flink.api.common.functions.FilterFunction; /** * ② 消费mail主题的消息,过滤其中login的事件 * @author wangxiaoming-ghq 2022-06-01 */ @Slf4j public class MailMsgForLoginFilter extends BaseBean implements FilterFunction{ @Override public boolean filter(MailMsg mailMsg) { if("login".equals(mailMsg.getSource())) { log.info("筛选原始的login事件:【" + mailMsg + "】"); } return "login".equals(mailMsg.getSource()); } }
keyBy算子
package com.data.dev.flink.mailTopic.OperationForLoginFailCheck; import com.data.dev.common.javabean.BaseBean; import com.data.dev.common.javabean.kafkaMailTopic.MailMsg; import lombok.extern.slf4j.Slf4j; import org.apache.flink.api.java.functions.KeySelector; /** * CEP 编程,需要进行key选取 */ @Slf4j public class LoginKeySelector extends BaseBean implements KeySelector{ @Override public String getKey(MailMsg mailMsg) { return mailMsg.getUser() + "@" + mailMsg.getClient_ip(); } }
窗口函数(核心代码)
这里我们主要考虑使用一个事件列表,用来存储每一个窗口期内得到的连续登录,当检测到登陆失败的事件,即存入事件列表中,之后判断下一次登录失败事件,如果检测到登录成功事件,但此时登录失败的次数不足20次,则清空loginEventList,等待下一次检测。一旦符合窗口内连续登录失败超过20次且下一次登录成功这个事件,则清空此时的loginEventList并将当前登录成功的事件进行告警推送。
package com.data.dev.flink.mailTopic.OperationForLoginFailCheck; import com.data.dev.common.javabean.kafkaMailTopic.MailMsg; import com.data.dev.common.javabean.kafkaMailTopic.MailMsgAlarm; import com.data.dev.utils.HttpUtils; import com.data.dev.utils.IPUtils; import lombok.extern.slf4j.Slf4j; import org.apache.flink.streaming.api.functions.windowing.ProcessWindowFunction; import org.apache.flink.streaming.api.windowing.windows.TimeWindow; import org.apache.flink.util.Collector; import java.io.Serializable; import java.util.ArrayList; import java.util.List; /** * 滑动窗口内复杂事件解析逻辑实现 * @author wangxiaoming-ghq 2022-06-01 */ @Slf4j public class WindowProcessFuncImpl extends ProcessWindowFunctionimplements Serializable { @Override public void process(String key, ProcessWindowFunction .Context context, Iterable iterable, Collector collector) { List loginEventList = new ArrayList<>(); MailMsgAlarm mailMsgAlarm; for (MailMsg mailMsg : iterable) { log.info("收集到的登录事件【" + mailMsg + "】"); if (mailMsg.getResult().equals("fail")) { //开始检测当前窗口内的事件,并将失败的事件收集到loginEventList log.info("开始检测当前窗口内的事件,并将失败的事件收集到loginEventList"); loginEventList.add(mailMsg); } else if (mailMsg.getResult().equals("success") && loginEventList.size() < 20) {//如果检测到登录成功事件,但此时登录失败的次数不足20次,则清空loginEventList,等待下一次检测 log.info("检测到登录成功事件,但此时登录失败的次数为【" + loginEventList.size() + "】不足20次,清空loginEventList,等待下一次检测"); loginEventList.clear(); } else if (mailMsg.getResult().equals("success") && loginEventList.size() >= 20) { mailMsgAlarm = getMailMsgAlarm(loginEventList,mailMsg); log.info("检测到登录成功的事件,此时窗口内连续登录失败的次数为【" + mailMsgAlarm.getFailTimes() + "】"); //一旦符合窗口内连续登录失败超过20次且下一次登录成功这个事件,则清空此时的loginEventList并将当前登录成功的事件进行告警推送; loginEventList.clear(); doAlarmPush(mailMsgAlarm); collector.collect(mailMsgAlarm);//将当前登录成功的事件进行收集上报 } else { log.info(mailMsg.getUser() + "当前已连续:【" + loginEventList.size() + "】 次登录失败"); } } } /** * 2022年6月17日15:03:06 * @param eventList:当前窗口内的事件列表 * @param eventCurrent:当前登录成功的事件 * @return mailMsgAlarm:告警消息体 */ public static MailMsgAlarm getMailMsgAlarm(List eventList,MailMsg eventCurrent){ String alarmKey = eventCurrent.getUser() + "@" + eventCurrent.getClient_ip(); String loginFailStartTime = eventList.get(0).getTimestamp_datetime(); String loginSuccessTime = eventCurrent.getTimestamp_datetime(); int loginFailTimes = eventList.size(); MailMsgAlarm mailMsgAlarm = new MailMsgAlarm(); mailMsgAlarm.setMailMsg(eventCurrent); mailMsgAlarm.setAlarmKey(alarmKey); mailMsgAlarm.setStartTime(loginFailStartTime); mailMsgAlarm.setEndTime(loginSuccessTime); mailMsgAlarm.setFailTimes(loginFailTimes); return mailMsgAlarm; } /** * 2022年6月17日14:47:53 * @param mailMsgAlarm :当前构建的需要告警的事件 */ public void doAlarmPush(MailMsgAlarm mailMsgAlarm){ String userKey = mailMsgAlarm.getAlarmKey(); String clientIp = mailMsgAlarm.mailMsg.getClient_ip(); boolean isWhiteListIp = IPUtils.isWhiteListIp(clientIp); if(isWhiteListIp){//如果是白名单IP,不告警 log.info("当前登录用户【" + userKey + "】属于白名单IP"); }else { //IP归属查询结果、企业微信推送告警 String user = HttpUtils.getUserByClientIp(clientIp); HttpUtils.pushAlarmMsgToWechatWork(user,mailMsgAlarm.toString()); } } }
最后一次map算子
package com.data.dev.flink.mailTopic.OperationForLoginFailCheck; import com.alibaba.fastjson.JSON; import com.data.dev.common.javabean.BaseBean; import com.data.dev.common.javabean.kafkaMailTopic.MailMsgAlarm; import lombok.extern.slf4j.Slf4j; import org.apache.flink.api.common.functions.MapFunction; /** * 逻辑统计场景告警推送ES消息体 * @author wangxiaoming-ghq 2022-06-01 */ @Slf4j public class AlarmMsgToStringMapper extends BaseBean implements MapFunction{ @Override public String map(MailMsgAlarm mailMsgAlarm) throws Exception { return JSON.toJSONString(mailMsgAlarm); } }
ElasticSearch工具类
package com.data.dev.elasticsearch; import com.data.dev.common.javabean.BaseBean; import com.data.dev.key.ConfigurationKey; import com.data.dev.key.ElasticSearchKey; import lombok.extern.slf4j.Slf4j; import org.apache.flink.api.common.functions.RuntimeContext; import org.apache.flink.streaming.connectors.elasticsearch.ElasticsearchSinkFunction; import org.apache.flink.streaming.connectors.elasticsearch.RequestIndexer; import org.apache.flink.streaming.connectors.elasticsearch7.ElasticsearchSink; import org.apache.flink.streaming.connectors.elasticsearch7.RestClientFactory; import org.apache.http.HttpHost; import org.apache.http.auth.AuthScope; import org.apache.http.auth.UsernamePasswordCredentials; import org.apache.http.client.CredentialsProvider; import org.apache.http.impl.client.BasicCredentialsProvider; import org.elasticsearch.action.index.IndexRequest; import org.elasticsearch.client.Requests; import java.util.ArrayList; import java.util.HashMap; import java.util.List; import java.util.Map; /** * 2022年6月17日15:15:06 * @author wangxiaoming-ghq * Flink流计算结果写入ES公共方法 */ @Slf4j public class SinkToEs extends BaseBean { public static final long serialVersionUID = 2L; private static final HashMapES_PROPS_MAP = ConfigurationKey.getApplicationProps(); private static final String HOST = ES_PROPS_MAP.get(ConfigurationKey.ES_HOST); private static final String PASSWORD = ES_PROPS_MAP.get(ConfigurationKey.ES_PASSWORD); private static final String USERNAME = ES_PROPS_MAP.get(ConfigurationKey.ES_USERNAME); private static final String PORT = ES_PROPS_MAP.get(ConfigurationKey.ES_PORT); /** * 2022年6月17日15:17:55 * 获取ES连接信息 * @return esInfoMap:ES连接信息持久化 */ public static HashMap getElasticSearchInfo(){ log.info("获取ES连接信息:【 " + "HOST="+HOST + "PORT="+PORT+"USERNAME="+USERNAME+"PASSWORD=********" + " 】"); HashMap esInfoMap = new HashMap<>(); esInfoMap.put(ElasticSearchKey.HOST,HOST); esInfoMap.put(ElasticSearchKey.PASSWORD,PASSWORD); esInfoMap.put(ElasticSearchKey.USERNAME,USERNAME); esInfoMap.put(ElasticSearchKey.PORT,PORT); return esInfoMap; } /** * @param esIndexName:写入索引名称 * @param esType:写入索引类型 * @return ElasticsearchSink.Builder :构建器 */ public static ElasticsearchSink.Builder getEsSinkBuilder(String esIndexName,String esType){ HashMap esInfoMap = getElasticSearchInfo(); List httpHosts = new ArrayList<>(); httpHosts.add(new HttpHost(String.valueOf(esInfoMap.get(ElasticSearchKey.HOST)), Integer.parseInt(esInfoMap.get(ElasticSearchKey.PORT)), "http")); ElasticsearchSink.Builder esSinkBuilder = new ElasticsearchSink.Builder<>( httpHosts, new ElasticsearchSinkFunction () { public IndexRequest createIndexRequest() { Map json = new HashMap<>(); //log.info("写入ES的data:【"+json+"】"); IndexRequest index = Requests.indexRequest() .index(esIndexName) .type(esType) .source(json); return index; } @Override public void process(String element, RuntimeContext ctx, RequestIndexer indexer) { indexer.add(createIndexRequest()); } } ); //定义es的连接配置 带用户名密码 RestClientFactory restClientFactory = restClientBuilder -> { CredentialsProvider credentialsProvider = new BasicCredentialsProvider(); credentialsProvider.setCredentials( AuthScope.ANY, new UsernamePasswordCredentials( String.valueOf(esInfoMap.get(ElasticSearchKey.USERNAME)), String.valueOf(esInfoMap.get(ElasticSearchKey.PASSWORD)) ) ); restClientBuilder.setHttpClientConfigCallback(httpAsyncClientBuilder -> { httpAsyncClientBuilder.disableAuthCaching(); return httpAsyncClientBuilder.setDefaultCredentialsProvider(credentialsProvider); }); }; esSinkBuilder.setRestClientFactory(restClientFactory); return esSinkBuilder; } }
事件实体类
package com.data.dev.common.javabean.kafkaMailTopic; import com.data.dev.common.javabean.BaseBean; import lombok.Data; import java.util.Objects; /** * @author wangxiaoming-ghq 2022-05-15 * 逻辑统计场景告警事件 */ @Data public class MailMsgAlarm extends BaseBean { /** * 当前登录成功的事件 */ public MailMsg mailMsg; /** * 当前捕获的告警主键:username@client_ip */ public String alarmKey; /** * 第一次登录失败的事件时间 */ public String startTime; /** * 连续登录失败后下一次登录成功的事件时间 */ public String endTime; /** * 连续登录失败的次数 */ public int failTimes; @Override public String toString() { return "{" + " 'mailMsg_login_success':'" + mailMsg + "'" + ", 'alarmKey':'" + alarmKey + "'" + ", 'start_login_time_in3min':'" +startTime + "'" + ", 'end_login_time_in3min':'" +endTime + "'" + ", 'login_fail_times':'" +failTimes + "'" + "}"; } public MailMsgAlarm() { } @Override public boolean equals(Object o) { if (this == o) return true; if (!(o instanceof MailMsgAlarm)) return false; MailMsgAlarm that = (MailMsgAlarm) o; return getFailTimes() == that.getFailTimes() && getMailMsg().equals(that.getMailMsg()) && getAlarmKey().equals(that.getAlarmKey()) && getStartTime().equals(that.getStartTime()) && getEndTime().equals(that.getEndTime()); } @Override public int hashCode() { return Objects.hash(getMailMsg(), getAlarmKey(), getStartTime(), getEndTime(), getFailTimes()); } }
消息实体类
package com.data.dev.common.javabean.kafkaMailTopic; import com.data.dev.common.javabean.BaseBean; import lombok.Data; import java.util.Objects; /** * { * "user": "wangxm", * "client_ip": "110.68.6.182", * "source": "login", * "loginname": "[email protected]", * "IP": "110.8.148.58", * "timestamp": "17:58:12", * "@timestamp": "2022-04-20T09:58:13.647Z", * "ip": "110.7.231.25", * "clienttype": "POP3", * "result": "success", * "@version": "1" * } * * user登录用户 * client_ip 来源ip * source 类型 * loginname 登录用户邮箱地址 * ip 目标前端ip * timestamp 发送时间 * @timestamp 发送日期时间 * IP 邮件日志发送来源IP * clienttype 客户端登录类型 * result 登录状态 */ @Data public class MailMsg extends BaseBean { public String user; public String client_ip; public String source; public String loginName; public String mailSenderSourceIp; public String timestamp_time; public String timestamp_datetime; public String ip; public String clientType; public String result; public String version; public MailMsg() { } public MailMsg(String user, String client_ip, String source, String loginName, String mailSenderSourceIp, String timestamp_time, String timestamp_datetime, String ip, String clientType, String result, String version) { this.user = user; this.client_ip = client_ip; this.source = source; this.loginName = loginName; this.mailSenderSourceIp = mailSenderSourceIp; this.timestamp_time = timestamp_time; this.timestamp_datetime = timestamp_datetime; this.ip = ip; this.clientType = clientType; this.result = result; this.version = version; } @Override public boolean equals(Object o) { if (this == o) return true; if (!(o instanceof MailMsg)) return false; MailMsg mailMsg = (MailMsg) o; return getUser().equals(mailMsg.getUser()) && getClient_ip().equals(mailMsg.getClient_ip()) && getSource().equals(mailMsg.getSource()) && getLoginName().equals(mailMsg.getLoginName()) && getMailSenderSourceIp().equals(mailMsg.getMailSenderSourceIp()) && getTimestamp_time().equals(mailMsg.getTimestamp_time()) && getTimestamp_datetime().equals(mailMsg.getTimestamp_datetime()) && getIp().equals(mailMsg.getIp()) && getClientType().equals(mailMsg.getClientType()) && getResult().equals(mailMsg.getResult()) && getVersion().equals(mailMsg.getVersion()); } @Override public int hashCode() { return Objects.hash(getUser(), getClient_ip(), getSource(), getLoginName(), getMailSenderSourceIp(), getTimestamp_time(), getTimestamp_datetime(), getIp(), getClientType(), getResult(), getVersion()); } @Override public String toString() { return "{" + " 'user':'" + user + "'" + ", 'client_ip':'" + client_ip + "'" + ", 'source':'" + source + "'" + ", 'loginName':'" + loginName + "'" + ", 'IP':'" + mailSenderSourceIp + "'" + ", 'timestamp':'" + timestamp_time + "'" + ", '@timestamp':'" + timestamp_datetime + "'" + ", 'ip':'" + "'" + ", 'clientType':'" + clientType + "'" + ", 'result':'" + result + "'" + ", 'version':'" + version + "'" + "}"; } }
源代码已去掉敏感信息,地址:https://gitee.com/wangxm-2270/alarmCollectByFlink.git
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